I S A R C NAT L INST. OF STAND & TECH

PUBLICATIONS

AlllOt MMbEAfl iiii

19th INTERNATIONAL SYMPOSIUM

ON AUTOMATION

AND ROBOTICS"^

CONSTRUCTION

Nisr

National institute of Standards and Technology

Technology Administration

U.S. Department of Commerce NIST SP 989
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' At Boulder. CO 80303. Some elements at Boulder. CO.
NIST Special Publication 989

19th International Symposium on

Automation and Robotics in Construction

William C. Stone, Editor

Materials and Construction Research Division,

Building and Fire Research Laboratory,

National Institute of Standards and Technology,

Gaithersburg, MD 20899-8611

September 2002

U.S. Department of Commerce

Donald L. Evans, Secretary

Technology Administration

Phillip J. Bond, Under Secretary for Technology

National Institute of Standards and Technology

Arden L. Bement, Jr., Director
Certain commercial entities, equipment, or materials may be identified in this document in order to describe an experimental procedure or concept adequately. Such

identification is not intended to imply recommendation or endorsement by the National Institute of Standards and Technology, nor is it intended to imply that the

entities, materials, or equipment are necessarily the best available for the purpose.

National Institute of Standards and Technology Special Publication 989

Natl. Inst. Stand. Technol. Spec. Publ. 989, 557 pages (September 2002)

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MESSAGE FROM THE ORGANIZERS

Welcome to the 19* International Symposium on Automation and Robotics in Construction. We at the National

Institute of Standards and Technology (NIST) are honored to host this prestigious conference and hope that you

will find the technical sessions, demonstrations, and after-hours festivities to have made your trip to Gaithersburg,

Maryland not only worthwhile, but memorable.

This year the conference has 88 papers from 20 countries. There are nine sessions including conferencetraditional topics such as Design and Development of Construction Robotics; Control Systems for Construction

Equipment; Construction Process Modeling and Simulation; Automated Inspection and Maintenance

Management Systems; Design Practices to Facilitate Construction Automation; and Construction Information

Management Systems. NIST has long held the position that to effectively bnng automation to the average

construction site one had to do three additional things: 1) provide affordable, ubiquitous, and powerful sensors to monitor construction status; 2) to encourage the development of standard protocols for communication of site data

to the business managers, foremen, and machines that need the data; and 3) to provide compelling economic

evidence to facilities owners and operators that automation is worthwhile: m short that there is a positive return on investment. We are pleased this year to present three sessions aligned with these goals: Advanced Sensing

and Imaging Technologies - including LADAR, Photogrammetry, GPS, and 3D Object Recognition; Field Sensor

Data and Construction Process Integration Protocols; and Economic Assessment of Automation and Robotics

Technologies.

Talking about robotics, automation, autonomy, and tele-operation is one thing; seeing it and getting your hands on

it in person is quite a different experience. With that in mind we have set aside a portion of the conference for a senes of live demonstrations that include automated steel frame building construction; autonomous off-road

vehicle navigation; tele-operative control of a remote earthmoving machine; 3D interactive visualization of 4D

construction simulation; 3D laser radar scanning of construction sites; and wireless ad-hoc networks for authorization, location, and emergency notification of crafts and frades on construction sites. All of these live events will take place on the NIST campus.

Many people both within NIST and on the ISARC conference steering committee did an exceptional job of

making this conference happen. We would like to especially acknowledge:

James Albus, NIST

Roger Bostelman, NIST

Robert Chapman, NIST

Geraldine Cheok, NIST

Nicholas Dagalakis, NIST

Martin Fischer, Stanford Univ.

James Garrett, Carnegie Mellon Univ

Carl Haas, Univ of Texas, Austin

Tsai Hong, NIST

Richard Jackson, FIATECH

Maris Juberts, NIST

SoonWook Kwon, Univ of Texas,

Austin

H.S. Lew, NIST

Robert Lipman, NIST

Haitham Logman, Univ of Texas,

Austin

Alan Lytle, NIST

Rajmohan Madhavan, NIST

Elena Messina, NIST

Richard Norcross, NIST

Mark Palmer, NIST

Frederick Proctor, NIST

Kent Reed, NIST

Kamel Saidi, NIST

Clifford Schexnayder, Arizona State Craig Schlenoff, NIST

Michael Shneier, NIST

Iris Tommelem, UC Berkeley

for their efficient peer-reviews of the conference papers. Special thanks are due to Kathleen Kilmer, Patrice

Boulanger, and Kimberly Snouffer of the NIST Conference Program Office for their dedicated and helpful

assistance. The organizers also would like to extend their sincere thanks to Noel Raufaste for his extraordinarily

efficient assistance with keeping all the details in line and encouraging us to meet all the deadlines.

S. Shyam Sunder

General Chair

William C. Stone

Technical Chair

Stephen Caviffman

Secretariat

111

ABSTRACT

This publication is the Proceedings of the 1 9 International Symposium on Automation

and Robotics in Construction (ISARC). The symposium was held at the National Institute

of Standards and Technology, Gaithersburg, Maryland during 23-25 September 2002.

The Proceedings include the technical program, list of Board of Directors, Message from

the Organizers, and the 88 technical papers from 20 countries authored for this

international meeting.

The manuscripts were presented during nine Sessions: Construction Information

Management Systems; Construction Process Modeling and Simulation; Design Practices

to Facilitate Construction Automation; Design and Development of Construction

Robotics; Economic Assessment of Automation and Robotics Technologies; Field Sensor

Data and Construction Process Integration Protocols; Automated Inspection and

Maintenance Management Systems; Control Systems for Construction Equipment;

Advanced Sensing and Imaging Technologies.

KEYWORDS: Advanced sensing; automation; construction; construction equipment;

construction process integration; control systems; 4D construction simulation; GPS;

imaging technologies; information management; inspection; LADAR; robotics;

simulation; 3D Object Recognition

CONTENTS

MESSAGE FROM THE ORGANIZERS Mi ABSTRACT v ACKNOWLEDGEMENTS xii

MANUSCRIPTS ....1

SESSION 1 CONSTRUCTION INFORMATION MANAGEMENT SYSTEMS

Collaborative Fire Protection Engineering Based on Software Agents, Uwe Rueppel,

Darmstadt University of Technology 3

Strategies for Realizing the Benefits of 3D Integrated Modeling of Buildings for the AEC

Industry, C. Eastman, R. Sacks, G. Lee, Georgia Institute of Technology 9

The Role of the CIMsteel Integration Standards in Automating the Erection and Surveying

of Structural Steelwork, K. Reed, National Institute of Standards and Technology 15

Beyond Webcam: A Site-Web-Site for Building Construction, S. Nuntasunti and L. Bernold, North Carolina State University 21

Developing a Construction Integrated Management System, Y. Shiau, M. Wang, T. Tsai,

and W. Wang, Chung-Hua University, Taiwan 27

Use Questionnaire and AHP Techniques to Develop Subcontractor Selection System, Y. Shiau, T. Tsai, W. Wang, and M. Huang, Chung-Hua University, Taiwan 35

Development of Electronic Acquisition Model for Project Scheduling (e-AMPS) Using

Java-XML, W. Lin, National Taiwan University 41

An Automated Selecting Subcontractor Model in E-Commerce, P. Lin, Feng-Chia

University, Taiwan 47

Mobile 3D Visualization for Construction, R. Lipman, National Institute of Standards and

Technology 53

Digital Archival of Construction Project Information, D. Latimer and C. Hendrickson,

Carnegie Mellon University 59

E-Work: The Next Iteration in Construction Information Materials Management Systems,

D. Castro-Lacouture and M. Skibniewski, Purdue University 65

Capitalizing on Early Project Opportunities to Improve Facility Life-Cycle Performance, C. Kam, M. Fischer, R. Hanninen, S. Lehto, and J. Laitinen, Stanford University 73

SESSION 2 CONSTRUCTION PROCESS MODELING AND SIMULATION

Dynamic Change Management for Fast Tracking Construction Projects, M. Park, National

University of Singapore 81

AUTM0D3: A Planning Tool for Modular Building System, V. Padron, O. Cardenas, R.

Diez, M. Abderrahim, and C. Balaguer, Carlos III University of Madrid 91

Simulation-Facilitated Factor-Based Approach for Cost Correlation Evaluation, W. Wang,

National Chiao-Tung University 97

Criteria of Taking Decisions at Technical Operation of Building Machinery in Conditions of

the Construction Plant, A. Bulgakow, A. Drownikow, and V. Perschin, Technical

University of Munich and South Russia State Technical University 103

Database Synchronization Technology for Multi-Project Schedule Coordination, H. Choo

and I. Tommelein, University of California, Berkeley 109

Project Performance vs. Use of Technologies at the Work Function Level, J. O'Connor

and L. Yang, University of Texas at Austin ...117

vii
Development of an Information Model to Enhance Integration and Coordination in the

Construction Projects, A. Cabaliero, S. Ahmed, S. Azhar, and M. Barcala, Florida

International University 123

Development of an Integrated Cost Estimation and Cost Control System for Construction

Projects, S. Azhar, S. Ahmed, and A. Cabaliero, Florida International University 129

Automated DSS for Lighting Design of Nighttime Operations in Highway Construction

Projects, K. El-Rayes and K. Hyari, University of Illinois at Urbana-Champaign 135

SESSION 3 DESIGN PRACTICES TO FACILITATE CONSTRUCTION

AUTOMATION

De Bolder, an Unusul Example of Off-Site Construction, G. Maas and B. van Eekelen,

Eindhoven University of Technology 143

Automated Data Acquisition and Planning of Highway Construction, A. Hassanein and O.

Moselhi, Concordia University 149

Asphalt Quality Parameters Tracability Using Electronic Tags and GPS, F. Peyret and R. Tasky, Laboratoire Central des Ponts et Chaussees 155

Monitoring Construction Equipment for Automated Project Performance Control, R. Sacks, R. Navon, A. Shapira, and I. Brodetsky, Georgia Institute of Technology

and Technion-lsrael Institute of Technology 161

Experiences with the Design and Production of an Industrial, Flexible, and Demountable

(IFD) Building System, F. van Gassel, Eindhoven University of Technology 167

FutureHome-a Prototype for Factory Housing, R. Wing and B. Atkin, Imperial College of Science, Technology & Medicine and Atkin Research & Development Ltd 173

Automation in Building Design with Spatial Information, H. Nguyen and A. Oloufa, North

Dakota State University and University of Central Florida 179

Genetic Algorithms for Accessing Engineering Performance, L. Chang and L. Zhang,

Purdue University 185

Mixed Reality Benefits for Design Perception, P. Dunston, X. Wang, M. Billinghurst, and

B. Hampson, Purdue University, University of Washington, and The McKinstry

Company 191

Automation Consideration During Project Design, M. Hewitt and J. Gambatese, Oregon

State University 197

SESSION 4 DESIGN AND DEVELOPMENT OF CONSTRUCTION ROBOTS

A Tool to Improve Efficiency in Large Scale Manufacturing, R. Bostelman, W.

Shackleford, F. Proctor, J. Albus, and A. Lytle, National Institute of Standards

and Technology 205

Remote Control of Machines for Removal of Damages Being Result of Disasters, Wars,

and Terrorist Attacks, A. Bartnicki, F. Kuczmarski, T. Przychodzien, A. Typiak,

and J. Wrona, Military University of Technology 21

1

Advancements in Tele-Robotic Pipelaying, L. Bernold and B. Li, North Carolina State

University 217

Motion Planning Taking Into Account the Dynamic Model of Vehicles: Application to the

Compactor, C. Lemaire, P. Vandanjon, M. Gautier, and F. Peyret, Laboratoire

Central des Ponts et Chaussees 223

Fagade Cleaning Robot for the Skyscraper, T. Bock, A. Bulgakow, and S. Ashida,

Technical University of Munich 229

Development and Application of Automated Delivery System for Finishing Building

Materials, D. Atsuhiro, H. Koji, K. Tomoya, and S. Takashi, Obayashi Corporation 235

Unmanned Construction System: Present Status and Challenges, Y. Ban, Advanced

Construction Technology Center 241

Report of the NIST Workshop on Automated Steel Construction, A. Lytle, K. Saidi, W.

Stone, and J. Gross, National Institute of Standards and Technology .' 247

Error Modeling for Automated Construction Equipment, Y. Cho, C. Haas, S. Sreenivasan,

and K. Liapi, University of Wisconsin and University of Texas at Austin .' 255

viii
Development of a Robotic Structural Steel Placement System, A. Lytle, K. Saidi, and W.

Stone, National Institute of Standards and Technology 263

Robots for Spacing of Wood, T. Bock, D. Parshin, T. Souetina, and A. Boulgakov,

Technical University of Munich, Rostov State Building University, and Moscov\/

Building University 269

SESSION 5 ECONOMIC ASSESSMENT OF AUTOMATION AND ROBOTICS

TECHNOLOGIES

An Economic Assessment of Selected Integration and Automation Technologies, R. Chapman, National Institute of Standards and Technology 275

A Micro Level Analysis of the Relationship Between Changes in Equipment Technology

and Wages in the U.S. Construction Industry, P. Goodrum and M. Gangwar,

University of Kentucky 281

Generating and Maintaining Activity-Based Cost Estimates with Feature-Based Product

Models, S. Staub-French and M. Fischer, University of British Columbia and

Stanford University 287

Construction Zone Generation Mechanisms and Applications, R. Akbas and M. Fischer,

Stanford University 293

Assembly + Disassembly of Interior Wall, A. Hanser, Technical University of Munich 299

SESSION 6 FIELD SENSOR DATA AND CONSTRUCTION PROCESS

INTEGRATION PROTOCOLS

Standardization of Data Flows on Earthworks and Road Pavement Sites Using

Information Systems, F. Peyret, Laboratoire Central des Ponts et Chaussees 305

Parts and Packets Unification for Construction Automation and Robots, T. Umetani, T.

Aral, Y. Mae, K. Inoue, and J. Maeda, Osaka University and Shimizu Corporation 31

1

An UML-XML-RDB Model Mapping Solution for Facilitating Information Standardization

and Sharing in Construction Industry, I. Wu and S. Hsieh, National Taiwan

University 317

Using Customized Navigational Models to Deliver more Efficient Interaction with Mobile

Computing Devices on Construction Sites, J. Reinhardt, B. Akinci, and J. Garrett,

Carnegie Mellon University 323

SESSION 7 ADVANCED SENSING AND IMAGING TECHNOLOGIES

Performance of Artificial Intelligence Approach on Bridge Coating Assessment, P. Chen

and L. Chang, Nanyang Technological University and Purdue University 331

The Application of 3D Scanner in the Representation of Building Construction Site, N.

Shih, National Taiwan University of Science and Technology 337

Data Interpretation from Leuze RotoScan Sensor for Robot Localisation and Environment

Mapping, D. Steward, S. Quayle, K. Zied, and C. Pace, Lancaster University and

University of Malta 343

Experiences with Point Cloud Registration, C. Witzgall and G. Cheok, National Institute of Standards and Technology 349

Human-Assisted Object Fitting to Sparse Range Point Clouds for Rapid Workspace

Modeling in Construction Automation, S. Kwon, K. Liapi, C. Haas, S. Sreenivasan, and J. McLaughlin, University of Texas at Austin and Los Alamos

National Laboratory 357

Reconstructing Images of Bar Codes for Construction Site Object Recognition, D. Gilsinn, G. Cheok, and D. O'Leary, National Institute of Standards and Technology and

University of Maryland 363

Artificial Intelligence Based Quality Control of Aggregate Production, H. Kim, C. Haas,

and A. Rauch, University of Texas at Austin 369

A MEMS Transducer for Ultrasonic Flaw Detection, A. Jain, D. Greve, and J. Oppenheim,

Carnegie Mellon University 375

ix
I

utilizing Radio Frequency Identification on Precast Concrete Components - Supplier's

Perspective, B. Akinci, M. Patton, and E. Ergen, Carnegie Mellon University 381

MEMS Application in Pavement Condition Monitoring-Challenges, N. Attoh-Okine and S. Mensah, University of Delaware 387

Towards the Ultimate Construction Site Sensor, W. Stone and M. Juberts, National

Institute of Standards and Technology 393

SESSION 8 CONTROL SYSTEMS FOR CONSTRUCTION EQUIPMENT

A Cost-Effective Positioning Solution for Asphalt Rollers Based on Low-Cost DGPS

Receivers, J. Jurasz and K. Kley, University of Karlsruhe 403

On-Board Data Management Structure for Advanced Construction Machine Support, J. Jurasz, A. Ligier, A. Horn, and J. Wendebaum, University of Karlsruhe 409

Offline Path Planning of Cooperative Manipulators Using Co-Evolutionary Genetic

Algorithm, M. All, N. Babu, and K. Varghese, Indian Institute of Technology and

Arizona State University 415

Model for Automated Road-Construction Control, R. Navon, Y. Shpatnisky and E. Goldschmidt, National Building Research Institute, Israel Institute of Technology 425

Force Sensor by Driving Hydraulic Cylinders: Identification of Inertial Parameters and

Tests, F. Malaguti and S. Zaghi, CNR-Cennoter 431

Intelligent Driving Control System-Automated Driving Management and Control System

Using Optimum Control Theory, T. Awata, K. Yoshida, and H. Hino, Nippon

Telegraph and Telephone Corporation 437

Automatic Steering System for Rotary Snow Removers, H. Hirashita, T. Aral, and T. Yoshida, Public Works Research Institute 443

Adaptive Control of a Construction Manipulator, V. Gradetsky, M. Rachkov, and M.

Pushkin, Russian Academy of Sciences and Moscow State Industrial University 449

Just-in-Time Continuous Flight Auger Piles Using an Instrumented Auger, N. Mure, J. Scott, D. Seward, S. Quayle, C. Clayton, and M. Rust, Stent Foundations

Limited, Lancaster University, and University of Southampton 455

GPS-Based Wireless Collision Detection of Construction Equipment, A. Oloufa, M. Ikeda,

and H. Oda, University of Central Florida and Fujita Corporation 461

Prototype Implementation of an Automated Structural Steel Tracking System, K. Furlani, D. Latimer, D. Gilsinn, and A. Lytle, National Institute of Standards and

Technology 467

The Efficiency of a 3-D Blade Control System in the Construction of Structure Layers by

Road Grader-Automated Design-Build of Road Construction in Finland, R.

Heikkila and M. Jaakkola, University of Oulu 475

Optimal Control of an Excavator Bucket Positioning, E. Budny, M. Chlosta, and W.

Gutkowski, Institute of Mechanised Construction and Rock Mining 481

Automated Construction Using Contour Crafting - Applications on Earth and Beyond, B. Khoshnevis and G. Bekey, University of Southern California 489

Rapid Human-Assisted Creation of Bounding Models for Obstacle Avoidance in Construction, J. McLaughlin, C. Haas, K. Liapi, S. Sreenivasan, and S. Kwon,

Los Alamos National Laboratory and The University of Texas at Austin 495

Computer Technologies in Construction Robots Control, T. Bock, D. Parshin, R. Neudorf,

and A. Bulgakow, Technical University of Munich and Rostov State Building

University 501

Equipment Operator Training in the Age of Internet2, L. Bernold, J. Lloyd, and M. Vouk,

North Carolina State University ' 505

Terrain Aided Localization of Autonomous Vehicles, R. Madhavan, National Institute of Standards and Technology 511

Monitoring of the Boring Trajectory in Underground Channel, T. Bock, A. Bulgakow, D.

Krapivin, S. Aleksyuk, and S. Pritchin, Technical University of Munich and South

Russia State Technical University 51

9

X
SESSION 9 AUTOMATED INSPECTION AND MAINTENANCE

MANAGEMENT SYSTEMS

A Multi-Sensory Approach to 3-D Mapping of Underground Utilities, L. Bernold, L. Venkatesan, and S. Suvarna, North Carolina State University 525

Automated Inspection of Utility Pipes: A Solution Strategy for Data Management, T. Shehab-Eldeen and O. Moselhi, Concordia University 531

A Concept of the Robotoid Manager with AR, T. Bocl< and S. Ashida, Technical

University of Munich 537

Representation and Integration of As-Built Information to IPC Based Product and Process

Models for Automated Assessment of As-Built Conditions, B. Akinci and F. Boukannp, Carnegie Mellon University 543

A Case Study: Using the Wearable Computer in the Construction Industry, S. Fuller, Z. Ding, and A. Sattineni, Auburn University 551

The Value of Handheld Computers in Construction, K. SaidI, C. Haas, and N. Balli, University of Texas at Austin 557

Situation-aware Interface Design: An Interaction Constraints Model for Finding the Right

Interaction for Mobile and Wearable Computer Systems, C. Burgy and J. Garrett,

Carnegie Mellon University 563

Disclaimer

Certain trade names and company products are mentioned in the text or identified in an

illustration in order to adequately indicate a manufactured product or specify an

experimental procedure or equipment used. In no case does such identification imply

recommendation or endorsement by the National Institute of Standards and Technology,

nor does it imply that the products are necessarily the best available for the purpose.

xi
ACKNOWLEDGEMENTS

Symposium Host

The Building and Fire Research Laboratory, National Institute of Standards and Technology

Symposium Sponsor

The International Association for Automation and Robotics in Construction

Officers and Directors

Prof. Carlos Balaguer (Spain) - President

Prof. Miroslaw Skibniewski (USA) - Immediate Past-President

Prof. Thomas Bock (Germany) - President-Elect

Prof. Eugeniusz Budny (Poland)

Prof. Naruo Kano (Japan)

Prof. Ger Maas (Netherlands)

Prof. Osama Moselhi (Canada)

Prof. Derek Seward (Great Britain)

Prof. Wolfgang Poppy (Germany)

Dr. M.T. Wang (Taiwan)

Dr. Ronie Navon (Israel) Dr. Carl Haas (USA)

Dr. N. Pai (Taiwan)

Mr. Tetsuji Yoshida (Japan)

Mr. Par Ahman (Sweden)

Mr. Francois Peyret (France)

Mr. Hannu Koski (Finland)

Mr. Johnatan O'Brien (Australia)

Mr. Fiorenzo Malaguti (Italy)

Symposium Co-Sponsors

Automation in Construction, An International Journal, Elsevier

Center for Integrated Facilities Engineering, Stanford University

Construction Engineering and Management Division, Purdue University

Construction Industry Institute Construction Institute, American Society of Civil Engineers

Continental Automated Building Association

Del E. Webb School of Construction, Arizona State University

FIATECH Consortium

Institute for Research in Construction, National Research Council, Canada

International Alliance for Interoperability, North America

Lean Construction Institute

xii
19 ISARC Steering Committee

Dr. Sherif Barakat, Institute for Research in Construction, National Research Council of Canada

Dr. Leonhard E. Bemold, North Carolina State University, Center for Construction Technology

and Integration

Mr. Stephen A. Cauffrnan, Vice Chair (Secretariat), National Institute of Standards and

Technology

Lt. Gen. Kenneth E. Eickmann (USAF, Retd.), Construction Industry Institute Dr. John M. Evans, National Institute of Standards and Technology

Dr. Martin Fisher, Stanford University, Center for Integrated Facilities Engineering

Ms. Karen M. Furlani, National Institute of Standards and Technology

Dr. James H Garrett, Jr., Carnegie Mellon University

Dr. Francois Grobler, U.S. Army Engineer Research and Development Center, International

Alliance for Interoperability - North America

Dr. Carl T. Haas, University of Texas at Austin, Construction Automation Laboratory

Dr. Miriam Heller, National Science Foundation

Dr. Richard H.F. Jackson, FIATECH Consortium

Dr. Ronie Navon, Technion - Israel Institute of Technology, Construction Automation Laboratory

Dr. Francois Peyret, Laboratoire Central des Fonts et Chaussees, France

Dr. Jeffrey S. Russell, University of Wisconsin-Madison, Construction Institute/American

Society of Civil Engineers

Dr. Clifford J. Schexnayder, Arizona State University, Del E. Webb School of Construction

Dr. Miroslaw Skibniewski, Purdue University, International Association for Automation and

Robotics in Construction

Dr. William C. Stone, Vice Chair (Proceedings Editor), National Institute of Standards and

Technology

Dr. S. Shyam Sunder, Chair, National Institute of Standards and Technology

Dr. Iris D. Tommelein, University of California at Berkeley, Lean Construction Institute Dr. Richard L. Tucker, University of Texas at Austin, Center for Construction Industry Studies Dr. John G. Voeller, Black & Veatch Holding Company

xiii

SESSION 1

CONSTRUCTION INFORMATION

MANAGEMENT SYSTEMS

1

Collaborative Fire Protection Engineering Based on Software Agents

by

Uwe Rueppel

ABSTRACT: This paper presents a new approach with software agents to support

the task of preventive fire protection engineering. Agents are stationary or mobile

software components to support the user in his planning tasks according to their specific design. Agents can act autonomously within their environment, which means that they can solve problems without the need of control through a human

being or another system. In order to react to modifications of the environment

agents observe their environment continuously and react adequately to modifications. To reach a result it is necessary for autonomous agents to react particularly in a goal-oriented way. The purpose of an agent system in the area of

fire protection engineering is to organize a distributed problem solution by many

agents representing adaptive experts. Using available object-oriented, net-enabled

models of standard applications and based on the technology of the software

agents, a platform for collaborative fire protection engineering is designed. Local

service-agents provide necessary information in a collaboration platform. By

communication between these local service-agents and mobile verifying-agents the

appropriate information can be processed to verify the fire protection model of a

building.

KEYWORDS: Collaboration platform; fire protection engineering; information

technology; software agents;

1. INTRODUCTION the communication, collaboration and control processes, especially in the area of fire protection engineering. Most software

solutions are based on proprietary solutions

with their specific technical model.

Collaboration is often implemented as a

centralized client-server architecture. Model

information in these client-server

architectures are static with the consequence

that every completion of a new model

requires the definition of new interfaces and

implementations in every module [1].

Fire protection engineering is a part of the

building design process in civil engineering and

consists of the cooperation of experts in multiple

disciplines. Consistent cooperation of engineers

in different fields is the requirement for high

product quality, for optimal and short

development with a minimum of investment

costs. The development process in building

engineering is strongly assigned by creating

unique buildings. Software methods and tools in building engineering do not sufficiently support

Professor for Computer Science in Civil Engineering

Darmstadt University of Technology

Petersenstrasse 13, 64287 Darmstadt, Germany

Tel.: +49 (0)6151 16 34 44

Fax: +49(0)6151 16 55 52

rueppel@iib.tu-darmstadt.de

3
2. Fire Protection Engineering

In addition to the described problems in collaboration, a great number of codes and

regulations for fire protection models of

buildings have to be evaluated. In Germany

every state has different fire protection codes

and a great number of special building

regulations (for multi-storey buildings, hospitals,

etc.) (see Figure 1). To consider these complex

standards completely and without errors during

the design process is a challenge in collaborative

fire protection engineering. Fire protection

models therefore are often inconsistent.

German codes define the fire protection needs

overall. There are different parts of fire protection engineering:

Organizational;

Operational;

Defensive; and

preventive.

The focus of the presented approach is the

preventive fire protection engineering. This part

has to be recognized during the whole planning

and construction phase and is the basis for the

defensive fire protection. The goals in preventive fire protection engineering are: prevention of fire; containing the fire using fire compartments;

developing an infrastructure for extinguishing the fire (fire extinguisher, sprinkler

etc.)

and developing an infrastructure for rescue. As it is shown in Figure 2, these preventive fire protection elements are represented by or have

strong relationships to building elements.

Normally the fire protection model is developed

by architects as a part of their building design.

Based on this draft, other planners have to complete the detailed planning and advance the

fire protection model continuously (see Figure

3). That means, that for example a structural engineer finds restrictions due to fire resistance

demands in the choice and design of the

stmctural elements. The technical services for # facilities have to be designed according to the

fire protection model, so that planned rescue

routes are free of smoke from flammable

components [2]. After some great fire disasters

in Europe, the compliance and inspection of fire

protection rules are taken very seriously.

With regard to the devastating consequences

to people living and working in buildings, it

is necessary to include the fire protection

concepts very early in the building design

process being conducted by the all specific

planners involved.

In order to support the disciplinary processes

of the fire protection model evolution in a

distributed environment, the integration of all participants in the entire planning process is necessary. Therefore data, methods and

knowledge of the partial models are to be

coupled for collaboration, while taking into

consideration that the planners are spatially

distributed. The concept of collaborative

work of distributed planners must support

sequential, parallel and iterative planning

processes within an integrated information

platform.

3. Software Agents

An agent is one that is authorized to act for another. Agents possess the characteristics of

delegacy, competency and proactive

behaviour. Delegacy means the discretionary

authority to autonomously act on behalf of

the client. Actions include making decisions,

committing resources, and performing tasks. Competency is the capability to effectively

manipulate the problem domain environment

to accomplish the prerequisite tasks. Competency includes specialized communication proficiency. Proactive behaviour is the

ability to adapt behaviour to optimize

performance in an often non-stationary

environment in responsive pursuit of the

goals of the client.

A software agent is an artificial agent which

operates in a software environment. Software

environments include operating systems,

computer applications, databases, networks

and virtual domains. Delegacy for software

agents means that they stay resident or

persistent as background processes after being launched. By making decisions and

acting on their environment independently.

4
software agents reduce human workload by

generally only interacting with their end-clients

when it is time to deliver results. Competency

within a software environment requires

knowledge of the specific communication

protocols of the domain. Protocols such as SQL

for databases, HTTP for the WWW and API

calls for operating systems must be implemented

into the software agents. Proactive behaviour for

software agents is generally limited to providing

control options and the generation of status reports that require human review.

Mobile Agents, also known as travelling agents,

will shuttle their code and state among

resources. This often improves performance by

moving the agents to where the data reside

instead of moving the data to where the agents

reside. The alternative typical operation involves

a client-server model. In this case, the agent, in the role of the client, requests that the server

transmit volumes of data back to the agent to be

analyzed. Oftentimes the data must be returned

by the agent to the server in a processed form.

With mobile agents load-balancing can be

achieved by distributing agents over a finite number of computational resources. Some

mobile agents are self-distributing, seeking and

moving to agent platforms that can offer the

higher computational resources at lower costs. Further a complex problem solution can be

achieved by dividing the problems into less complex sub-problems addressed by

collaborating agents.

Collaborative agents interact with each other to share information or barter for specialized

services to effect a synergism. While each agent

may uniquely speak the protocol of a particular

operating environment, they generally share a common interface language which enables them

to request specialized services from other agents

as required. This means that agents have to communicate [3]. The communication and

cooperation with other agents, machines or people is realized by specific languages as KQML [4] [5], ACL [6] or Tel [7].

4. Fire Protection Engineering with Software

Agents

These qualities of agent systems are utilized for the evolution of an integrated fire protection model. The information of the fire protection model is determined from two

different sources. On the one hand, fire protection relevant rules must be accessible

to the system. On the other hand, the

information of building product models must

be available. The fire protection model must

be adapted to the different views of the %

planners within the collaborative building

design and relevant information must be

evaluated within the agent-based platform

[8]. The system architecture of the

collaboration platform for preventive fire protection engineering is shown in Figure 4.

The determination and access of the fire protection information are designed as a mobile verifying-agent. The architect designs

a fire protection model on the basis of his

building design in his working environment.

He defines the elements, relevant, for

preventive fire protection. A fire protection

application for AutoCAD ADT was

developed for this purpose. On completion

of a design, the architect publishes the fire protection model on his agent-platform. For

this purpose a fire protection- XML-interface

for AutoCAD ADT was developed. The

verifying-agents are then available on the server with the fire protection model in order

to support the collaboration of all other

planners. On the one hand, every planner can

retrieve the fire protection model from the

server in the form of mobile agents and

check his own models for consistency with

the fire protection model. The planner is supported by the agent in the form of a check

list. A fire protection inspection can occur at the time the agent gets all information

needed. On the other hand, the architect can

verify the released technical information of

the planners for consistency with the fire protection model by mobile verifying-agents.

For this purpose he defines the run places for

the verifying-agents representing the

cooperation partners. The mobile verifyingagent determines the necessary information

from every cooperation partner. This can ^

come about automatically, when on the one hand a link is already defined between the

corresponding technical model (e.g. building

services model or structural model [8]) and

5
the fire protection model. On the other hand, a communication of the responsible planner can

be initiated to link the information.

Each planner makes his model information

available to other participants in the design

process through a local service-agent. This

service-agent has control over the specific model

information and can supply the verification. The

protection of the planner specific information is guaranteed by encapsulating it within the

interface of the service-agent. Other users cannot

manipulate the information since the

encapsulation is controlled completely by the

local service-agent.

5. CONCLUSIONS

This paper described how the technology of

software agents enables the integration of

different technical models to support

collaborative fire protection engineering. A new

methodology was developed to verify fire protection models in a distributed environment

by means of software agents. This approach

integrates the information of building design,

structure and technical services with knowledge

and rules of German fire protection codes (see

Figure 4). The communication between the

integrated fire protection model and local technical models of the planners is integrated

into the system. The concept allows the

integration of fire protection regulations into the

planning processes during early design stages.

The new software approach enables

collaborative engineering with fire protection

models and leads to an increase of quality and

consistency in the resulting preventive fire protection design system [8] [9].

6. REFERENCES

[1] Rueppel, U.; Meissner, U.: Cooperative

Structural Engineering in Distributed Systems.

In: Proceedings of the 8"' International

Conference on Computing in Civil & Building

Engineering, ISBN 0-7844-0513-1, P. 504-509,

Stanford University, USA 2000.

[2] Loebbert, A., Pohl, K.D. and Thomas, K.- W.: "Brandschutzplanung fuer Architekten

und Ingenieure (Fire Protection Engineering

for Architects and Engineers)", Verlag

Rudolf Mueller, Koeln, Germany, 2000.

[3] Brenner, W., Zamekow, R. and Wittig,

H.: "Intelligente Softwareagenten (Intelligent

Software Agents)", Springer Verlag, Berlin,

Germany, 1998.

[4] Finin, T., Fritzson, R., McKay, D. and

McEntire, R.: "KQML as an Agent

Communication Language", In: Proceedings

of the third International Conference on

Information and Knowledge Management

(CIKM'94), ACM Press, USA 1994.

[5] Labrou, T. and Finin, T.: "A Proposal for a new KQML Specification", In: Technical

Report TR CS-97-03, University of

Maryland, USA, 1997.

[6] Fipa: "ACL - Agent Communication

Language", Foundation for Intelligent

Physical Agents (FIPA) specifications

homepage. Available online at http://www.fipa.org, 06-2002.

[7] Oustershout, J.K.: "Tel and the Tk

Toolkit", Addison Wesley, New York, USA,

1994.

[8] Meissner, U.; Rueppel, U.; Petersen, M.:

Cooperative Management of Product Models

in the Planning Process of Structural

Engineering. In: Proceedings of the

International Conference for Computational

Engineering Science (ICES2K), ISBN 0-

9657001-3-5, P. 240 - 245, Los Angeles,

USA 2000.

[9] Rueppel, U.; Theiss, M.: Cooperative

Developing of Building Projects in Computer

Networks. In: Proceedings of the

International Conference for Computational

Engineering Science (ICES2K), ISBN 0-

9657001-3-5, P. 1182- 1187, Los Angeles,

USA 2000.

6
Mall

Figure 1 : Fire Protection Regulations in Germany

Fire Protection Elements Building Elements

Fire Spread Clearance Areas

Fire Compartment Material

Fire Resistance

Escape Route

Slabs, Walls

Doors

Fire Extinguisher Stairs, Corridors

Smoke Extract Windows

Figure 2: Fire Protection and Building Engineering

7
r Cliertt 1 Architect | 1 Fire Expert | 1 Fire Dept. | 1 Authority | 1 Planner |

0)w

(0

1 o

3 is

III c

!^

0) Q

Motivation

0)w

(0 £

0>CL

.£ c 2 .2 3 a

m g

cou

C C 0)

tQ Q.

Building Type

No. of users

Local fire regulations ? Land use act |?

Architectural

Model I FP Model

Result

i

Dispute about exception

or special pnethods

Fire Protection

Model I

Architectural

Model !

I Building applicption with FPI\/| |~|

BuHding permit i Planning basics

Checkiup of detailed planning

Figure 3: UML Diagram for Fire Protection Planning

Figure 4: Platform Architecture for Collaborative Fire Protection Engineering
Strategies for Realizing tlie Benefits of 3D Integrated Modeling of Buildings

for the AEC Industry

by

Chuck Eastman*, Rafael Sacks* Ghang Lee'

ABSTRACT: We explore the reasons why advanced information technology applications

have not been adopted by the AEC industry. Within the industry, however, some sectors have made significant moves toward adoption of advanced IT. By examining these areas of

success, we propose a framework for the incremental conversion of the AEC industry to

fully incorporate advanced IT. KEYWORDS: knowledge-based applications, building models, information technology

innovation, construction automation.

1. INTRODUCTION

The business models in each industrial domain

provide different contexts for information

technology innovation. Here, we focus on the

building design and construction part of the

Architecture, Engineering and Construction

(AEC) industry. The building industry custom

designs, engineers and constructs projects on

varied construction sites. The components are

either procured off-the-shelf, made-to-order or

fabricated on-site. A variety of design and en- gineering specialists collaborate on a project,

each bringing specific expertise and employing

specialized software. In the US, the value of all construction work is 845 billion dollars (Economic Census, 2000), making it one of the

largest industries in the nation.

Digital knowledge-based models of buildings

have been advocated as the base representation

for work in the construction industry for over

twenty-five years (Eastman, 1999, Chapter 2). Here, we use "knowledge-based building models" as a shorthand reference for the integrated use of several technologies: (1) multiple het- erogeneous computer applications allowing

three dimensional representation, design,

analysis and management of the systems and

components that make up the proposed building, all incorporating significant domain

knowledge, (2) the backend integration of

workflow using one or more building product

models; (3) associated Internet links to material supplies, delivery planning, operational

controls and other such services needed for the

building's procurement, fabrication and operation, and (4) expanded automation of all as- pects of work, including design automation,

automation of built-to-order components, and

automation of on-site fabrication. We consider

these technologies together to define current

best practice use of advanced Information

Technology (IT).

Although serious building model efforts have

been carried on for ten years (e.g., CIMsteel -

CIS/2 2001), national and international efforts

in moving the AEC industries toward the use

of advanced information technologies has

shown little progress. Virtually all buildings

designed today still rely on two-dimensional

(2D) drawings as their principal representation.

This is not to say that there has been no movement; rather, the particular conditions in the construction industry have not allowed it to proceed as fast as other product-oriented domains, such as manufacturing, electronics,

aerospace and other industrial areas. It has also not even progressed as fast as art or entertainment industries, such as television, motion

pictures, or music production.

This paper reviews why there has been so little movement and outlines a strategy for the in- cremental conversion of the AEC industry to the use of advanced IT applications. We build

upon two examples, involving the structural

* Professor and Director of the College of Architecture Ph.D. Program, and Professor of Computing. Georgia Institute of Technology, Atlanta, GA 30332-0155; chuck.eastman@arch.gatech.edu

** Research Faculty, College of Architecture Ph.D. Program, Georgia Institute of Technology, Atlanta, GA 30332-0155;

rafael.sacks@arch.gatech.edu *** Ph.D. research Assistant, College of Architecture Ph.D. Program, Georgia Institute of Technology, Atlanta, GA 30332-

0155; ghang.lee@arch.gatech.edu

9
steel and precast concrete sectors of the building industry. The issues and strategy may be

useful for other industries, beyond AEC.

2. WHY THE CONSTRUCTION

INDUSTRY HAS LAGGED

The commonly held assumption why building

design, engineering and construction have not

utilized knowledge-based building models is due to fragmentation. The construction industry has traditionally been craftsman-oriented,

with many small participants. There are 656,000 construction-related firms in the

United States alone. Of these, over 62 percent

have fewer than 4 employees, while less than 1 percent have more than 100 (ICAF, 2000).

Each firm carries out only a few steps of an

increasingly complex process. No one organization has as much as five percent of construction dollars. These many organizations come

together to execute construction projects in a very competitive setting, with each project

typically involving a change of participants.

Within this fragmented setting, 2D architectural and engineering drawings have evolved

over hundreds of years as the basic representation and physical artifact used by all construction industry participants. Business practices of

all construction-related firms, financial and

insurance institutions, standards and codes and

reference materials are organized around 2D

drawings and associated formatting conventions. However, it is generally recognized that

it is not possible to verify the consistency of

2D drawings or to derive all the needed ge- ometry for design and production automation.

These are only possible with 3D modeling.

The very broad embedding of 2D drawings,

combined with the fragmentation of the participants, is assumed to result in the situation

where no single participant and no single project have enough economic impact to justify the

investment - in technology purchases, in learning and in changing business practices -

to convert to knowledge-based building models. No organization has the power to force

conversion of the others (seemingly, not even

the US government).

The potential economic benefits of knowledgebased building models are varied in nature: some occur in isolated construction processes

(e.g. CNC production of made-to-order components), while others depend on improving

the process as a whole (e.g. reduction of re- work resulting from errors). The motivations

cited in most research have emphasized longterm system benefits without identifying

measurable short-term payoffs (Moreau and

Back 2000, Griffis and Sturts 2000). Because no one party to the building process seems to benefit, but the process as a whole improves, it

is argued that the owners and clients of buildings are the beneficiaries and should financially support this IT transition. However, no

effective business model has been implemented based on this premise.

We accept these conditions, in general, and

conclude that IT technology innovation must

evolve based on local benefits, not industrywide ones.

3. SECTOR-LEVEL ADOPTION OF

ADVANCED IT

Given the complex conditions cited above, it is apparent why current strategies have not moved the construction industry toward

knowledge-based building models; there is no

one business entity or financial incentive large

enough to move the industry as a whole. (Griffis et al. 1995) and production (HATECH

2001) indicates that the potential exists for significant process improvements in construction

itself, and that these process improvements

require IT support.

Despite this state of affairs, certain sectors of

the construction industry have made strong

steps to implement knowledge-based building

models within their sector. We review two:

structural steel and precast concrete.

Structural Steel

Structural steel fabrication and erection is a

significant sector within the construction in- dustry, with 8.5 billion dollars of production

(Economic Census, 2001) and half a million

workers (US Dept. of Labor 1999). Steel is used in a wide range of structures, including

buildings, industrial facilities and process

plants. Engineering companies, steel fabricators and structural engineers, as well as architects, are involved in aspects of the building

structural steel sector. The processes in this

10
sector include designing, detail engineering,

prefabricating of pieces, shipping and erection

of the pieces on the construction site.

Steel design and fabrication involves a signifi- cant amount of engineering that can benefit

from knowledge-based design automation. In- dustry experts suggest that steel fabrication,

which is dependent on engineering design, in- creases the value of raw steel sections by a

factor of 2.5. The sector is supported by more

than 30 commercial computer applications,

providing computational services for design,

analysis, detailing, bills of material and material tracking, scheduling and fabrication management (ERP) programs. A significant number of these applications are based on 3D modeling of the structure and pieces. The sector is also supported by a variety of production

automation equipment ~ for cutting, drilling,

welding and other operations. Steel fabricators

take different roles within the construction

process. While the most common is as a subcontractor, they sometimes serve as general

contractor; in some cases, steel fabricators

have embraced design-build and offer package

services.

In the mid-1990s, the American Institute of

Steel Construction (AISC), the main industry

sector association, adopted the Structural Design Neutral File (SDNF) as a way to exchange

data between the various applications. When

limitations in SDNF were found that restricted

its use, the AISC initiated an Electronic Data

Interface (EDI) initiative to select a more ro- bust and complete data representation for inte- gration and exchange of structural steel data. In late 1999, they adopted CIMsteel Integration Standard, Version Two (CIS/2), developed

at Leeds University, as part of a European

Union automation effort. Major efforts have

been directed toward its deployment, and at this time, ten applications have developed

working CIS/2 interfaces. Several building

projects have now been built using CIS/2 and

it is coming into wide use within this industry

sector (CIS/2 2001).

Precast Concrete

The precast concrete sector — prefabricating concrete products off-site, often prestressed,

then shipping and erecting them - is a fairly

young sector of the construction industry.

Compared to structural steel, the precast concrete sector in the US is smaller, with 2.6 bil- lion dollars of annual work (Economic Census,

2001- non-building products omitted), about

200,000 employees. Industry experts suggest

that the fabricated value of precast products is on the order of 6.0 times the raw material

costs, again, with a large engineering component. In Europe, this industry sector is much

larger; its share is above 15% while in the US,

it deals with 1.2% of construction (Sacks et al. 2002). Like structural steel, careful design and

coordination with the rest of the building design is required for the prefabricated pieces to

fit correctly when erected. While the level of

automation in the US is generally low, it is more advanced in Europe, providing both mature technology to draw upon and examples of

its use. Precast concrete fabricators assume

varying roles within the construction process:

while the most common is as a sub-contractor, a significant number of precast fabricators

provide design-build package services for specific structures, such as parking garages.

In contrast to steel, the precast concrete industry sector has been supported by only a small

number of commercial software applications,

with small sales volumes. Many of these have

been custom-programmed and paid for by in- dividual precast producers. Some software has

been funded by industry associations, primarily the Precast Concrete Institute. A significant

percentage of precast fabricators have implemented Enterprise Resource Planning (ERP)

systems.

In 2000, the North American precast industry

initiated an information technology initiative (see http:// usa.arch.gatech.edu/pci/), using a limited liability corporation called the Precast Concrete Software Consortium (PCSC). The

first step of the PCSC was to undertake careful

process modeling by the member companies,

to gain understanding of their current workflow and identify opportunities for IT

(Eastman et al. 2002). They then developed a plan that included specification for design and

engineering software of precast concrete

building assemblies and also individual pieces

(Eastman et al. 2001) and for the development

of a precast concrete building model. The

software specification defines a knowledgebased CAD application for the precast concrete

industry. The specification was completed in

11
December 2001 and distributed to twenty-six

software organizations; twelve proposals were

submitted. Today, they are negotiating with

two candidate companies to develop and implement software. Definition of the precast concrete building model was begun in the

Spring of 2002.

It is clear that the internal conditions within

these two sectors of the building industry were

appropriate to make significant investments to develop and implement knowledge-based

building models, as we have defined that term. The benefits were not industry-based, but

rather for their own sector and companies. The

authors propose that given these initiatives in IT and their different situations, it may be possible to generalize and posit a framework for IT development that lays out the necessary

conditions for IT innovation. If such a framework was developed, it would allow us to identify necessary conditions for particular

types of IT innovation to be made, and to rec- ognize whether an industry sector was "ready"

(or not) for various innovations leading to knowledge-rich building models.

Below, we propose such a framework of technology innovation within a complexly struc- tured industry, focused on IT innovation in construction.

4. A FRAMEWORK FOR IT

INNOVATION IN THE

CONSTRUCTION INDUSTRY

The adoption of knowledge-based building

models by companies in the construction in- dustry is obviously dependent on many factors. We have identified seven conditions, organized hierarchically:

Pre-conditions: only if these conditions exist, or are perceived to exist by industry leaders,

will there be motivation to take risks and ex- pend intellectual development effort to undertake industry sector change:

(1) an economic situation with a significant

value-added component to the sector's activities, allowing capital and knowledgebased investments;

(2) perceived benefits from technology innovation, in possible gains in market share, in capturing profits of an outside but closely

related sector, or other business incentives;

Leveraging conditions; these conditions pro- vide the use benefits of knowledge-based

building model technology:

(3) the availability of automation technologies that require rich digital project data; the

automation may be at the production level,

supporting computer controlled machining,

welding, concrete mixing, conveyors, fin- ishing, etc.; it may be at the erection planning

or erection level; it may be at the analysis

and simulation level; (4) computer integration in the internal busi- ness environment, which would benefit from

integrating project level automation with enterprise level data management, for scheduling, procurement, manpower planning, etc. Many of the capabilities are provided by ERP

systems;

(5) computer integration of aspects of the

external business environment; this includes

building code checking, web-based bidding

for services, web-based procurement, webbased project management or other business

activities with outside organizations;

Information generation conditions ; knowledgebased data throughout the industry sector must

be generated by specific applications:

(6) the availability of knowledge-based 3D

modeling CAD software, capable of providing the rich digital data needed to support design or production automation within that in- dustry sector; development of such software

requires embedding much of the codified en- gineering knowledge in that sector into the

CAD software, automating conventional design practices; data-rich CAD also provides

the detailed engineering data used for production, purchasing, scheduling and other

activities;

Information integration and exchange; the final

step, in this view, allows the knowledge-based

data to be fully utilized throughout the industry

sector, for automation, enterprise integration

and web-based e-commerce:

(7) development of a product data model for

the industry sector, that supports the integration of the above aspects of the business with

enterprise and web-based applications.

We consider these conditions to define a cas- cade or waterfall set of conditions, where pre- vious conditions must be met before others
below can be successfully implemented. These

conditions are being met in the structural steel industry, and are rapidly developing in the precast concrete industry.

5. CURRENT EFFORTS TOWARD IT

INNOVATION THE AEC

INDUSTRY

Most of the conditions outlined above have not been met in the architectural or general contracting sectors. Yet, the majority of research

in the building construction product-modeling

arena has focused on integration at the front- end architectural design part of the process, because these activities are the primary information generators. The current major effort in developing a knowledge-based building model

is centered around the International Alliance

for Interoperability (lAI) and its Industry

Foundation Class (IPC) building model (IFC

2001). In the lAI, a wide range of construction

industry organizations have come together to fund the development of the IPCs.

However, architects and engineers have been

expected to make equally significant investments in adapting their business practices to new software tools required of the IFC inte- gration technology. Effective implementation

of large IT systems requires not only vision

and investment, but also significant process

changes, which imply organizational restruc- turing (Egan 1998). While design activities have a large value-added component, architects and engineers receive a small and rela- tively fixed percentage of the construction

dollar. No effective business plan has been

implemented to pay for the additional work

that populating a building model would re- quire. Also, personnel issues and training often

stand at the forefront of such restructuring.

Currently, only a few architectural or building

design software applications exist that claim to be able to fully populate a building model. No

set of applications, as of 2001, was able to support all the design detailing typically in- volved in architectural practice. Thus the soft- ware needed to take advantage of a building

model has been lacking.

On the software side, the large software companies whose products are widely used in the

AEC industry stand to reap relatively small

and uncertain benefits from developing new

generations of software technology. Such

changes may even result in their losing market

share when new selection criteria and lack of

track records in the new functionality open the

market to new competitors. On the other side,

small software companies that are naturally

interested in displacing the established ones, do not have the financial backing needed to educate designers to new technologies and new

ways of doing design.

Because there have been few serious efforts at deployment, many technical problems have not been resolved (Amor and Faraj 2001, Eastman

and Augenbroe 1998). Among the issues

needing further work are: integrating applications and data exchange with productive

workflows, system architectures to support

integrated data models, and data management

and integrity issues where many organizations

and individuals contribute to a building project, with various levels of involvement and

over differing segments of a project life-span.

Hurdles also exist in software able to deal with

the datasets associated with large, complex

production-oriented 3D models. Even medium

sized projects are likely to require models with on the order of a half a million objects. These

issues are among those that have stifled taking

advantage of recent developments regarding

web-based project coordination.

While there are significant analysis and simulation applications that could be integrated,

their benefits have not been viewed as signifi- cant by architectural practitioners (as evidenced by current investment). Benefits from

integration with enterprise-level computer

systems in architectural firms appears not to be

significant. One under-developed potential

benefit of knowledge-based building modeling

for architects is for design automation support

of design development and contract drawing

preparation.

Similarly, contractor services have not been

computerized beyond project estimating and

billing, often because of the claim that none of

their subcontractors are ready. Again, strong

knowledge-based CAD systems have not been

available for either industry sector.

However, the framework above suggests that different sectors of the downstream building

13
production process, certainly including precast

concrete, structural steel, but also possibly

curtainwall and window wall fabricators, ele- vator and vertical circulation systems, HVAC

systems, and others, may have better business reasons to implement advanced IT. If this happens, then the context for general contractors

will change, leading to opportunities for them

also to adopt advanced IT.

6. SUMMARY

We have developed a simple framework based on the above seven issues. The framework

suggests a sequence of undertakings within

each AEC business sector, based on the current

situation of that sector. It can be used to identify, for any AEC industry segment, the eco- nomically beneficial IT development steps and

the potential benefits of those changes. It avoids predicating computer integration on any

single design, construction or IT technology, in favor of a systems approach, using contextually based implementation criteria. We are using this model to evaluate AEC in- dustry business sectors, with two goals: measuring their potential to derive benefit from

knowledge-based building modeling; and pro- posing incremental strategies for achieving the

benefits of advanced IT, with each step pro- viding distinct payoffs. Assuming that additional industry sectors will follow the lead of

the steel and precast concrete sectors in incorporating 3D modeling in their business practice, multiple critical masses may be reached,

leading larger segments of the construction

industry to move to integrated IT. These may

percolate through the whole AEC industry,

which will eventually make the transition to integrated 3D modeling.

7. REFERENCES

Amor, R.. and Faraj, I., (2001). Misconceptions

about Integrated Project Databases, Information

Technology in Construction Journal (ITCON),

http://www.itcon.Org/2001/5/, ISSN 1400-6529,

Vol. 6, pp.57-68.

CIS/2 (2001), CIMsteel2 http://dcom.arch.aatech . edu/aisc.

Eastman, CM., Lee, G., and Sacks, R., (2002). "A

New Formal and Analytical Approach to Modeling

Engineering Project Information Processes", CIB

W78 Conference, Aarhus, Denmark, June 2002.

Eastman, CM., Sacks, R., and Lee G. (2001).

"Software Specification for a Precast Concrete Design and Engineering Software Platform", PCSC

Research Report, Georgia Institute of Technology,

Atlanta GA USA.

Eastman, CM., (1999). Building Product Models,

CRC Press. Boca Raton, FL, USA.

Economic Census (2001). Manufacturing Subject

Series for 1997, Doc. # EC97M31S-PS, U.S. Dept.

of Commerce, Economics and Statistics Division,

October, 2001.

Egan J. (1998). 'Rethinking Construction', UK

Govt. Department of Trade and Industry,

http://www.dti.qov.uk/construction/rethink

Economic Census, (2000) Industry Summary, 1997

Economic Census, Document EC97C23-IS, U.S.

Dept. of Commerce, Economics and Stadstics Division. January, 2000

FIATECH (2001). "Economic Impact of Imperfect

Interoperability" FIATECH Projects

http://www.fiatech.org/projects/eiii.htm

Griffis, F.H., Hogan, D. and Li, W. (1995). "An

Analysis of the Impacts of Using ThreeDimensional Computer Models in the Management

of Construction" Construction Industry Institute Report RR106-11

Griffis, F.H. and Sturts. C. (2000). "ThreeDimensional Computer Models and the Fully Inte- grated and Automated Project Process for the Management of Construction" Construction Industry

Institute Report RRl52-11

ICAF, Industrial College of the Armed Forces,

(20(X)). Construction, available at: http://www.ndu.edu/ndu/icaf/industrv/construction/co

nstruction.htm IFC (2001) "Intemafional Alliance for

Interoperability", http://www.iai.org Industry

Foundation Classes IFC Release 2.X.

Moreau, K.A. and Back, W.E. (2000),"Improving

the design process with information management"

Automation in Construction, 10, pp. 127-140

Sacks, R., Eastman, CM., and Lee, G., (2002). "Process Model Perspectives On Management and

Engineering Procedures in the Precast/Prestressed Concrete Industry", submitted to the ASCE Journal

of Construction Engineering and Management,

May.

US Dept. of Labor (1999). National IndustrySpecific Occupational Employment and Wage Estimates (1999). SIC 327 - Concrete, Gypsum, and

Plaster Products, 1999, Bureau of Labor Statistics, US Dept. of Labor.

14
THE ROLE OF THE CIMSTEEL INTEGRATION STANDARDS IN

AUTOMATING THE ERECTION AND SURVEYING OF STRUCTURAL

STEELWORK

Kent A. Reed

Leader, Computer Integrated Construction Group

Building Environment Division

Building and Fire Research Laboratory

National Institute of Standards and Technology

Gaithersburg, MD 20899-8630

http://cic.nist.Rov

kent. reed@nist.gov

ABSTRACT: The second release of the CIMsteel Integration Standards (CIS/2) has been endorsed by the American Institute of Steel Construction as the standard for the electronic exchange of structural steel project information for the North American steel design and construction industry. Derived from the deliverables and experiences of the Pan-European Eureka CIMsteel Project and pubhshed by the Steel Construction Institute in the UK, the CIS/2 was developed with a life-cycle view of structural steelwork

information in mind. However, the primary focus of both developers and implementers of

CIS/2 has been on the pre-construction processes of design, analysis, detaiUng, and shop

fabrication. This paper examines the appUcabiUty of CIS/2 to on-site construction

processes, focusing on automating the erection and surveying of structural steelwork and

integrating these two processes into the overall project dehvery system.

KEYWORDS: automated construction, integration, product data model, project

delivery, structural steelwork

Introduction

Successful integration of an automated process

into a project delivery system depends on the

ability to describe the desired result of the

process in a manner understandable to its automation technology. Similarly, it depends on

the ability of the automation technology to describe the actual result of the process in a manner understandable to subsequent processes.

In this paper, the second release of the CIMsteel

Integration Standards (CIS/2) [1] is examined

for its ability to specify these descriptions in the

specific cases of automating the erection of new

structures and the surveying of existing

structural steelwork.

The CIS/2 has been endorsed by the American

Institute of Steel Construction (AISC) as the

standard for the electronic exchange of structural

steel project information for the North American

structural steel design and construction industry

[2]. The CIS/2 is derived from the deliverables

and experiences of the Pan-European Eureka

CIMsteel project and is intended to specify the

exchange of data and the integration of

engineering applications across steelwork

design, analysis, and manufacturing.

A number of software vendors with structural steelwork applications are developing and

demonstrating CIS/2-compliant translators for

their products as part of the AISC Electronic

Data Interchange initiative [3]. Initial case

studies have shown significant benefits resulting

from the use of these translators to exchange

data between software applications in real projects. These benefits include knowing earlier in the project timeline approximately how much

and what types of steel need to be reserved,

reducing the time needed to estimate the

material cost as part of the bidding process, and

15
saving weeks of detailing time in a typical

project [4].

The CIS/2 characterization of steelwork is intended to cover the needs of on-site

construction as an aspect of manufacturing.

However, the emphasis in the CIS/2

documentation is clearly on the pre-construction

processes of design, analysis, detailing, and shop

fabrication. None of the existing implementation

efforts specifically addresses the information

needs of field erection, although some do

involve applications that can assist construction

planning (for example, through the breakdown

of the structure into erection zones and the

identification by zone of the members to be

shipped).

In order to automate the field erection of a

structure as an integrated process in the overall

project delivery system, one needs to access computer-sensible descriptions (1) of the parts

and prefabricated assemblies that are to be

delivered to the construction site, (2) of the

sequence in which these parts and assemblies are

to be assembled during erection to create the

final structure, (3) of the joint systems

connecting these pieces together, and (4) of the

positions and orientations of all the pieces in their final locations. Automated construction

equipment can then proceed to erect the

structure without human direction.

Likewise, to automate the surveying of an

existing structure as an integrated process, one

needs a computer-sensible description of a model of the steel pieces composing the

structure that can be populated with piece

identification and position data acquired in the

survey using various metrology systems.

In the following sections, the ability of the CIS/2

to provide these descriptions and thus to support

the automation and integration of the erection

and surveying of structural steelwork is explored.

Overview of CIS/2

The following is an extremely brief overview.

The specification [1] should be consulted for

details about what is said here, and for all the

topics that aren't discussed here, such as the

definitions of features and fastener mechanisms.

The CIS/2 was developed using some of the

methodologies and technologies of the

international product data standard ISO 10303

[5], known familiarly as STEP. The information

requirements for relevant concepts in the domain

of structural engineering were captured in structured English. After these information

requirements were agreed, they were interpreted

in a formal, computer-sensible model known as the Logical Product Model (which is LPM/5 in the second release of CIS). The information

constructs in LPM/5 are defined as a schema

using the ISO/STEP information modeling

language known as EXPRESS [6]. This schema

represents the constructs in terms of their underlying data entity types, attributes,

relationships among entity types, and

constraints.

An implementation of CIS/2 in a software

application proceeds first by developing

mappings between the concepts represented in the application and like concepts defined in the

LPM/5. Depending on the particular concept(s)

involved, a mapping may be as simple as one-to- one or as complicated as many-to-many with

associated constraints. Translators for importing

and exporting information to and from the

application in the form of CIS/2 exchange files are developed based on these mappings and the

ISO/STEP clear text encoding method [7]. This

method establishes the syntax of the exchange

file and the rules for composing exchange

structures in that syntax. It should be noted that the exchange structures can not be interpreted

without recourse to the LPM/5 which establishes

their meanings.

The LPM/5 supports three principal views of

structural steelwork information, represented as analysis models, design models, and

manufacturing models. Data representing one, two, or all three views may be present in an exchange file.

Analysis models of the structure are built up

from nodes and elements and support a number

16
of different static and dynamic analysis methods.

Further, analysis results may be given at nodes,

element ends, or at a point within an element,

and the results can be described in a variety of

ways.

Design models represent the structure as a design assembly for the purpose of member and

connection design. Design assemblies can be

decomposed into other design assemblies and

ultimately into design parts and design joint

systems, which are the conceptual

representations of a basic piece of steel and a basic joint system, respectively. Design results for members and connections can be described

in terms of elastic or plastic resistance.

Manufacturing models represent the structure as manufacturing assemblies for the purpose of

detailing, production planning, and

manufacturing. Located assemblies are built up

from located parts and located joint systems,

which are the representations of a basic physical

piece of steel and of a basic physical joint

system (e.g., a fastener group or a weld),

respectively. In turn, all these located items can

be built up into larger located assemblies,

culminating in the complete structure. Features

also are located with respect to the item they

modify.

The located parts and located joint systems and

their higher order located assemblies represent

the items that actually occur in the completed

structure. The material and geometrical

definitions of these items are separated into part,

joint system, and manufacturing assembly

definitions that are referenced by their respective

located items. This separation of data facilitates the economical reuse of generally verbose

definition data across many occurrences of what

are often identical items.

Although the LPM/5 supports the explicit

description of geometry using the ISO/STEP

geometric resources [8], most CIS/2 parts are expressed using implicit descriptions of

geometry based on the specification of a

transverse section profile (or a sheet width) and

a longitudinal length through which the section

profile is swept.

The LPM/5 defines a hierarchical system of

locations (e.g., positions and orientations) such

that an item is located with respect to the higher

order item to which it belongs. For example, a

feature may be located with respect to a part,

which in turn may be located with respect to an

assembly, and so on up to the location of a

structure with respect to a site and the location

of the site with respect to the earth. Each

location is defined using a specialization of the coord_system entity. For most CIS/2

manufacturing model instantiations, this specialization turns out to be the

coord_system cartesian_3d entity, which

encapsulates the ISO/STEP geometrical entity

axis2_placement_3d [8]. This entity has among

its attributes a 3D point defining the origin of the coordinate system and a set of vectors defining

the 3D orientation of the coordinate system.

The preceding information constructs allow the

expression of information about structural steelwork in the form of data instances. They

don't allow the expression of information about

that data, e.g., of metadata related to its management over the life of a project. The Data

Management Control (DMC) schema in the

LPM/5 provides that capability. The DMC

concepts are important to this study because they

allow one to exchange and manage multiple

versions of data instances. For example, they

could be used to maintain simultaneously an "as designed" model of a structure, an '"as built" model, and a current "as is" model, with the data

instances interrelated in a manner similar to the content of a software change control and

configuration management system. The details of the DMC are given in the CIS/2 [1]. For the

purpose of this study, it is sufficient to know that the DMC schema allows the representation of

such information as the unique identifier for a data item, the person who created the data item,

whether the data item is new or has been

modified, why it was modified, and the date of

modification.

CIS/2 Applicability to Automated Erection

It should already be apparent from the preceding

overview that the CIS/2 is applicable to the

17
automated erection of new structures. Through

the composition hierarchy of the manufacturing

model, all the parts and prefabricated assemblies

that are to be delivered to the construction site can be described, along with the joint systems

connecting these pieces together. Through the

nested coordinate systems that locate parts in assemblies and locate parts and assemblies into

bigger assemblies, and so on up to locating a

structure on a site, the positions and orientations

of the pieces and all their features can be defined

with respect to a geo-referenced global

coordinate system. Of course, the global

coordinate system used in the manufacturing

model and the global coordinate system used in the automated erection process must be

reconciled before proceeding with erection.

One complication that arises in using the LPM/5

manufacturing model is its extensive use of

implicit geometry. A member may be

represented by a manufacturing assembly

composed of several plates welded to a wideflange section with a number of clip angles on

the section and on the plates. As stated in the

overview, each of these parts—plate, section,

and clip angle—is normally represented

implicitly through the specification of a transverse section profile and a longitudinal

length. Any datum of interest, sometimes called

a principal point or a fiducial point, on the

member must be calculated from these

specifications and the (possibly) nested

coordinate systems. However, this is really just a

detail to be taken care of in software.

Another complication that arises is the need to be able to map betv.'een a piece physically

present on the site and the representation of the same piece in the manufacturing model. A

unique piece mark can serve to identify the two

items but this is insufficient to ensure the items

are oriented the same way in both worlds. An

obvious way to ensure this orientation is to create a rule-based convention for placing the

piece mark in a specific location on the physical

item. This is similar to the rule-based

conventions found in software that lays out members in a common way in 2D fabrication

drawings, such that the left end and the front

face of the member as shown in the drawing

always bear the same relationship to the

member.

Finally, the LPM/5 location mechanism is based on the STEP axis2_placement_3d entity, which

encapsulates the 3D point of origin and the 3D

orientation of a Cartesian coordinate system.

With some automated placement techniques, this

is just the right information. With others, the

information needed may be, e.g., the set of 3D

points defining all the comers of the member.

Again, this is a detail to be taken care of in software.

CIS/2 Applicability to Automated Surveying

Two different situations arise in the surveying of

existing structural steelwork. In the first, a CIS/2

representation of the structure in the form of a manufacturing model already exists. It might be

the "as required" model provided by the project

design team, for example. The member

identification and location data measured in the

survey can be used in this situation to update the

existing CIS/2 representation to document the "as is" condition of the structure. Automation of

this process would be relatively straightforward.

If the surveying application supports the DMC

schema, then this "as is" representation could be

achieved economically using DMC constructs to record the survey measurements with respect to their equivalent measures in the existing model.

This process can be thought of as the electronic

version of "red lining" a drawing. With DMC

implemented, even fragmentary survey

measurements can be associated properly with

the model.

If the DMC schema is not supported in the

survey application, then the existing CIS/2

representation would have to be duplicated and

the copy updated to account for the survey

measurements. Because it results in an entirely new model, this is a less desirable approach. It is a particularly undesirable approach if less than

100 percent of the structure is surveyed. In this case it becomes difficult to build a consistent

model because the CIS/2 manufacturing model

does not provide any versioning capability and

18
hence can not make a distinction between

original and updated location values.

Of course, the global (presumably georeferenced) coordinate systems used in the

existing manufacturing model and in the survey

process must be reconciled before any model

updating can occur. As well, the nested

coordinate systems present in the manufacturing

model must be taken into account properly. This

nesting is dependent on the composition

hierarchy used in creating the manufacturing

model and that hierarchy may not be apparent to the survey process. Hence, the most transparent

approach would appear to be to make the survey

measurements in the global coordinate system

and transform the location data for each survey

datum in the manufacturing model to the same

global coordinate system for comparison. As

described in the previous section, the datum may

have to be computed from an implicit

geometrical description of the item in question.

For each datum, the inverse of the transform

then can be used to transform the relevant

survey measurement back into the nested

coordinate systems as required for updating the

model. Finally, all survey data of parts and

assemblies must be reduced to the LPM/5

location mechanism, based on the

axis2_placement_3d entity, which encapsulates

a 3D position and a 3D orientation as opposed to a collection of 3D positions of the end points of

a member.

In the second situation arising in surveying, a CIS/2 representation of the structure does not already exist but must be created from the

survey measurements. This task could be

accomplished directly in the CIS/2

representation with a suitable new software

application. Equally, the application could be an

existing structural steelwork detailing package

with a CIS/2 translator. Either way, the

surveying application must build up a model of

the parts and assemblies in the structure from

detailed measurements of the members without

a priori knowledge of the nature of the

members, making automation of the surveying

process difficult. In this situation, however, the

composition hierarchy is known explicitly and

the location data can be transformed

appropriately.

General Issues

Establishing that the information structures needed to support construction site processes are present in the LPM/5 is a necessary but not

sufficient condition for success. These

information structures must be implemented in the CIS/2 translators for the attendant software

applications. The CIS/2 use conformance classes

to document implementation requirements. The

conformance classes already developed in the CIS/2 need to be reviewed for adequate

coverage of construction-related information

requirements and then used to specify the required translator capabilities.

In common with most significant product data

standards, the LPM/5 sometimes provides more

than one way to specify the same information.

Where found to be present, these redundancies

must be circumscribed through implementers'

agreements so that misinterpretation of

exchanged information is minimized.

Also in common with most significant product

data standards, the LPM/5 contains many

weakly specified uses of character strings as

identifiers, labels, and descriptions. Again,

where these are found to be present in the

information structures needed to support

construction site processes, they should be

strongly specified in implementers' agreements

so that misinterpretation of exchanged

information is minimized. As an example of

such an agreement, albeit at the national level rather than the level of individual implementers,

the AISC has updated its naming convention for

structural steel products for use in electronic

data interchange so that software implementers no longer have to decide for themselves how to construct character strings to designate standard

sections.

Finally, the use of CIS/2 to integrate automated

processes in the construction of structural steelwork will still fail despite attention to all of

the above general issues if the users of the

CIS/2-enabled software applications don't

19
provide the necessary information. As an example, the CIS/2 allow for the use of georeferenced coordinate systems, and the

conformance class approach taken in CIS/2 can

be used to ensure the translators involved

properly map to and from the LPM/5

representation of this information, but none of

this can force the user correctly to geo-reference

the manufacturing model of a structure, and

virtually no one does today using their favorite

structural steelwork detailing system. A series of

recommended practices will need to be

developed to guide the end user to ensure

success.

Summary

The second release of the CIMsteel Integration

Standards has been endorsed by the American

Institute of Steel Construction as the standard for

the electronic exchange of steel project

information for the North American structural

steel design and construction industry. In this paper, the applicability of the CIS/2 to on-site

construction processes has been assessed,

focusing in particular on the erection of new

structures and the surveying of existing

structural steelwork. The manufacturing model

view of CIS/2 has been found to be capable of

supporting these processes. With the ongoing

implementation effort in the AISC Electronic

Data Interchange initiative and with the

development of modest new applications, these

processes can be automated and integrated into

the overall project delivery system using CIS/2

as the baseline specification.

REFERENCES

3. Hamburg, S. E., and Holland, M. V., Leaping

Ahead with EDI, Modern Steel Construction,

Vol. 39, No. 1, pp. 42-48, American Institute of

Steel Construction, Chicago, IL, February 1999.

(see also http://www.aisc.org/edi.html )

4. Electronic Data Interchange Case Studies,

The American Institute of Steel Construction,

Chicago, IL, 2001. (electronic version available

from http://www.aisc.org/edi.html )

5. ISO 10303-1, Industrial automation systems -

Product data representation and exchange - Part

1: Overview and fundamental principles,

ISO/IEC Geneva, Switzerland, 1994.

6. ISO 10303-11, Industrial automation systems - Product data representation and exchange -

Part 11: Description methods: The EXPRESS

language reference manual, ISO/IEC Geneva,

Switzerland, 1994. (with Technical

Corrigendum 1, 1999)

7. ISO 10303-21, Industrial automation systems - Product data representation and exchange -

Part 21: Implementation methods: Clear text encoding of the exchange structure, ISO/IEC

Geneva, Switzerland, 2002.

8. ISO 10303-42, Industrial automation systems - Product data representation and exchange -

Part 21: Integrated generic resource: Geometric

and topological representation, ISO/IEC

Geneva, Switzerland, 2000. (with Technical

Corrigendum 1, 2001).

1. Crowley, A.J., and Watson, A. S., CIMsteel

Integration Standards Release 2, Vol. 1-6, The

Steel Construction Institute, Ascot UK, 2000.

(see also the companion website

http://www.cis2.org)

2. Press release, American Institute of Steel

Construction, Chicago, IL, 2001 (reprinted in Foreword of CIS/2), (see also the website

http://www.aisc.org )

20
BEYOND WEBCAM:

A SITE-WEB-SITE FOR BUILDING CONSTRUCTION

Suchart Nuntasunti

Graduate Research Assistant, snuntas@unit^\ncsu.edu

Leonhard E. Bernold

Associate Professor

Director, Construction Automation and Robotics Laboratory, http://carl.ce.ncsu.edu

North Carolina State Univ., Raleigh, NC, 27606

bernold @eos.nesu. edu

ABSTRACT: The use of project website and web cam technology in the construction

industry' is Umited to providing basic information about the project and 24/7 pictures of

the site. This paper discusses the promises of a site-based website that serves as the

central hub for real-time communication, monitoring, and control in building

construction. Such a website offers opportunities that go further beyond what is in use

today. The paper Usts a series of possible appUcations that have been tested at several construction sites in Raleigh. North Carolina. In addition to helping contractors plan and

control the resource flow in real time the site-web-site is also used as a tool for creating

daily reports, rapid problem solving, remote inspection, productivity measurement, on

site security, communicate with on-site equipment (e.g., in emergencies), and to create

visual as-builts.

KEYWORDS: collaboration; productivity; Internet; logistics; value; website;

equipment; safety

Introduction

According to U.S. Census Bureau, in 1997 the

construction industry performs more than $845

billion of work or almost 1 1 % of GDP and

employs more than 5.6 million employees.

Thus, construction productivity is important for

the growth of entire U.S. economy. However,

statistics show that productivity of the

construction industry has been far below other

industries for the past three decades. In

addition, productivity is not the only problem

facing the industry. Quality of work, waste, and

safety are among the issues that decline the

industry's overall performance. Therefore,

increasing productivity, improving quality,

minimizing waste, and providing a safe

environment for workers are main the goals in managing a construction project. In order to achieve these goals, attention must be paid to the

planning and controlling of the processes rather

than on assessing, measuring, and repairing after

the product is finished. In other words, it is only

before and during the actual operation that management has the chance to intervene and

correct, ensuring optimal performance under the

given circumstance. This, however, requires

real-time and accurate information coming from

different sources.

With today's digital and world-wide-web

technologies, communication has never been

easier and faster. The construction industry has

adopted web technology and some projects

already have their own websites. Nevertheless,

the application has been limited to providing

basic information such as project participants,

construction area, and contact information.

Some projects also have a web cam to provide

real-time pictures of the site. However, by

integrating the web with other technologies such

as wireless, sensor, and tracking devices, the

project web site can be transformed into a powerful tool for every participants to plan and

21
control. Because the potential use of the

technology is limitless, it is imperative to investigate the benefits they could provide to each user. This paper discusses the promises of

a site- web-site (SWS) that serves as the central hub for real-time communication, monitoring,

and control in building construction. Such a website offers opportunities that go far beyond

the conventional project website and web cam.

Coalition Building: A Win-Win Strategy

The SWS is designed for six major users: 1.) Owner, 2.) Designers, 3.) Inspector, 4.) Contractors, 5.) Subcontractors, and 6.) Suppliers. Prerequisite of the successful SWS is open information sharing between participants.

Unfortunately, the sharing of information is very

uncommon in an industry that is constantly

squeezed by the low-bid mentality of the owners. Low-bids foster a zero-sum culture

where everybody fights for a piece of a small pie

without considering how his piece is connected

to the much larger pie. If we can't change the zero-sum strategy of contractors, the main

benefit of web-based communication network

will be lost. Thus, this paper will first develop a concept that could entice contractors, suppliers,

and subcontractor to build coalitions as a framework to share information using a site- web-site (SWS).

Collaboration between contractors and suppliers

of a building project offers to drastically

improve productivity and cut resource waste. The basic premise of a contractor coalition is to cut the cost of operation for the participating

coalition partners by optimizing the use of the

combined resources. Figure 1 presents a simplified comparison between a competitive

and collaborative approach. As indicated, the

overall benefit or the value of collaboration is $20 ($150 - $130). This gain, however, can only

be achieved if the supplier spends $10 more on

his operation when compared to the traditional

method. It is apparent that the only beneficiary

of the coalition is the contractor who shows a net gain of $ 30. In order to make collaboration

attractive to the supplier, the contractor has to be

willing to share the savings, which he really can

only achieve with the added work of the

supplier. If we assume that the two coalition

partners are splitting the gain equally, the

supplier will be reimbursed his $10 extra cost and receive an additional $5 from the "coalition

fund" reducing his actual cost to $45 compared

to the $50 in the competitive mode. The

contractor, on the other hand, will end up with a

cost of $95 vs. $100. Figure 2 highlights a real world application of this concept.

In a comparative field test Salim and Bemold

(1994) showed that through up-stream planning,

rebar could be bundled and shipped according to the way the rebar is placed. If the rebar is staged

properly, as indicated in Figure 2, ineffective

time spent on re-handling and searching can be

eliminated. The result of the study showed that placement-oriented delivery and staging

improved crew level productivity in the

placement of rebar by 30% compared to the

traditional method. Key to the productivity gain

in laying the bars, however, was a supplier who

was willing to collaborate with the subcontractor

in shipping the steel in a way that matched how

the crew was progressing.

Framework of the Site-Web-Site (SWS)

The main objective of the SWS is to providing an electronic hub that allows the real-time

sharing of information between collaborating

entities. The system consists of a notebook

computer with broadband Internet access as a hub and a set of peripherals such as docking

station for PDA, motion detector, and video camera. The camera used can be wire or

wireless. The wireless camera provides more

flexibility but the drawback is poor clarity of the

picture. In addition, the series of digital picture

have also been taken and keep in the website as a project history. The information maintained in the system is visual and media rich. The system

has been tested at the residential building

construction site in Raleigh, North Carolina.

Furthermore, the extension of the system is limitless. As shown in Figure 3, the list of

integrated transmitters, receivers, sensors, data

entry ports, access portals, etc. can be extensive.

It is also indicated that on-site data

22
communication using wireless technology will

make the system extremely flexible.

Applications of the Site- Web-Site (SWS)

The following section describes several possible

applications for SWS.

Synchronizing the Resource Supply

The Council of Logistics Management (CLM),

defines logistics as a part of the supply chain

process that plans, implements, and controls the

efficient, effective flow and storage of goods,

services, and related information from the point

of origin to the point of consumption in order to meet customers' requirements (CLM, 2001).

In addition to the physical material, information

about the material such as: 1) bill of material, 2)

purchasing order, 3) specification, 4) delivery

date, and 5) staging area can also be modeled as a flow. Figure 4 presents a schematic that indicates that besides material, all the resources necessary to complete a process can be

incorporated into a flow model that links the

Point of Origin (POO) of a resource to a point of

consumption (POC). It is apparent that the goal

of a synchronized resource logistics model is to ensure the availability of all resources, at the

right time, at the right quality, at the right

quantity, at the right place, for the right price. As

the example of placing rebar indicated, optimal

resource logistics in construction offers many

opportunities for collaborative cost savings,

since many of the resources are controlled by

independent business entities. Web-based

resource logistics offers a unique technology

that supports such coalition building.

24/7 Visual Site Access

An example website that includes the picture

from a web cam is presented in Fig. 5. The

interval time for refreshing or storing pictures can be set from 1 to 10 min. Some of the most

common benefits of such a technology include:

• Real-time review of project status from

anywhere w/intemet access

• Automatic recording of environmental

conditions, project progress, etc.

• Rapid problem-solving if visual information

is needed

• Automatic surveillance at night if connected

to a motion detector and light source

Visual Inspection

Many inspections required during construction

are visual. Figure 6 features two digital images

during and after the completion of the

foundations for a single family home. In the same vein, SWS would allow company safety

inspectors to do their visual inspection remotely.

Visual As-Builts

One unique opportunity provided by SWS is the

creation of visually or electronically generated

as-builts. Spatial data about the exact location

of a new water pipe can be collected from a laser positioning system. Alternatively, digital

pictures allow the new homeowner to see through the walls. Figure 7 exhibits, two

examples how digital images can be used for

establishing as-builts. If the inspection of the

electrical and pluming system would include

taking a series of digital pictures, an extremely

useful information bank could be established.

Another example of useful visual as-builts is the

pictorial marking of buried utilities such as water, sewer, cables, and gas. Any homeowner

who has changed the landscape around his/her

house could benefit from the availability of such

information.

Automatic Resource Tracking

The RFID (Radio Frequency IDentification) tag

technology has successfully been used in the

retail and service industries. For example, WalMart and FedEx have implemented RFID tags to improve their supply-chain and logistics

management. By using RFID tags, the SWS

will be able to track and identify materials,

equipment, tools, and other resources

automatically.

As was discussed earlier, synchronizing the resource logistics must be one of the main goals

of a concept that wants to create win-win

partnerships. Since equipment, material and

23
labor are key resources on a building site, tracking their whereabouts is essential. Figure 8

displays two situations where tracking is able to provide valuable information for different

project participants. Figure 8 a) is of value to the framing and general contractor, as well as to the lumber supplier. For example, both

contractors can estimate precisely when the

framing crew can start and when the materials

should be delivered. It would allow the framing

contractor to indicate where he would like the

lumber to be staged. He could do this by

marking the digital picture and submitting it to the supplier. The effect would be similar to the

rebar example discussed earlier in that unproductive transportation time could be

eliminated.

Figure 8 b) shows that the trusses have been

delivered but not necessarily in an optimal

position. First, it will be necessary to separate

the stacks of trusses. If no crane is available,

this work has to be done by hand one truss at a

time. Secondly, the staging location is not

efficient because the distance to the footprint of

the house is quite large. Most importantly,

however, the framing contractor can see clearly

the status of the framing work and the exact

location of the delivered roof trusses.

BlackBox Technology

Electronic monitoring of large systems can have

many different goals. One example is to detect an unsafe status of equipment while in operation. Bemold (at el., 1997) developed such

a system for cranes. The intelligent monitoring

system can be used to retrofit existing crane

hardware. The simple architecture and the

transportability of the sensors provide

opportunities for utilizing the concept for other

types of cranes or even for other machinery

where unsafe conditions cannot be detected

easily by an operator. Figure 9 depicts how a BlackBox mounted on a crane can be equipped

with a wire-less communication interface to alert people or establish communication between

equipment that are linked to the SWS system

automatically. In addition, such information can

be maintained in the server computer and be

used as a historical record for the equipment.

Summary

Resource logistics, which was once limited to storing and moving of goods, has become a

critical component of company management.

Storing and transportation are still necessary but

now these processes are seen as source of

"waste" that should be minimized. In addition,

logistics of goods alone is no longer sufficient. Information, considered itself a resource, needs

to be part of logistics management. Because of

the highly fragmented nature of the construction

industry information is being created and needed

by many different companies. The main obstacle

to sharing information freely, however, is the

low-bid orientation of the industry. Using a winwin coalition building strategy will create the

necessary incentive to make a site-web-site an economically successful concept.

This paper presents a prototype website for building construction designed to help owner,

contractors, suppliers, and other participants to plan and control resources in real time using

24/7 visual accesses to the site. Using a set of

examples different uses and benefits of SWS

were explained. The system has been tested at various construction sites in Raleigh, North

Carolina. The results show promise to create an

effective tool to improve communication

between contractors, supplies, and homeowners.

In addition to real time accesses, the system is also used as a tool for rapid problem solving,

and increase security. The digital images taken

at the site provide a historical record and "visual

as-built" for the homeowner to show the location

of utility lines both behind (inside) the wall and

buried under ground.

Acknowledgements

The work presented in this paper has been

funded by grant CMS 0080073 from the

National Science Foundation. Their support is gratefully acknowledged. Any opinions,

finding, conclusions, or recommendations

expressed in this study are those of the writers

and are not necessarily reflect the views of the

National Science Foundation.

24
REFERENCES

Bemold, L.E., Lorenc, S.J., and Luces, E.

(1997). "Intelligent Technology for Truck Crane

Accident Prevention." J. Construction

Engineering and Management., ASCE, Vol. 123,

No. 3, September, pp. 276-284.

Council of Logistics Management (CLM).

(2001). http://www.clml .org

Koskela, L. (2000). "An Exploration Towards a Production Theory and Its Application to Construction." Ph.D. Dissertation, Helsinki

University of Technology, Finland.

Salim Md. and Bemold, L.E. (1994). "Effects of

Design-Integrated Process Planning on

Productivity in Rebar Placement." ASCE, J. Construction Engineering and Management,

Vol. 120, No. 4, December, pp. 720-739.

Schonsleben, P. (2000). "Integral Logistics

Management: Planning & Control of

Comprehensive Business Process" New York:

St. Lucie Press / APICS.

o tn c

Mode

of Relatioivv Cost

to

Suppliei

Cost

to

Contraci

Total

Cc

Cost

Sax

Competitive

Collaborative

$ 50

$ 60

$100

$ 70

$ 150-1

$ 130-1 $20

^ ^ 'ft '^Wl

Fig 2. Rebar delivered according to the sequence

of placement

Fig 1. Cost-benefit analysis of collaboration

Material Supplier

Fig 3. Communication Network of a Site-Based

Website

25
N«d Point o( Origin (FOC)

FoinI <,l Consumption Final Stage (POO

urd&nng Fatification C'eliverv

Materials (_>•.•• J". -f^ i h

Emplovm^-ntl AssiQnmi?nl

Equipment / Tools (^;«»«-«-[««<^>

Meeting Planning Information (~> « « . . ij. .

[ i n I

Fig 4. Integration of Resource Logistics

ffUA. ^tXi Mi

Fig 5. WebCam On a Site-Web-Site

Fig 6. Remote Inspection of Foundation Using SWS

a) Studs, Pluming, Power b) Buried Water Line

Fig 7. Digital Pictures as As-Builts

a) Labor is Establisliing Foundation Walls, Bricl< is Staged at Road, Bobcat is Operating

b) Wall Framing is being Worl<ed on. Roof Trusses Are Delivered

Fig 8. Tracking Status and Location of Resources

Fig 9. BlackBox Linked to SWS

26
DEVELOPING A CONSTRUCTION INTEGRATED MANAGEMENT SYSTEM

Yan-Chyuan Shiau, Ming-Teh Wang, Tsung-Pin Tsai, Wen-Chian Wang

Associate Professor

Department of Construction Engineering

Cfiung Hua University

Email: ycshiau@ms22.hinet.net

Abstract: Building market has been shortened for last few years and tremendously af- fected the construction profit in Taiwan. In order to survive in such abominable envi- ronment, people have put many efforts on construction methodology, materials, budget

planning, and strategy alliance. However, to properly enhance the construction management is the key issue to raise company's competition. Therefore, an effective administrating tool is a must in construction life cycle such as estimating, bidding, procure- ment, scheduling, site managing, and valuation. This research has utilized Object Oriented concept, E/R techniques and Delphi environment to develop the Construction In- tegrated Manage System (CIMS). Through the help of this tool, user can effectively

generate Bidding List, Purchasing Materials, Labor and Material Analyze Items and

Specifications. Basic Database System can help us to modify resource prices to adjust

budget, effectively control project cost and financial planning. Budget Control System

will inform engineers when overspend occurs. Purchasing System can assist us to select the best subcontractors with most reasoning price. Valuation system can extract money

request data from site records; therefore, prevent the over-calculating and short- calculating to achieve a better financial administration. With the help of CIMS, we can

effectively control all details such as bidding, purchasing, contracting and evaluating,

for each construction stage. This integrated system can practically control all information, maximize construction management efforts, raise company's strength, increase

competition, and create profit for construction industry.

Keywords: Construction Management, Cost Control, Delphi, Object Oriented.

I. Introduction

With the rapid development of information

technology, the traditional business behavior is deeply affected by the e-Commerce, and the

management strategies of traditional industries are undergoing a fierce evolutional change.

The features of the e-Commerce include:

A. Fast Speed - Real-time service, quick re- sponse and update. B. Large Quantity - Simultaneity, automation and diversity.

C. Lower Failure Rate - Digital data trans- mission reducing personal input errors. D. Consecutive Service - 24-hour and 7-day

service for the v^hole year.

With the aforementioned advantages, the

services rendered by e-Commerce are better in quality than the services rendered by tradi- tional providers. The traditional service providers are much weaker in competitive

strength in comparison with e-Commerce

companies as they are restricted by manpower.

Thus, it is required to respond to the development of this tendency to enhance the productivity and competitive strength of the tradi- tional building industry

To assist the industry in achieving the aforementioned goal, the "Integrated Information

Management System for the Building Industry" is developed to integrate vertically the es- timate, price assessment, bidding, price comparison, construction management, price cal- culation, payment request, and cash flow management. All the relevant information during

the life cycle of a project I, and the calculation

result of each pre-operation is stored in the

system for future use to avoid any errors caused by repeated calculations and inputs.

n. Structure and Function of the System

The "Construction Integrated Management

System" comprises the following modules:

A. Basic Database

B. Budget Module

t

27
C. Procurement Module

D. Price calculation Module

E. Settlement Management Module

To integrate the sub -modules successfully, the

study uses the object-oriented and network

development tools to develop the modules.

The function of each sub-module is described

as follows:

2.1 Basic Database

Each building project is unique in its nature. Two buildings may have the same appearances, but the underlying bearing capacity and

the conditions of neighboring houses are dif- ferent from buildings to buildings. However,

common characteristics exist among the components (column, wall, beam and formwork),

materials (such as steel bar, concrete, ceramic

tile), laborers (laborers in charge of reinforced

steel, painting, plumbing) and documents

(contract, construction instructions) used for a

building.

Since such information is common for differ- ent projects, it is very useful to arrange it for

future use so as to significantly educe the

workload for data management and apply the

cumulative experience for future projects.

The data contained in the database of the sys- tem include the basic resource data, work data,

material analysis data, project instance data,

subcontractor's data, labor data, project data,

owner's data and database maintenance data

(Fig. 1).

2.1.1 Basic Resource Database

The Basic Resource Database contains the

data of manpower, machinery, materials, and

other data concerning the resources to be used

for the work.

2.1.2 Project Items

The project items are the data contained in bid

documentations. In order to cope with complex information for a project, we need to use Object Oriented concept to mimic real world

data by different objects. Based on the WBS

[1], we make out the construction project

items into three levels (Fig. 2): Large Items

(15 items). Medium Items (341 items) and

Small Items (3583 items). In this structure,

Large Items are used for the high level items

of the project (such as Reinforced Concrete

Structure Engineering); Medium Items are used for the middle level items of the project

(such as Systematic Formwork) and Small

Items are used for the low level tasks of the

project (such as DOKA column formwork).

2.1.3 Material Analysis Data

The cost of a project is acquired by analyzing

the costs of material, labor and machinery. All

the quantities and types of material, labor and

machinery for are created in the system for the use of decision makers.

2.1.4 Project Data

In addition to the numbering, name, location

and type of a project, the project data contains

the data about the client number, contract number, commencement data, finish data,

timeframe, contract price, contractor number,

and designer name.

2.1.5 Subcontractor's Data

The Subcontractor's Data contains the data

about (Fig. 3): A. Basic Data (such as name, address, uniform number, capital and performance)

B. Business Items (Set upon the selection

from the database)

C. Evaluation Data (including construction

capability, reputation and financial

status)

D. Unit price (Quoted by each subcontractor)

2.1.6 Owner's Data

The Owner's Data provides the data about

the unit number, telephone number, responsible person, address, e-mail address, uniform

number of the construction company concerned, project name, contact person, remark

and other data related to the owner.

2.1.7 Database Maintenance Data

The cost structure differs significantly from

projects to projects due to the difference in the

location, timeframe, working environment,

and nature of projects. To reflect the actual

28
status, the user is allowed to set different construction conditions for different projects. The

variables are adjustable according to the

budget of each project and, in doing so, the user may control the progress of the construction. When the unit price of any resource changes, the user may adjust the cost and

budget of the project concerned easily with the

assistance of the internal calculation of the

database.

2.2 Budget Module

The Budget Module is used to calculate the

construction cost based on drawings, rules and

other documentations. The system uses indi- vidual works of the project concerned as a basis to estimate the quantities of labor, machinery and material required for each unit, which

will further be used as a basis for the procurement and price calculation operations.

The Budget Module is designed based on an open structure to allow the user to define the

smallest budget unit in accordance with

awarding and procurement. The awarding can

be conducted by combining the labor and material, depending on the nature and works in- volved. The Budget Module of the system

provides the functions of budget preparation,

budget adjustment and bid document preparation.

2.2.1 Budget Preparation

The system divides the budget of a single

work into several categories to reflect the actual status. The divided budget includes the

construction budget, awarding budget, execution budget and closing budget. The system

creates different project budgets based on se- lected databases, work instances and reversed

designs.

2.2.2 Budget Adjustment

In general, the budget may be affected by some factors appearing during the budget

preparation phase and needs to be adjusted.

The system allows the user to adjust the

budget by one of the following approaches:

A. Adjust the total work price based on a

fixed percentage.

B. Estimate and evaluate the possible

change in price index in accordance with

the time set in the Construction Progress

Sheet for different resources. C. Adjust the unit price of a resource that may be affected by external elements

and cause the price to rise significantly.

The overall change of the work can also

be calculated in this step.

2.2.3 Bid Document Printing

The Bid Document Printing function of the

Budget Module is used to print bid documents.

All documents of a project, or the data of indi- vidual works, units, houses or buildings can be

printed separately or integrally without problems.

2.3 Procurement Module

The procurement is the first step for a company to gain profits. The management may

use the Procurement Module provided by the

system to control dynamic market prices, conduct price negotiation, build advantageous

niches and create the highest profits. The Pro- curement Module provides the functions of:

2.3.1 Price Enquiry

Before the awarding is conducted, it is re- quired to analyze the instructions, quantities

and rules of the project and print relevant data, so as to control the site conditions and other

information before quotation is made and

minimize the possible problems that may be

encountered during the construction. The

system is capable to integrate the resources re- quired for the project and analyze relevant

works and materials before sending the price

enquiry sheet. It will also prepare construction instructions and unit price analysis sheets

for subcontractors to arrange their resources. The system provides the following two price

enquiry approaches:

A. Announcement via Network: The system

will announce the awarding information

via network, including the name, location, works, scale, rules and instructions

of the project. The subcontractors may

register, enquire and print on line. B. Price Enquiry Sheet Printing Operation:

The price enquiry sheet provides the in- formation of awarding, project type,

quantity, and unit price analysis and construction instructions. The printed price

29
enquiry sheets will distributed to subcontractors so that they may arrange their resources accordingly (Fig. 4).

2.3.2 Price Negotiation and Comparison

The quotation of the subcontractors input in the system and the data imported by the subcontractors on line are integrated to make a

price comparison sheet. After the identities of

the subcontractors are confirmed, the price

comparison sheet and the awarding budget

will be considered carefully to form a basis for

price negotiation.

The system will integrate the data provided by

subcontractors and calculate the total score of

each subcontractor objectively based on dif- ferent evaluation criteria and weights (including the construction capability, management

capability, financial status, reputation and

market advantages) [2].

2.3.3 Contracting Documentations

This function is used to investigate what projects and works a subcontractor has ever per- formed and the experience, financial status and management capability of the subcontractor.

2.3.4 Material, Labor and Machinery

Requirement Sheet

This function is used to print the type, specifications and quantity of the material, labor and

machinery required by a subcontractor to per- form the work.

2.4 Price calculation Module

The Price calculation Module is used to transfer the data about the works and quantities

from the site daily report system, and perform

the price calculation for the current works and

quantities of the site. The system will read the

data of the contract quantity, procurement

counts and cumulative payment request counts

for cross comparison and analysis. When

finding that the payment request counts ex- ceed the procurement counts, the system will give an alert. The management may control

the expected and actual construction status from the system and prevent the occurrence of

possible problems as early as possible to minimize the risk of loss.

III. System Development

The system is developed through the following steps:

3.1 Analysis of Existing Systems and Collection of Relevant Information

The existing construction management sys- tems available in the domestic market are in- vestigated in the study to find out their short- comings and the solutions to meet the demands of construction companies. The study

also analyzes the historical records of different

projects to investigate the difference in their nature and create an integrated system that is capable to handle multiple projects.

3.2 Analyses of System Features and User

Demand

The process analysis technique is used to determine the functions and information flow

processes required for the system. All unnecessary functions or processes are removed to simplify the maintenance of the system. The

safety system is analyzed thoroughly by in- vestigating individual potential problems and

risks of safety, their affection and possible solutions.

Surveys are done to users about their demand

for the "Integrated Information Management

System for the Building Industry" to deter- mine the requirements for each module, data

type, printing format and other functions, in the hope to provide the best interface operation features for the industry.

3.3 Creation of the Basic Data Framework

The data processed by the system comes from

the database. Therefore, it is crucial to create an effective integrated data framework. In addition to referring to the database structure of

existing construction management systems,

the study also takes the habits of users into

consideration to create a basic data framework

that are appropriately integrated for each

module.

3.4 Programming of Each Subsystem

The study uses Delphi and BDE Administrator

as the development tools and makes use of the

30
network database writing technique to write

subsystem programs. In addition to the single

PC operation mode and the client/server design concept, the system integrates the Internet and muhi-platform features. The standard

Windows""^"^' interface format is used to minimize the difficuhy in operation.

3.5 Test of System Functions

In addition to confirming that the functions

designed for each module can run as expected,

the functions are tested to make sure that the

system can meet the demand of the industry.

The practical instances of the industry are collected for the test, and the comments of the users are analyzed for the modification of each

subsystem. The integrated test is performed

after all the functions of each subsystem have

been tested and confirmed. The objective of

the integrated test is to make sure that the data

stream runs smoothly between different modules. The users confirm it after trial use that the system is capable to demonstrate the functions set for the industry and meet its demand.

rV. Database Structure

4.1 Classification of Works and Analysis of

Materials

The work data in the database is divided into

three levels: Large Items (15 items). Medium

Items (341 items) and Small Items (3583

items). Users may use the work data to create

their own project data easily. The system also

provides the material analysis sheet for each

work, and all the labor, machinery and material fields in the material analysis sheet have

their own resource numbering and quantity

data. The users may change or update the data

stated in the material analysis sheet from time

to time and aggregate them to acquire the unit

price of the work concerned.

4.2 Engineering Resources

The system contains 1100 resources and is ca- pable to analyze the resources required for

each work. The users may use the system to improve their finance management capability

effectively, control the budget before commencing the procurement procedure, and pre- vent the cost from exceeding its allowed

range. The database structure of the system is

built with ER/Studio (Fig. 5).

V. Conclusion

The system is capable to integrate the tasks of

a project, including planning, design, estimate,

budget, procurement, documentation and price

calculation. It is a very useful tool for the

management of a construction company to control its projects effectively. The system

provides the following functions:

5.1 Basic Database

The system divides the works to 17 large

items, 341 medium items and 3583 small

items, and integrates 1200 types of resources.

5.2 Budget Module

The system creates the project budget, awarding budget, execution budget and settlement

budget based on the data in the database, indi- vidual projects and the latest plans. It also

provides three approaches to adjust budget

plans.

5.3 Procurement Module

The system provides a very useful technique

for the selection of subcontractors and the determination of their weights, and allows users

to announce the project to be awarded via

Internet. The users may also use the system to

print the quotation submitted by subcontractors for price comparison and negotiation, and

select appropriate subcontractors in a fair and

objective manner.

5.4 Price Calculation Module

The Price Calculation Module provides the

works and quantities based on the data in the

daily report system, and performs the price

calculation for the current works and quantities of the site. The system will read the data

of the contract quantity, procurement counts and cumulative payment request counts for cross comparison and analysis.

With the assistance of the system, construction

companies may effectively control the information they need and integrate vertically the

budget development, procurement and price

calculation to carry out the construction man31
agement more efficiently. The system is capable to integrate the information scattered at different sites via Internet in a real-time manner to optimize the construction management

of the construction company concerned, improve its competitive strength, enhance its or- ganization, and bring it more profits.

VI. Acknowledgement

I would like to take this opportunity to show

my appreciation to National Science Council,

Executive Yuan, for its support of the study.

Project No.: NSC 90-221 l-E-2 16- 015D

Database

Specialty Data

Proprietor Data

Comnuan Wxrker Data

Subcontractor Data

Project Data

Laboi^Material Analvae Data

Project Items

Basic Resources

Fig. 1 Data Structure of the Basic Database

SB \'mm »* I*** 1^

Fig. 2 Construction Project Dialog

a

1 fi 10.70 rtO.dU

i2.:-o so.oo

7.00 :30.00 W.nj^mi&t$ 7.90 85.00 ^nnmmit i2.«o: ;38.oo W»f*nt.*» 2.70 87.00: 9»S:'if!l|iS(t 6.50 76.00

i H)iS3p*3lf 620: 76.00 :

3.70 90.00 im 87.00

Fig. 3 Subcontractor Maintain Dialog

sgns

t- # 1"? a e

»:8tJt'2 aa

Fig. 4 Subcontractor's Quotation Dialog

thl !^ H*!':

6 B>

Fig. 5 Database Structure of the System

Vn. REFERENCE

1. Xing-Dao Zhang, "WBS, the First Step to Integrate Cost and Schedule",

Construction Management, pp40~44.

2. Zong-Bin Cai, "Research on Pro- curement for Building Projects", A

Master Dissertation, Department of

Construction Engineering, Chung

Hua University, Xin-Zhu, Taiwan,

32
pp55~56, 2001.

3. Fouad M. Al-Sinan and Donn E. Hancher'Facility Project Delivery

Selection Model,"Journal of Management in Engineering, ASCE,

Vol.4, No.3, pp224-259, 1988.

4. Jian-Yu Chen and Zhong-Cheng Luo,

"Contract Management for Government Project", Universal Law-108,

pp29~30,1999.

5. Xian-Zhang Wu, "A General Discussion for Construction Contract

Problem", Construction World,

pp37~41,1999.

33

USE QUESTIONNAIRE AND AHP TECHNIQUES TO DEVELOP SUBCONTRACTOR SELECTION SYSTEM

Yan-Chyuan Shiau, Tsung-Pin Tsai, Wen-Chian Wang, Miao-Ling Huang

Associate Professor

Department of Construction Engineering

Chung Hua University

Email: ycshiau @ms22.hinet.net

Abstract: The construction scale is growing rapidly; therefore, to subcontract is a common

style in Taiwan's construction industry. Selecting appropriate subcontractors is a key to as- sure the success of a construction project. With different environment, construction project

usually invoke complex attributes. We need a good tool to help engineers to pick the best

selections during various and comphcate market. In this research, we use questionnaire to survey about 400 construction companies, which help us to obtain subcontractor selection

factors and their weights. Subcontractors can fill available price for specific items from

Quotation System, meanwhile. Appraisal System will integrate and calculate related data to determine total grades for all factories. Subcontractor Selection System can be used to compile all information about special area. Through the help of this system, Construction Company can use Internet to announce procurement, collect factory quotation and perform sub- contractor selection. This can make the procurement process be fair, pick better partners, increase competition and create profit for company.

Keywords: AHP, Bid, Procurement, Quotation, Subcontractor Selection System.

I. Introduction

1.1 Motive of the Study

Comparing to other phases, such as planning,

design, construction and so on, procurement consumes shorter time in the life cycle of a

construction work. However, it is the key

phase in which the cost of the project is determined. The selection of subcontractors often

encounters problems, such as the selection of

inappropriate subcontractors, difficulty in the

management of subcontractors and out-ofcontrol of budget and quotation systems. Such

problems might be caused by insufficient time

for execution, complicated procedures or poor

information channels. It is, therefore, important for construction companies to control the

subcontractor selection operation and make

sure to conduct it in a fair and objective manner.

1.2 Objective of the Study

The objective of the study is to analyze the

aforementioned problems so as to:

A. Investigate the status quo of the subcontractor selection system in Taiwan;

weights by doing surveys and via AHP;

and

C. Develop a Subcontractor Selection Management Aid System, including Basic Database, Budget Management Module and

Subcontractor Selection Module.

1.3 Scope of the Study

The study is limited to the procurement and

subcontractor selection operations of a construction company. Construction projects are used as the subjects of the study.

1.4 Methodology and Process of the Study

The method and process used in the study is shown in Fig. 1

.

n. Study of the Subcontractor Selection

There are some problems in traditional subcontractor selection strategies:

A. Engineers always pick familiar subcontractors, therefore, cannot get the best bargain for company.

B. The purchasing message can only reach to limited subcontractors.

B. Acquire the evaluation criteria and their C. People can easily collude with subcon35
tractor and commit cheat in close environment.

The subcontractor selection operation includes

the determination of evaluation criteria and

their weights. This is the most difficult operation to conduct effectively and fairly in the

procurement phase.

The importance of subcontractor examination

is described in [1]. The study finds that it is important to establish methodologies for the

examination system and design a simple and

easy-use examination sheet for the of subcontractor selection.

Huang, Chung-Fa divides the subcontractor

management into six subtopics in [2] and

makes comparison among them. The six subtopics are registration of new subcontractors,

final selection of subcontractors, examination

of subcontractors, payment, handle and re- move of disputes, and scale economy of procurement. The selection of subcontractors is described as follows:

2.1 Subcontractor Evaluation Form

The subcontractor evaluation comprises

"Evaluation Facets" and "Coordination of Facets and Evaluation Principles". In [2], the

evaluation criteria and their weights are di- vided based on Work Quality, Progress Control, Cooperativeness, Safety Management,

and Material Management. Some construction

companies divide the evaluation criteria into

12 facets.

2.2 Evaluation and Scoring

Subjectivity is the factor unlikely to be eliminated in the evaluation of subcontractors. Different evaluators may evaluate one subcontractor differently. To prevent the objectivity

of the evaluation from being affected by subject factors, it is required to establish a reliable

scoring system for the evaluation.

m. Evaluation Criteria and Weighing

3.1 Evaluation Criteria and Their Weights

To acquire an objective analysis result, sur- veying is used to investigate the evaluation

criteria and their weights. The perfect score is 100. A fair, open and appropriate selection

model is established by using the computer

aided automatic calculation function in conjunction with arranged relative weights. It is

used as a tool to select appropriate subcontractors in the awarding phase.

The flowchart of the evaluation criteria and

their weights is shown in Fig. 2:

3.2 Application of AHP

3.2.1 Introduction of AHP

Analytic Hierarchy Process (AHP) is a decision analysis approach developed by Thomas

L. Satty in 1971 [3]. As an easy-use and very

practical tool based on a simple theory, AHP is capable to extract the comments of multiple

experts and decision makers, and is mainly

applicable to handling the problems arising in an uncertain environment in which multiple

evaluation criteria exist. The AHP are used to systemize complicated problems and dissolve

these factors into different levels from various

directions. A comprehensive analysis is con- ducted via the process of quantification to assist decision makers in the selection of appropriate plans.

Many factors must be taken into consideration

when operating the evaluation mechanism.

The study uses AHP to establish a hierarchical

structure for all affecting factors and acquires

the weight of each factor by pair-wise comparison. The acquired weight distribution is more objective than setting the weight for in- dividual factors.

3.2.2 Steps of AHP Analysis

The study uses AHP to conduct the decision

analysis with reference to [4] and [5]. The

steps of the analysis are described as follows:

The study uses AHP to conduct the decision

analysis with reference to [4] and [5]. The

steps of the analysis are described as follows:

1. Establishment of the Hierarchical Structure

After the final goal of establishing the hi- erarchical framework is achieved, a mutually independent hierarchical relationship is built by interviewing experts and

doing surveys (secondary goal), and analyzing the elements that might affect the

secondary goal. The elements of similar

importance are collected on the same

level in this step. (Fig. 3)

2. Weight between the Elements on Differ- ent Levels

36
The calculation of the weight between the

elements on different levels is completed

though the following four steps:

A. Establishment of Pair-wise Comparison Matrix:

The element comparison is conducted

in this step. The parent element of an

element on a lower level is used as an

evaluation criterion for the pair-wise

comparison.

B. Calculation of Priority Vector

Divided each comparison value by the

sum of the values in corresponding

fields for the aggregation of the rows; namely, the sum of the percentage

each comparison value occupies in its corresponding row. ^ cell _valuei

column _sum

Formula ( 1 ) shows the sum of the per- centage each comparison value occupies in its corresponding row. An n x

1 matrix is acquired in this step.

C. Calculation of the Maximum Eigenvalue .max:

Multiply the entire matrix with the ac- quired priority vector to produce an n

X 1 matrix. Then divide this matrix by

the priority vector to acquire unit vectors. Calculate sequentially the aver- age of the unit vectors to acquire the

maximum eigenvalue .max.

D. Examination of Consistency:

During the pair-wise comparison, discrepancies might occur between the re- sults of the comparison and the decision. The consistence ratio of Satty's

AHP is used to examine the consistency of the entire matrix.

3.3 Arrangement of Evaluation criteria and

Their Weights

Surveys are done to 400 contractors and the

consistency of the weight analyses is examined

in the study. When the consistency is confirmed, the arrangement of the "Relative

Weight Analysis of the Secondary Goal" and

the "Relative Weight Analysis of the Evaluation Criteria" is conducted to acquire the overall relative weight. Table 1 shows the relative

weight of the entire evaluation criteria.

IV. Development of the Subcontractors

Selection System

The system mainly comprises the maintenance

of subcontractor's data, quotation module,

subcontractor selection module, budget control

module, report preparation and maintenance of

relevant data.

4.1 Maintenance of Subcontractor's Data

The "Maintenance of subcontractor's data"

provides the basic data of the subcontractor

and the data of guarantors. The user is re- quested to input the data of the subcontractor

(Fig. 4). The basic data includes the name,

address, telephone number, fax number, name

and ED number of the responsible person, and

uniform number of the subcontractor. The

scoring of each evaluation item is conducted

based on the basic data.

4.2 Quotation Module

The .Quotation Module, provides the data of

the subcontractor and the project, the settings

of each quotation item and the quotation data.

(Fig. 5). This system also provides an enquiry

function for the user to enquire relevant data of

the subcontractor.

When selecting the subcontractor and the project, the user may select the work to be quoted

and input the selection in the field of Quotation Data (Fig. 6).

4.3 Subcontractor Selection Module

Price is usually the key criterion for the tradi- tional subcontractors selection. However, this traditional price-oriented selection approach

only emphasizes the price and neglects the

quality, timeframe and other factors supposed

to be considered during the procurement process [6]. In the period of recession, this ap- proach may lead to an awarding price that is much lower than the average bidding price,

bringing a higher risk of failure to the owner

[7]. Since each construction company has dif- ferent consideration for each project. People

may want to adjust the weights for each

evaluation factor to reflect the real need. This

study, therefore, conducts the analyses simultaneously for each evaluation item. Different

37
weights can be set depending on the demand of

each project.

The .Subcontractor Selection Module, provides

the functions of project selection, setting of

evaluation criteria, selection of subcontractors

and awarding operation. The user is requested

to choose a project and select the item to be

evaluated from the options of the project. The

system will arrange the subcontractors that have provided the quotation for the selected

item. The user may then compare the quotation based on the data provided by the system

(Fig. 7). During the awarding operation, the

system will arrange the data to be compared

and provide it to the user for the selection of

subcontractors. When the awarding operation

is completed, the system will calculate the

awarding progress and aggregate the awarding

amount.

4.4 Budget Control Module

The .Budget Control Module, provides the

functions of project data selection and project

quotation enquiry. When the awarding budget

exceeds the planned budget, the system will

give an alert to users (Fig. 8). 4.5 Report Preparation

All reports related to the procurement can be

printed by using the .Report Preparation, function. The Progress Chart of Procurement can

be printed by using the sub-function of the

.Report Preparation. (Fig. 9).

4.6 Maintenance of Relevant Data

This function provides the maintenance of unit

data, owner's data, project data, basic database, resources data and selection data. The

evaluation criteria and their weights are cre- ated by the system based on the calculation of

Section 3.3. To provide scalability to meet the

future demand, the system allows the user to input the data to be changed here.

V. Conclusion

The results of the study are described in the

following two major points:

5.1 Creation of Evaluation criteria and

Their Weights

The study analyzes the subcontractor selection

operation and uses AHP to calculate the weight of each selected evaluation item. The

evaluated items and their weights are then integrated into the aided system to select appropriate subcontractors under the consideration

of the price. The project may be adjusted to meet actual demand. The evaluation criteria and their weights acquired in the study are shown in Table 1.

5.2 Development of the Subcontractor Selection System

The study discovers the shortcomings of the current procurement operations and proposes

feasible management strategies. The developed aided system provides the functions of

the maintenance of subcontractor's data, quotation module, subcontractor selection module,

budget control module, report preparation and

maintenance of relevant data, which are capable to provide the following services:

A. The system sets the tasks for selected project and create unit price analysis and re- sources management data for effective cost

analysis and control.

B. The system can select appropriate subcontractors based on the result of the evaluation. A fair and open process is provided

by the system for construction companies

to select appropriate subcontractors objectively.

C. The system successfully combines the pro- curement operations with the budget control, and is capable to give an alert when

the budget exceeds its range.

D. The system provides the progress control

function for the procurement operations, so that the decision makers may investigate the progress.

E. The objectivity of the evaluation criteria and their weights is confirmed by the in- dustry. Both the evaluation item and the

weights can be adjusted depending on the

demand of each project.

VI. Acknowledgement

I would like to take this opportunity to show

my appreciation to National Science Council,

Executive Yuan, for its support of the study.

Project No.: NSC 90-221 l-E-216- 015.

38
Initial Compile for Appraisal Items t I

Questionnaire Design

Interview Appraisal Items

Questionnaire Design for Weight of Appraisal Items

Interview for Weight of Appraisal Items

Calculation for Weight of Appraisal Items

a R A n

J5»IS¥«S [a;

t — »

5.yO S5.00

4.10 70.00

13.30 90.00

10.70 90.00 123 80.00

7.00 79.00

7.90 70.00

12.80 85.00

2.70 85.00 630 85.00

3.70 85.00

7.00 85.00 520 80.00

1

ITS, K Q m

Fig. 4 .Data Maintenance. Dialog

Fig. l Apply Weight into CMCS bsearch

Determine Research Scope and Objective

Determine Research Methodology and Flow

Review Documents

Analyze construction Project Administration system

Construct Subcontractor Selection system

owchart of Evaluation Criteria

Final

Destimtio

Evaluate

Standards

Subcontr actor

Sekcticari

Ccaiitnictian

Evaluate

Event

Schedule Control

CoardKiaticri

Saf « XtAn-micrratin)-.

Firimciil

CorulitiarL

jC^ial I

RepulAtLari CandiicTL

\ Arbitr^tiori Hl^toiy]

CondilKiri

Matjeml Regixoial

Corujitiooi J SubcoirtrsctOT

Fig. 3 Hierarchical Structure of the Factors for

the Selection of Subcontractors

mm

mm

C002 -mm. Wtm iEeSSirfSiJ«JfS;Eli;'iI)l

Fig. 5 .Quotation Module. Dialog

r«J5M 1*1*1 »Si 1 Iff *)a*t(a(t

ou

A^.li] ) ] 700 0(1 117 Virii nil AAW 700.011 £

.^A^.'! 76 'JL yoo.oij 6

D7 7O0.tiu AACl S«awi«*wit5t* m: :70uc 650.00 17 AAOl 50 Ciu 5,90000 AAOt 1 00 ;> (iOO 00 >T»l rUVTIS-Bu • S-'Et 790 011 J*1.|.-:il nil

t- -

Fig. 6 .Quotation Data. Dialog

l!OiSi.XS

LiJ

430 0 500 090,00 70 OC

78 00

70 58

1

4 10

1

1

1 u /i",i »5I«S(?ff 1

:

7 'Jij 70 r

1 ; eo

: 70 r 650 850

HQS Svi,'/J,:*5

Fig. 7 Subcontractor Selection Screen

39
e!«:--.;'«t)!IEl!'Ei w

:i 1-1 ijii.. .y.iii -./.li.i.' ;

1. M lT.:o:i

»,"«? ndiii; :<driri !!',, ..-Jn jtiin.ii'

>B7/ .^fl77 7:f -^,11 :;;1.;79S

ff*iRii» T

r'tftfe^Fr F l(W)» m ;j7'- ;5n; 47.r7Ji

1 .'.I

fss,«fS!; « t *"

Fig. 8 Budget Control Screen

Fig. 9 Progress Chart of Procurement

Table 1 . Relative Weight of the Evaluation

Criteria

Eva uate Standards Weight

Construction

Capability

Construction Quality 0.107

Schedule Control 0.122

Construction Capability 0.070

Management

Capability

Coordination 0.133

Safe Administration 0.065

Financial

Condition

Capital 0.041

Payment 0.070

Banking History 0.059

Reputation

Condition

Arbitration History 0.027

Business Evaluation 0.037

Trade History 0.062

Regional

Condition

Material Regional Condition

0.128

Subcontractor Regional

Condition

0.079

Vn, REFERENCES

1. Ji-Zhong Zhang, "Research on Construction Subcontract Management", Master

Dissertation, Department of Science and

Construction Engineering, National Taiwan Institute of Technology, Taipei,

ppl41~ 151, 1996.

2. Zhong-Fa Huang, "Research on Construction Subcontract Management of Tactic

and Organization", Doctoral Dissertation,

Department of Civil Engineering, National

Central University, Tao-Yuan Taiwan,

pp 126- 131, 2000.

3. Satty, T.L., "The Analytic Hierarchy Process", McGrawHill, New York, 1980.

4. Zhen-Yuan Deng And Guo-Xiong Zeng,

"Application of Analytic Hierarchy Process (AHP) on Intension Characteristic And

Analytic I", National Statistics Report,

pp5~22, 1989.

5. Zhen-Yuan Deng And Guo-Xiong Zeng,

"Application of Analytic Hierarchy Process (AHP) on Intension Characteristic And

Analytic 11", National Statistics Report,

ppl~15, 1989.

6. Zohar Hersman and Ralph Ellis, Multiparameter Bidding System-Innovation in Contract Administration. Journal of Construction Engineering and Management,

ASCE, Vol.1 18, Nol, ppl42-150, 1992.

7. Gysbert J. R. Van Der Meulen and Arthur

H.Money..The Bidding Game,. Journal of

Construction Engineering and Management, ASCE, Vol.110, No.2, ppl53- 164,

1984.

40
Development of Electronic Acquisition Model for Project Scheduling (eAMPS) Using Java-XML

Will Y. Lin

Ph. D. Candidate, Dept. of Civil Engrg., National Taiwan University,

Taipei 10617, Taiwan, E-mail: will@ce.ntu.edu.tw

Abstract: During the construction phase, participants in a multi-contract project acquire external

real-time scheduling information from other involved parties and use this to make appropriate

decisions in regard to project control. There are two major obstacles to project participants gaining

efficient access to external information in a distributed data environment: (1) the variety of data

structures that project members may use, and (2) lack of an automatic mechanism for data

acquisition. Based on the ontology defined by extensible markup language Schema (XML

Schema) and an automatic mechanism called Message Transfer Chain (MTC), an Electronic

Acquisition Model for Project Scheduling (e-AMPS) centraUzed in an information agent. Message

Agent (MA), was developed. Each participant equips a Message Agent as his unique information

window to automatically acquire external information and provide other participants with

scheduling information as well. The ultimate goal of this study is to build an automatic

communication environment for multi -contract projects to solve the abovementioned difficulties, and thus achieve effective communication among project participants.

Keywords: Internet; WWW; Project Management; Intelligent Agent; Information Integration

Introduction

Most scheduling theories take into account a

variety of situations, such as weather, site layouts and so on, according to available

information while scheduling to produce a "perfect" schedule, which seems to forecast the

future very well. However, due to a large

number of construction uncertainties before the

project starts, such as material shortages and

interference between two tasks of different

subcontractors, it is coinmon that the initial schedule has such a variance with the real condition of construction that some planned

tasks cannot be carried out accordingly. Recent

planning-related research, such as Lean

construction suggests that schedules should be

updated adequately and constantly after the

construction starts, according to the real-time

engineering information available to keep

themselves concurrent and useful. In most

multi-contract projects, however, it's common

for 80-90% of the tasks to be performed by

subcontractors such that scheduling for these

projects is a cooperative task which requires

many project members to take part in. In order

to realize the continuous scheduling suggested

by Lean construction under this circumstance.

it's necessary for these subcontractors to "dynamically communicate" together.

Communication in construction industry

during construction phase is extremely

complex. In terms of information technology,

communication can be simplified as the

exchange and reuse of information or messages between two independent parties. In

this sense, to automate the communication

among construction project members implies

to automate the exchange and reuse of

information or messages. The exchange and

reuse of engineering information have been an

issue in the field of automation in construction

since information technologies were first introduced in 70' s. Much research and related

applications have also been developed to achieving all kinds of automation in communication. However, there still are two

major obstacles to automate the continuous

and collaborative scheduling for multi-contract

projects: (1) the variety of data structures for

scheduling that project members may use, and

(2) the lack of an automatic mechanism for

data acquisition in such a multi-user workplace

for most multi-contract projects.

41
Based on the ontology defined by the

extensible markup language Schema for

Scheduling (XSS), the Data Acquisition

Language for Scheduling (DALS), the

Hierarchy Searching Algorithm (HSA), and an

automatic mechanism called Message Transfer

Chain (MTC), an Electronic Acquisition

Model for Project Scheduling (e-AMPS)

centralized in an information agent, Message

Agent (MA), was developed. Each participant

equips a Message Agent as his unique

information window to automatically acquire

external information and provide other

participants with scheduling information as

well. The ultimate goal of this study is to build an agent-based communication environment

for multi-contract projects to solve the abovementioned difficulties in automating

communication in a multi-user workplace, and

thus realize continuous and collaborative

scheduling.

of our model. The complete framework of e- AMPS consists of five major components:

Ontology base. Message Agent (MA), Open

Data Repository, DALS-speaking Decision

Support Systems for Scheduling, and Message

Queues [1].

Decisjon-Making

Level

DaAa-Retrieving

Level

Figure 1 : Main Framework of e-AMPS

Architecture of e-AMPS

To solve the difficulties involved in sharing

scheduling information among project

participants in a data-distributed environment,

an agent-based communication environment

called Electronic Acquisition Model for

Project Scheduling (e-AMPS) has been

developed. The model is centralized in an

information agent called Message Agent.

Basically, Message Agent is a computer

program that deals with all messaging tasks

involved in automatic communication, and will

be introduced in the following sections. Each

participant in the same project, named a Host

or Contact Node in the following paragraphs,

equips a Message Agent as a unique

information window so that Message Agents in the same project can automatically

communicate with each other. In this section,

we introduce the basic framework of e-AMPS

and the functions of Message Agent in order to give an overall picture of the proposed

concepts. Figure 1 illustrates the complete

architecture of e-AMPS. The complete

automatic communication consists of two

different levels of replying to the imported

requests: Data-retrieving level and Decisionmaking level. In this paper, we only focus on

the Data-retrieving level. However, the

components within the Decision-making level are also addressed to some extent in this section to help draw a more complete picture

(1) Ontology base: This stores all ontology on

scheduling in terms of data schema, called

XSS, the syntax of which is adopted from

XML schema in our study. The ontology here

is defined as "a specification of a conceptualization, or a description of the

concepts and relationships that can exist for an

agent or a community of agents."

(2) Open Data Repository: This contains

scheduling information with standard data

structure defined by the ontology (XSS),

whose data structure is shown in Figure 2, and

is in XML syntax [1]. It's basically a file folder that contains all scheduling information

files of standard formats. There are two kinds

of scheduling information files for each e- AMPS: Schedule File (schedule.xml) and

Contract File (contract.xml).

(3) Message Agent: This deals with all manipulation of incoming and outgoing

messages following the communication

mechanism built by e-AMPS concepts. It communicates with other Message Agent

mounted on other contact nodes, and also with

its local decision support systems through the

mapping table.

(4) DALS-speaking Decision Support Systems

for Scheduling: They are built by the host,

independently from the Message Agent. They

have independent decision support models to

42
generate specific decisions toward certain

fields. Most important of all, these decision

support systems all recognize the DALS and

use it to request for information from other

project participants as their input data [1].

(5) Message Queues: Message Queue,

physically an open access file folder, contains

all messages (requests or responses) from other

Message Agents. Each Message Agent will access its Message Queue regularly and

automatically to react according to the

messages [1].

Participant

fj Header |-|[-| Request [-|

4Con1ent| M Ftesponse P

Name/Description

i TimeMlestone

-

| LafaorPlan

] ResourcePlan |-

-

| EquipcnentPlan

-

j MaterialPlan Progress

--*-| Progress! 1 TaskComptetePercwnf

lomlyfteportl Figure 2: Data Structure of XSS

The utilization of e-AMPS can be divided into

three stages:

(1) Installation: Every practitioner in the

construction industr>', i.e. Owner, A/E,

contractor, and supplier, equips a Message

Agent that is implemented by Java, regardless

of platform to be used, and therefore a communication environment is then built where Message Agents in the same project can

automatically communicate with each other. When installing the system, a practitioner is prompted to specify the local file folders for

the Ontology Base that contains the data

schema file, the Open Data Repository that contains the scheduling files, and the Message

Queue that contains the message file. The

folder for Message Queue should also be

associated with a Uniform Resource Indicator

(URI), which can be openly accessed by

Message Agents of other project participants.

(2) Contract signing: Once the practitioner

signs a contract with another party, the

scheduling information is then prepared

according to the data schema, and is deposited

in the Open Data Repository, where the

Message Agent can access and make inquires

about the shared scheduling information.

(3) Contract execution: While the contract is being carried out, the Message Agent checks

the Message Queue regularly and deals with all messaging tasks automatically according to the

message it receives, such as sending the

requests originating from the Host or passing

the responses sent by other Message Agents to another Message Agent.

The detailed design of the Message Agent can

be referred in another paper [1].

Implementation of Message Agent 1.0

Java

TM

language is a rich environment for

XML programming since there have been more XML-specific resources available in Java

than in any other programming language.

There are two major reasons why Java meets

XML programming. The first is their shared

reliance on the Internet. XML was designed to be straightforwardly usable on the Internet,

while Java was designed to be used over the

Internet. Java works well in a distributed

environment, allowing users and programs to share information easily, while XML provides

a tool for distributing and storing that information. The other reason is their shared

use of hierarchical structures. Java's objectorientation and XML's fundamental use of

nested hierarchies is a suitable match of

combination. Programmers can easily develop

tree structures with Java that match the

structures of an XML document, making it easy to convert XML files into instantly usable

data in Java application or applet. Due to the

above reasons, this research uses Java 2 as the

developing language. The Java

TM

API for

XML processing has been added to the Java 2

Platform. It provides basic support for processing XML documents through a standardized set of Java Platform APIs, and

other network-specific programming facilities suitable for the implementation of e-AMPS

and Message Agent. Several programming

features are addressed first, which are multithread processing, parsing with a validating

mode using XML Schema, and the use of

Remote Method Invocation (RMI).

(1) Multi-thread processing: A thread —

something called an execution context or a lightweight process — is a single sequential

43
flow of control within a program. A single

thread process means that a process has a beginning, a sequence, and an end and at any

given time during the runtime of the thread,

there is a single point of execution. On the

other hand, multiple threads mean that there are more than one single thread running at the same time and performing different tasks

within a program. Since carrying out various

manipulations of a message, the Message

Agent is implemented with multiple threads

and thus different manipulations of a message

are able to proceed independently and

smoothly.

(2) Validating documents using XML Schema:

There are two types of XML parsers, divided

by different function levels: validating parser

and non-validating parser. There ai'e also two

methods to validate an XML document: using

Document Type Definition (DTD) or using

Schema. An XML document is valid if it has an associated DTD or Schema, and if the

document compiles with the constraints

expressed in it. A DTD defines the data

structure of an XML document. It specifies the

order in which tags occur, what the tags are, and how many tags are allowed. A DTD

provides a uniform format for defining the

structure and markup of an XML document.

Unlike DTDs, however, XML Schemas adhere

to the XML specification and provide better support for XML namespaces and more data

types. It is also a recommendation of the W3C.

Schemas provide a more flexible means for

defining the structure, content, and semantics

of XML than DTDs. In many areas of

application, DTD is replaced with XML

Schema nowadays although DTDs had been

widely adopted for years. Due to the above-mentioned advantages of

XML Schemas, the Message Agent adopts a

validating parser using XML Schema.

(3) Use of Remote Method Invocation (RMI):

Since several major manipulations of a message are involved in passing an XMLbased message from a local Message Agent to remote Message Agents, an approach of file transferring from one host to another is required by the Message Agent. Although the

protocol File Transfer Protocol (FTP) or other

message transfer methods such as SOAP is a possible way to be applied to this end, the

Message Agent 1.0 adopts a remote access

mechanism provided by Java called Java

Remote Method Invocation (RMI) since RMI

allows an object running in one Java Virtual

Machine (VM) easily to invoke methods on an

object running in another Java VM. RMI

provides for remote communication between

programs written in the Java programming

language.

Figure 3 is the flowchart of starting up and

stopping Message Agent, which is the main

stream of the whole program. Since the

process of dealing with messages undertaken

by the Message Agent is a routine task with a given running period, the main stream starts at arousing a thread called MainLoopQ.

MainLoopO then triggers three child threads:

MessagingTask_AppendingMessage(

)

, MessagingTask_CheckingMessage(), and

MessagingTask_DispatchingOutboxMessage(

).

Figure 3: Flowchart of Running Message

Agent

In three child threads of the thread

MainLoopO, whether the thread lifecycle of

last execution is finished or not would be

examined first. If the thread is still "alive", the

new thread will not be triggered. Thread

priority is set mainly according to the average

running time spent. The thread that spends the

longest time averagely gets highest priority.

Figure 4 illustrates the core objects of Message

Agent version 1.0 and their relationships one

another. The class MainFrame is the visual user interface that initiates the root class MessageAgent of the whole program. Under

44
the root class, there are thread class MainLoop

with three child threads, five major message

processor/manipulation classes, and a RMI

class RemoteReceiver that implements the

interface FileReceiver.

facts and results are extracted to emphasize the

effect of e-AMPS.

FiteftecEivg

Figure 4: The Relationship between Objects

Scenario

A hypothetical design-build project is made up

to illustrate more fully the concept of e-AMPS

and the effect of the Message Agent. The

milestone network and bar chart of the project

are shown in Figure 5.

Finish

0 Time(day) 220

Figure 5:The Project Network of the Example

There are 12 packages enclosed in this project,

undertaken by a general contractor and his 1

sub-participants, from PI to Pll. Figure 6

shows summary bar charts of all subparticipants under the cooperation structure of

the example project. The entire project starts on Jan 1*', 2002 and finishes on Aug 8'*' in the same year using a calendar of 7-workingday a week due to simplify the complexity of the

example.

In following paragraphs, a scenario is made up

respectively associated with a typical

communication behaviors for scheduling:

requesting for progress data. The whole

communication cycle, from the original

request to the terminal responses, is recorded

and represented as well as some important

Legend:

Request passing Ai P*' A: Task ID or Package ID F^SPOnse passinq S: Subcontractor ID

s Package Ai:_£ Task (s)starting Node ^Selected Node

(S) Not-Selected Node

Figure 6: Message Passing Path of the

Scenario

On Mar 10* 2002, the general contractor

originates a request for the progress

information of all tasks whose duration

overlaps a period between Mar 15* and Mar

25*, about two weeks before the Task H&K

of participant PI starts. The original request

without the header created by a pre- programmed process at the general

contractor's site is deposited in the Message

Queue, and waits for his Message Agent to dispatch it. The Message Agent of the general

contractor detects this request and

automatically performs the HSA. Since having no upper messengers. Message Agent of the

general contractor decides to dispatch the

request to two of its lower messengers, S2 and

S3, since the packages undertaken by S2 and

S3 meet time and scope constraints.

The request to S2 is bypassed to S2's lower,

S6, due to Package P-F undertaken by S6

meets the constraints specified by the request.

Upon receiving the bypassed request from S2,

S6's Message Agent perform the query

transformation and generate a response

sending back to S2, flowed by another

bypassing by S2 back to the general contractor.

Figures from Figure 7 to Figure 9 show the

sequences of message manipulations by the

Message Agents of participants involved in

this scenario, G, S2, and S6, respectively. At

the site of G in this scenario, G's Message

Agent passes two requests (requestid: 3945 &

requested: 8379) to two of his lowers, S2

45
(URI: 140.112.10.31) and S3 (URI:

140.112.10.32), respectively. 35 seconds later,

it receives the first one response (responseld:

3884) from S3 in which the original replier is S8, according to the message log at the site of

G. 10 more seconds later, it receives the

second responses (responseld: 3389) from S2,

in which the response is generated by S6. 6 more seconds later, it receives the last response

again from S3, in which the original response

is generated by Sll and is bypassed through

S8 and S3 in turns.

;:Fila Help

; ConFieijration j Message Bosrd Message Receivsf

j TransiKtion Log

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Conclusion

Sharing of project scheduling information

among subcontractors is useful for predicting

potential delays and taking any necessary

precautions. However, there are two major

obstacles to multi-contract project participants

accessing the external information they need

efficiently: (1) the variety of data structures

that project members may use, and (2) lack of an automatic mechanism for automatic data

acquisition. An agent-based communication

environment called Electronic Acquisition

Model for Project Scheduling (e-AMPS) is developed to solve the abovementioned

shortcomings. Message Agent was

implemented using Java 2 and tested in IBM

PC with Windows 2000 OS. The testing and

system performance have been evaluated with

positive results.

Acknowledgement

The authors would like to acknowledge the

National Science Council, Taiwan, for

financially supporting this work under contract No. NSC-90-2211-E-002-074.

Reference

1. W. Y. Lin, "Development of Electronic

Acquisition Model for Project Scheduling

(e-AMPS) Using Java-XML" PHD

Dissertation, Department of Civil

Engineering, National Taiwan University,

2002.

46
An Automated Selecting Subcontractor Model In E-Commerce

by

Pao-Hung Lin

Asst. Prof., Dept. of Civil Engineering, Feng-Chia University, Taichung, Taiwan

E-mail: paolin @fcu. edu. t\\>

Abstract: From the observation of organization changes in digital economy, the

features of organization expansion from its concentrated kernel to the globalized e- commerce scope is identified to rebuild the relationships and connections between

the whole subcontracting supply chain for construction projects. An automated

subcontracting selection model is proposed and the final decision-making for selection will be approached by Multiple Attribute Utility Theory. Following this methodology, it can be expected to bring the excellent decision support into full play

for the selection of subcontractors.

KEYWORDS: utility theory, e-commerce, subcontract, decision-making

1. INTRODUCTION

Knowledge-based and networked characteristics

shape the all new information era in the digital

economy. "Electronic Commerce" (e-commerce)

has been the symbol of enterprise activities in digital time. The force of virtualization and

virtual market constitutes the heart of e- commerce in the digital economy. The nature of e-commerce is to build the innovation of

competitive advantage between enterprises by

way of web connection, to alter the operation

process and to enhance the efficiency of

organization. Digitization not only improves the

information quality and enables interactivity, but

also provides a powerful approach for management in many respects. The new

economy is creating a reformation of conflicting

drivers causing every enterprise in every

industry to rethink its competitive advantage, to rebuild its system of value chain, and to restructure its organization pattern. All the

traditional thinking way to communication or

transaction is facing the unprecedented

challenges to shift.

Tapscott (1996) pointed that the result of this

shift from physical to virtual does not simply

reduce redundancy and speed up

communication. Rather, the substantial changes

in the essence of human and organizational

communication occur. Inter-enterprise

computing is causing new economic dynamics

in the following ways: accessibility of partners,

new interdependence, interorganizational

metabolism, cooperative competitiveness, and

interorganization value creation. Through the

connection of information network, the resources are distributed and values are generated in the boundless virtual marketplace.

Due to the sharp differences between the "virtual

market" transaction atmosphere in the postinformation era and the traditional physically

economic market, major impact are certain to occur within traditional main contractor and

subcontractor relations. The processes of these

change, and whether they will completely alter previous subcontracting relationships and

models is a topic worthy of further research and

consideration. From comparisons of the

construction industry with the manufacturing

industry or other productions that have gone

through relatively little in the way of developing

IT environment, it is quite clear that, based on

the ideas of e-commerce and the importation of

practical methods, in the future it will be

possible to improve on abuses that arise in traditional construction industry business

processes.

Although it's crucial to select appropriate

subcontractors to implement specific

construction project, few research really touched

47
the selection techniques and methodologies and

extended further into the connection of overall

supply chain. Therefore, what the influence to the whole subcontracting supply chain of the

research's concern in this digital economy is analyzed from the new vision of economics of

electronic commerce. The new transaction

mechanism is shaping in digital economy and all the trends and properties existing in the

omnipresent environment have resulted in great

change of organizational structure and the nature of transaction, and even paradigm shift.

2. METHODOLOGY

The methodology of this research is founded on

the observation of e-commerce economics as well as networking mechanism and put the

problem in center of subcontracting supply chain

management or the combination of

subcontractors. The major significance of this methodology is to support the acquisition of

optimal selection set from myriad subcontracting

combinations for specific construction project.

All the bidding information and decision are implemented through omnipresent Internet. Every client user needs only to open their web

browser to use the system's capabilities to retrieve all of the needed information online.

The architecture of data transformation can be

shown as Figure 1. Further, this methodology is proposed by taking advantage of the portfolio

theory of investment choice under conditions of

uncertainty on the mean and the variance of the

distributions of returns to approach the selection

model of subcontractors in construction project.

That is, the risky connection in whole supply

chain will be considered and obviously the profit

will no longer be the only factor to the decisionmaking of bidder selection as the traditional

bidding strategy. And most importantly, the

factor that must be taken into consideration in electronic bidding system is how to provide a compatible environment and services meeting

the needs of all participating enterprises of the

global market in a timely and sharing manner.

This methodology also extends the decision manner of two factors of portfolio theory to multiple attribute decision-making in order to be

endowed with potential for encompassing all the

possible factors of influence to selection. The

final selection will be dependent on the risk

preference of decision-maker by the utility

function. Comprehensively, the methodology is

enclosed by the internet-based information

technology as the demonstration of Figure 2.

3. NETWORKING MECHANISM

In retrospection of the development of

commercial organization, there can be classified as function oriented, department oriented, and

the matrix type in traditional organization

categories (Miles and Snow, 1992).

Nevertheless, "networking" has been the main

research focus in management field and the

trend to the application of reality. There are many different denominations to interpret the

remold organization, such as Peter Drucker's

(1998) "Networked Organization," Peter Senge's

"Learning Organization," Keen's (1991)

"Relational Organization" and Davidow and

Malone's (1992) "Virtual Organization." They

all put emphasis on the "relational" network

between members of organization. No matter what the idea of networking interpreted from the

view point of resource dependence (Joanson and

Mattsson, 1987), transaction cost (Williamson,

1975; Oliver, 1990), or strategic alliance (Porter

and Fuller, 1987), the essence of networking lies on that the specific enterprise can concentrate on

the most valuable activities with competitive

advantages, to reach the economies of scale and

obtain the benefit of work specialization (Porter,

1985). The "networked organization" opens a new style and feature in the area of organization

structure and strategic management, revives the

traditional organization pattern (Miles and Snow,

1992), and provides the alternatives except

vertical integration as well as diversification.

From the investigation and observation of the

evolutionary process in traditional organization

relationship, it can be found that the

"information network" is indeed playing a very

crucial role to push the changes and

virtualization (Tang, 1998). Figure 3 represents

the process of organization development under

both the coordinate axes of relation network and

information network. It demonstrates the

features of organization expansion from its limited kernel, partnership, vertical integration,

outsourcing to the e-commerce global scope

according with the developing information

network, and simultaneously expresses the

virtualized evolution of organization

relationship. Also, the corresponding space-time

situation of this research's concerns are located on the relation plane to show the focus of the

48
present model. Additionally and importantly,

this research is not only focusing on the

exploration of the forming of virtual organization, but on the searching of the profitbase and efficiency to improve the link of

selecting subcontractors by observing the

organization changes in digital economy.

4. THE PRESENT CONCEPTUAL MODEL

The proposed selection model takes three main

attributes into subcontracting consideration,

namely, the expected return (ERN), the planned

performance dispersion (PPD), and the

comprehensive risk index (CRI). The expected

return and the planned performance dispersion

are the leading roles and have been exactly

discussed by Tsemg and Lin. This research, the

comprehensive risk index is to integrate the

bidder's credit degree and quotation deviation

(including tender price and duration) to expansively consider the correlation between

subcontractors in the specific combination of

construction project, hi the concrete, the CRI is a

representative evaluation index composed by

three kinds of uncertaintyOy ,Py , andy, , wherea,y

is the measurement of dispersed degree of

quoted duration for subcontractor / to the market

value in the bidding of specific subproject j ; (3^ is the measurement of dispersed degree of

quoted price for subcontractor / to the market

value in specific subproject j ; andy, is the credit

rating for subcontractor / evaluated by the

general contractor in advance. Expressed in equation form and taken the absolute value in numerator to eliminate the negative situation, it shows that

\Qd -Mo I a,.=^ (eq-l)

in which is the quoted duration of

subcontractor / in the bidding of specific

subproject j ; jU^ is the mean value of all

quoted duration in bidding market for specific

subproject j ; O^ is the standard deviation of all

quoted duration in bidding market for specific

subproject j. In the same way, (3/, can be

obtained. The present model denominates the

comprehensive uncertainty of (a»(3*Y) as "quasia", compared with the physical variance Q' of

specific asset returns in portfolio theory. Thus, it can be expressed as following equation

a^=a»p»Y {eq-D

From portfolio theory, the comprehensive risk

index CRI can be expressed as

J>>

, = 1 , = 1 j=i

j>i

where the proportion coefficient x, in portfolio

theory, here represents the weight factor which

is equal to the ratio of the quoted price of

specific subcontractor / or j to the quoted

summation of the whole selected combination;

andp,, is the coefficient of correlation between

subcontractor / and j.

The present conceptual model combined three

attributes is depicted as Figure 4 in the space

constructed by ERN, PPD, and CRI three

dimensions. Straightly, the concept model is adherent to the two-attribute model of portfolio

selection to demonstrate it in 3-D space. However, it is quite different and much more

complicated to find the solution between the

utility function surface and nondominated

frontier surface in 3-D space than it is in the 2-D

space. As a matter of fact, the mathematical

construction of utility function surface and

nondominated frontier surface is a very difficult task. Therefore the present model will take the

multiattribute utility theory to search for the

finally optimal selection for decision-making.

5. DECISION-MAKING MODEL

As stated in relevant literature, multiattribute

utility theory evaluates utility functions intended

to accurately express a decision-maker's

outcome preferences in terms of multiple

attributes. It really reduces the complex problem

of assessing a multiattribute utility function into one of assessing a series of unidimensional

utility functions. Accordingly, the three

concerned attributes of ERN, PPD, and CRI in the present model are individually appraised by

the preference of decision-maker. From

Keeney's (1993) theorem, under the assumption

of mutual preferential independence and mutual

utility independence of the three attributes, the

utility function can be expressed as either the

multiplicative function or the additive function.

49
That is, the following equations:

U,,j=[tlyl+kl^uM))-\]/k {eq-5)

i=i /=i

or

1=1 /=1

where Uobj is the objective function of utility; k

is the scaling constant; and u{x) is the individual

utility function for each attribute. The three

attributes in decision-making will also be

normalized to satisfy with the condition that the

summation of all weighted scaling constants is equal to one. Exactly, the additive utility

function of Equation 2 is held in the present

model to formulate the objective function:

3 3 Maximize U^^j = ^ m, ( ), '^k.=\ {eq-1)

i=i 1=1

The maximum utility value implies the optimal

selection for the combination of subcontractors.

The solution for Equation 3 is necessary to decide the scaling constants and individual

utility functions. The method of determining

weights in additive utility models includes

multivariate linear (MLR) or non-linear

regression analysis, analytical hierarchy process

(AHP), direct decomposed tradeoffs and so on (Schoemaker and Waid, 1982). In general, it can be separated into statistical versus subjective

approaches. For simplicity and practical

purposes, the present operation on weights will thoroughly leave to the arbitrary setting by the

decision-maker. More, the sensitivity analysis

will be tested to evaluate the changing

influences of each weight. Consequently, the

procedures for assessing individual utility

functions unquestionably become the most

significant key point in the present model.

Utility theory assumes that a decision-maker can choose among the alternatives available to the

individual to meet the maximum satisfaction

degree in individual preference. This can be

certainly implied the individual is aware of those

alternatives and is capable of evaluating them

through "utility function." Moreover, relative to

a series of objectives it is assumed all information belonging to the various levels of

the objectives can be captured by an individual's

utility function. In effect, a utility function is simply a mapping of the values in the range of an attribute into a cardinal worth scale and can be stated as a formal, mathematical

representation of individual preference structure. Thus if an individual conforms to specific

axioms, a utility function can be constructed.

Utility functions have been used extensively in consumer demand theory and economics, and

they have been applied to private and public

decision-making problems (Goicoechea et al., 1982). For multiobjective problems utihty

functions can completely order the set of

nondominated objectives. The nondominated

solution which yields the highest utility is referred to as the best-compromise solution.

6. CONCLUSION

The present model system is constructed under

the internet-based environment. All the

participants in this system are necessarily

provided with the basic requirements and

functions for web-usage. In other words, the

initial investment to build up a suitable

networking environment is indispensable to this system. Under the current developing

environment, the testing case had ever been

completely dealt with in a few minutes to provide decision-making support following this methodology. Although it is very difficult to evaluate the precisely quantitative benefit and

economic efficiency between the traditional way

to subcontract and the present methodology, it can be greatly expected to reduce the overall

amount of time and capital required for the

complicated process of procurement. Above of

all, it apparently enhances the potential ability to maximize the preferred degree of decision

maker's utility in a scientific manner. In spite

that the system performance is highly dependent on the computing complexity of raising

problems and it will also be compressed by the

bandwidth capacity as well as the flow of web

transportation thereupon, nevertheless, the

present model indeed brings excellent decision

support into full play for the selection of

subcontractors.

REFERENCES

50
1. Davidow, W. H. and Malone, M. S., The

Virtual Corporation, Harper Collins

Publishing, N.Y., 1992.

2. Drucker, P. E., "The Coming of the New

Organization," Harx'ard Business Review,

Vol. 66, No. 1, 1988, pp. 45-53.

3. Goicoechea, A„ Hansen, D. R. and

Duckstein, L., Multiobjective Decision

Analysis with Engineering and Business

Applications, Wiley Publishing, New York,

1982.

4. Johansson, J. and Mattsson, L. G, "Inter- organizational Relations in Industrial

System: A Network Approach Compared

with the Transaction-Cost Approach,"

International Studies of Management and

Organization, Vol. 17, No. 1, pp. 34-48,

1987.

pp. 241-265.

9. Tang, H. C, Study of Construction of Virtual

Organization Model From Network

Perspective, Example: the Electronics and

Information Industries, Ph.D. Dissertation,

Graduate School of Business, National

Taiwan University, 1998.

10. Tapscott, D., The Digital Economy: Promise

and Peril in the Age of Networked

Intelligence, McGraw-Hill, N.Y., 1996.

11. Tsemg, H. P and Lin, P H., "An

Accelerated Subcontracting And Procuring

Model for Construction Projects,"

12. International Journal of Automation in Construction, 2002, pp. 105-125.

Keeney, R. L. and Raiffa, H., Decisions with

Multiple Objectives: Preferences and Value

Tradeoffs, Cambridge University Press,

1993.

6. Keen, P. G W., Shaping the Future: Business Design through Information

Technology, Harvard Business School Press,

1991.

7. Miles, R. E. and Snow, C. C, "Cause of

Failure in Network Organizations,"

California Management Review, Vol. 35,

1992, pp. 53-72.

8. Oliver, E. C, "Determinant of Inter- organizational Relationships: Integration

and Future Directions," Academy of

Management Review, Vol. 15, No. 2, 1990,

GLC /DecinDn Malcx

Figure 1. Architecture and Data Transformation of the Present Model

51
Figure 2. Methodology of The Present Model

Global Market

Note: Mod^edfrom Konsynski (1 993) Figure 3. Evolution of Organization Type Under Networking Mechanism

Figure 4. The Expression for Conceptual Model

52
MOBILE 3D VISUALIZATION FOR CONSTRUCTION

Robert R. Lipman^

ABSTRACT: Until recently, visualization of 3D models required computational

resources available only on desktop computers in office environments. With the advance of technology, it is now possible to visualize substantial 3D models on mobile

handheld computers in the field. This paper discusses some of the current technology,

discusses the use of the Virtual Reality Modeling Language on mobile handheld

computers, shows several examples of 3D structural steelwork models visualized on a mobile handheld computer, and identifies some of the limitations imposed by current technology.

KEYWORDS: construction; handheld computer; visualization; VRML

1. INTRODUCTION

Over the past decade, CAD software for

construction has gone from simple 2D drafting

programs to complex 3D solid modeling systems

that support structural analysis, logical product

models, project management information

systems, collaborative environments, and task

scheduling. The hardware on which those

programs run has progressed from mainframes

to desktop computer and laptops. The size of

computer storage and memory has gone from

megabytes to gigabytes. Communication

between client-server applications has advanced

from dialup modems to always on broadband

and wireless networks.

Mobile handheld computers and personal digital

assistants (PDA) such as PocketPC [1] and Palm

[2] devices are now gaining acceptance as useful

tools at a construction site [3]. Software

applications previously confined to the

engineer's office, are now available on the

construction site. They provide a means to have

access to project information that is stored

locally on the PDA or accessed from a server through a wireless Internet connection. The

information can also flow in the opposite

direction where the PDA is used to collect data

from the construction site and is communicated

back to desktop applications for subsequent

processing.

Although 3D solid modeling is becoming more

popular, there are very few applications for doing 3D visualization on PDAs. A common

format used for displaying 3D models on

desktop computers is the Virtual Reality

Modeling Language (VRML) [4,5], which is a scene description language for representing 3D

interactive models on the web. VRML models

are displayed in freely available VRML plugins

[6,7,8,9] for Netscape or Internet Explorer. A

VRML browser has also been developed for the PocketPC [10]. Most CAD programs can export

their models in VRML format; however, the

VRML representation of a CAD model is not

well suited for viewing on a PocketPC because

of its memory and computational limitations.

The VRML generated from CAD programs

usually does not take advantage of any of the

useful features in VRML to make the file sizes

smaller and more efficient.

2. HARDWARE

The most common type of handheld computers

are PDAs that run either the Palm or Windows

CE operating system. PDAs typically have a screen resolution of 240 x 320 pixels. This low

' National Institute of Standards and Technology; Building and Fire Research Laboratory; Gaithersburg, Maryland 20899-8630

(301)975-3829 robert.lipman@nist.gov http://cic.nist.gov/

DISCLAIMER: Any mention of commercial products does not imply recommendation or endorsement by NIST.

53
screen resolution limits the type of 2D or 3D

information that can be effectively displayed.

Traditional methods of displaying data on a normal sized computer monitor are often not

appropriate for PDAs and new visualization

paradigms need to be developed. Devices

running the Palm OS usually have 8 MB of

memory while newer PocketPCs running

Windows CE typically have 64 MB of memory.

Depending on the operating system, the memory

is used to store the operating system,

applications, and files and provide memory to run programs. PDAs normally do not have a

fixed hard disk. Currently the processors in PDAs are not very powerful or suited to dealing

with large amounts of data that might be needed

for 3D CAD applications. The first 2D graphics

accelerators for PocketPCs are only beginning to be available [11].

The user interacts with the PDA using a stylus to pick menu items or to write on the screen. Some

PDAs have a small joystick-like device to aid in navigation. Detachable keyboards can also be

used to enter information. Files and applications

are usually transferred to and from a PDA by

synchronizing with a host computer.

Information can be transferred directly between

PDAs or other computers by beaming it through an infrared port.

Most PDAs have expansion slots for compact

flash memory, wireless Internet access, and

other CF or PC expansion cards such as global

positioning system receivers or barcode

scanners. Some PDAs have built-in wireless

access. There are even PC expansion cards that incorporate a 1 GB miniature hard drive [12].

With this amount of storage on a handheld

device, an enormous quantity of information can

be brought to the construction site.

One of the primary limiting factors for

displaying 3D data on a PDA is the amount of

built-in memory. Adding memory or a hard

drive through an expansion slot only increases

the amount of space available for storing

programs and files. The memory available to run programs is restricted to whatever is built-in to the PDA. For example, in a PocketPC

running Windows CE with 64 MB of memory.

by default, half of the memory is allocated to storing programs and files and the other half to running programs. The memory allocation

between storing and running programs can be

adjusted to provide more or less of the built-in memory to each function.

There are also several PDAs that run the Linux

operating system. Larger pen-based tablet computers run the Windows XP operating

system. One manufacturer has even developed a pocket-sized computer that runs Windows XP

with a 10 GB hard disk and 256 MB of memory

[13].

3. SOFTWARE

Several CAD and construction related software

applications are commercially available for PDAs. In general, the more complex and

graphics oriented applications run on PocketPCs

with the Windows CE operating system.

Applications that run on Palm devices are usually text oriented such as punch list, project

management, or scheduling software. Research

into collaborative dynamic project management

has shown how PDAs and even web-enabled

cellphones can be used as wireless display

devices for traditional desktop construction

management software [14].

A number of 2D graphics applications that display traditional CAD drawings in DWG,

DXF, or DGN formats are available for PDAs.

Some of the programs can display the drawings

directly, while others require that the drawing be

converted to a proprietary format that is optimized for the software. Other applications

provide the means to markup existing or create new CAD drawings [15,16]. Certainly the low

screen resolution and small screen size are limiting factors for the utility of working with

CAD drawings on a PDA. Version control of

CAD drawings between a PDA and desktop

computer is also of concern. Simple file synchronization may be inadequate when format

conversions are taking place on one platform but

not the other.

The development of 3D visualization programs

is only in its infancy. At least two commercial

54
products are available for developing and

delivering 3D content and applications for PDAs

and other mobile devices [17,18]. However,

these applications are geared towards 3D games

and not to 3D visualization for CAD.

Preliminary research at IBM led to the development of a 3D viewer that could display a subset of VRML [19] on a PocketPC.

Pocket Cortona [10] is an inexpensive VRML

viewer for PocketPCs that supports most of the

VRML specification including application

specific nodes. VRML models that are generated by CAD programs can be displayed in Pocket Cortona without modifications. Pocket

Cortona can run in a standalone mode or as a plugin to a web browser. In the standalone

mode, the VRML file to be displayed is stored

locally on the PocketPC. PocketPCs with a

wireless Internet connection, web browser, and

Pocket Cortona can access VRML models

through a web page in the same way they are accessed on a desktop computer.

4. VRML

VRML is an ISO standard [20] for describing

3D geometric objects and their behaviors.

Information in a VRML model is arranged in a scene graph that defines the parent-child

relationship between VRML nodes. Some

common VRML nodes describe 3D shapes, the

appearance of the shapes, and geometric

transforms that can be applied to the shapes.

The shapes include primitives such as boxes,

spheres, cones, cylinders, extrusions, and

general sets of points and polygons known as IndexedFaceSets. Transforms that can be

applied to the primitives include translation,

rotation, and scale.

Typically the VRML models exported by CAD

programs use IndexedFaceSets and geometric

transforms to represent all of the geometry in a model. While this provides an accurate visual

representation of the geometry, it does not take

advantage of several features of VRML to reduce the file size and make the processing of

the VRML model much more efficient.

The VRML prototype mechanism allows for the

creation of application-specific geometric

objects similar to the built-in primitives such as boxes, spheres, cones, and cylinders. Research

at NIST [21,22,23] has developed a mapping

between the CIMsteel Integration Standard

(CIS2) [24] and VRML. CIS2 is a logical

product model [25] for describing steel structures and has been adopted by the American

Institute of Steel Construction as their standard

for electronic data interchange [26]. VRML

prototypes have been developed that correspond

to CIS2 entities such as parts (beams, columns,

braces, clip angles, plates), bolts, holes, welds,

and locations.

Another important feature of VRML, which is usually not implemented in the VRML model

exported by a CAD program, is the ability to define one geometric object and create many

instances of it. In a typical steel structure there are many identical parts, each with their own

location. In the VRML model only one of each

type of part needs to be modeled. The rest of the

VRML model is built from instances of the

defined parts. This is much more efficient than

modeling all of the geometry explicitly.

VRML models using the CIS2 related VRML

prototypes represent a steel structure much more

efficiently, effectively, and intelligently than the

VRML models exported from a CAD program.

Therefore much larger models can be displayed

in a VRML browser on a handheld computer.

With this capability, 3D visualizations of CAD

models of steel structures can be viewed in the

field at a construction site.

5. EXAMPLES AND CONCLUSIONS

The following VRML models were displayed on

a Compaq iPAQ H3670 PocketPC [27] with 64

MB of memory running Pocket Cortona. The

memory allocation was adjusted so that 40 MB

was available to run programs. All steel parts

with the same cross section have the same color,

but all parts with the same color do not

necessarily have the same cross section. All I- and T-beams are green, yellow, and cyan. All

other sections are red, magenta, or blue except

plates, which are gray.

55
Figure 1 is a VRML model of a simple three

story steel structure with diagonal bracing. This

model is small enough that the user can easily

interactively move around the structure. Figure

2 is a VRML model of the steel support structure

that is part of the emissions control system

(ECS) ductwork for the NIST Large Fire

Research Facility [28]. This model contains over 1600 parts and is a good example of the

limitations of displaying VRML on a PocketPC.

To minimize the number of polygons that are displayed, the thickness of the webs and flanges

have been ignored. Nevertheless, it takes about

five minutes for the model to display and is so

large that the user cannot interactively navigate

through the model. The only way to move

around in the model is with predefined

viewpoints in the VRML model. Small details

such as the handrail look incomplete because of

the low screen resolution. Figure 3 shows more

detail of the structure in Figure 2. A close up

view of a connection is shown in Figure 4. The

location of the head of several bolts is shown as

a black cross.

These examples show how 3D visualizations of

steel structures can be displayed on a PocketPC.

The VRML models are generated directly from

CIS2 files and use VRML prototypes and other

features to make the VRML files smaller and more efficient to process. Although there are

limitations to the size of a VRML model that can

be effectively displayed on a PocketPC, the

inevitable improvements in processing power

and graphics accelerators for handheld

computers will provide an improvement for 3D

visualization in the future. Within several years,

it should be practical to make 3D visualization on PDAs a commonplace tool at construction

sites.

6. REFERENCES

1 . Microsoft Mobile Devices PocketPC,

http://www.pocketpc.com/

2. Palm, http://www.palm.com/

3. Saidi, K., Haas C, Balli N., "The Value of

Handheld Computers in Construction", in the Proceedings of the 19'*' International

Symposium on Automation and Robotics in

Construction, Washington, DC, September

2002.

4. Ames A., Nadeau D., Moreland J., "VRML

2.0 Sourcebook (2"'' edition)", John Wiley &

Sons, Inc., 1997.

5. Web3D Repository,

http://www.web3d.org/vrml/vrml.htm

6. Cosmo Player, http://www.ca.com/cosmo/

7. Cortona,

http://www.parallelgraphics.eom/products/c

ortona/

8. blaxxun Contact, http://www.blaxxun.com/

9. Pivoron Player, http://www.nextemet.com/

10. Pocket Cortona,

http://www.parallelgraphics.eom/products/c

ortonace/

11. ATI Imageon 100,

http://www.ati.com/technology/hardware/im

ageon 1 00/index.html

12. IBM Microdrive,

http://www.storage.ibm.com/hdd/micro/inde

x.htm

13. OQO Corporation, http://www.oqo.com/

14. Pena-Mora F., Dwivedi G.H., "Multiple

Device Collaborative and Real Time

Analysis System for Project Management in Civil Engineering", Journal of Computing in Civil Engineering, January 2002.

15. Arc Second PocketCAD,

http://www.pocketcad.com/

16. GiveMePower PowerCAD,

http://www.givemepower.com/

17. Fathammer Ltd. X-Forge Technology,

http://www.fathammer.com/x-forge/

18. Superscape Swerve,

http://www.superscape.com/

19. "Pervasive 3D Graphics", Visual and

Geometric Computing Group, IBM T.J. Watson Research Center,

http://www.research.ibm.com/vgc/pdaviewe

r/ 20. ISO/IEC 14772-1, "The Virtual Reality

Modeling Language (VRML)", 1997,

http://www.web3d.org/vrml/

2 1 . Visualization of Steel Structures from

CIMsteel Integration Standards (CIS2) Files,

http://cic.nist.gov/vrml/cis2.html

22. Lipman R., "Mapping VRML Prototypes to the CIMsteel Integration Standards", to appear.

56
23. Lipman R., Reed K., "Visualization of

Structural Steel Product Models", Electronic

Journal of Information Technology in Construction, to appear.

24. Crowley A., Watson A., "CIMsteel

Integration Standards Release 2", Steel

Construction Institute Publication P268,

2000, http://www.cis2.org/

25. Eastman, C, "Building Product Models:

Computer Environments Supporting Design

and Construction", CRC Press, 1999.

26. AISC Electronics Data Interchange,

http://www.aisc.org/Content/NavigationMen

u/Steel_Solutions_Center/Time,_Money_an

d_Management/Electronic_Data_Interchang

e/Electronic_Data_Interchange.htm

27. Compaq iPAQ,

http://athome.compaq.com/showroom/static/

iPAQ/handheldJumppage.asp

28. NIST Large Fire Research Facility,

http://www.bfrl.nist.gOv/info/facilities.htmI#

bum

Figure 1. Three story structure with diagonal

bracing.

^ Cortona 3:27p @)

Figure 2. Steel support structure for the NIST

ECS.

57
Figure 3. Detail of the steel support structure for

the NIST ECS.
DIGITAL ARCfflVAL OF CONSTRUCTION PROJECT INFORMATION

By

DeWitt Latimer IV^ Chris Hendrickson^

ABSTRACT

The Digital Library Initiative (DLI) concerns itself with the automatic creation, organization, and

indexing of complex collections of data. With its own wealth of data types, the construction industry

pushes the boundaries of the current technologies,

especially with regards to automatic archival of

construction project information. Many issues unique

to the construction projects, such as data provenance

and multi-media searching, require the integration of

many technologies being developed at the various

DLI funded research universities. This paper seeks to define those issues, the research being done, and

provide some direction for future work in this area.

KEYWORDS

Digital Ubrary, document management, project

document archival

L INTRODUCTION

Construction projects generate volumes of

information on a regular basis. However, access to

this information can be difficult or awkward.

Typically a person must go to a document area and

rifle through papers, copies, or other documents to locate a specific document. Even worse, if a specific

item is to be investigated, then the researcher must know where to search for informadon. If searching

for information about a defect in the built entity, the researcher's information may be in the construction

plans, meeting minutes between the contractor and

the owner, in a bill of materials for parts relevant to the defect, inspector's reports, or even in a pre- construction environmental study. This problem is exasperated by the many media types common in the construction industry, apphcation data files (such as CAD models, project schedule databases, or analysis

calculations), images, structured formal documents,

analysis results, and even audio or video. Although

dl4s@andrew.cmu.edu

" cth@andrew.cmu.edu

Department of Civil and Environmental Engineering

Carnegie Mellon University

5000 Forbes Ave

Pittsburgh PA 15213

current web search technologies are becoming more

sophisticated, these methods do not necessarily

extend well to multiple distinct types of media. In a sense all these various media are the "documents" of

the project.

This search problem is even an issue for construction document management. Current efforts in document management systems focus on 4 main

issues: central storage of documents, routing of

documents to interested parties, document version

control, and security of documents. On the other hand, archiving is not only concerned with the saving

of all versions of all documents over time but also indexing and providing an interface that allows for search across all the documents. Needless to say, the

additional effort, and therefore cost, needed to properly archive documents is outside the budgets of

construction projects. What is needed is a means of

automatically generating archive documents quickly

without much effort. The digital hbrary initiative [4] is sponsored by

many federal agencies, including the National

Science Foundation, DARPA, NASA, the National

Library of Medicine, and the Library of Congress,

among other federal agencies and private sector

interests. Currently in its second phase, the goal of

this program is to develop digital library technologies on a broad base to support the growing need for access to information. Many university research

efforts are sponsored through this initiative. These

universities are developing the base technologies and

sciences to support the generation of these archives. Much attention is being paid to multi-media archives

and archives with little, user-provided structure. The remainder of this paper is organized in 4

sections. Section 2 provides the goals for archiving

the documentation of a construction project as well as

a taxonomy of the types of documents for typical

construction projects; addressing these goals are the requirements for successful implementation of a

construction digital hbrary. Section 3 briefly outUnes some commercial systems to indicate where these systems fail to meet the goals. Section 4 outhnes some of the current research being performed that may be apphcable to solving the issues in archival of

59
construction projects. Section 5 closes the document

by stating some conclusions from the material presented and suggests directions for future work.

2. ARCHIVING A CONSTRUCTION

PROJECT

2.7 Goal

The goal of a construction project archive is to provide a searchable data repository that represents

both the final constructed artifact and the process that was used to construct the artifact. This archive must

be constructed from the materials provided and yet

must minimize the user's involvement in the creation of indices or other organizational tools (including

keywords) needed to operate the archive. Care must

be taken to ensure that the archive can handle the wide scope of items to be covered as well as able to manipulate the digital representation of those items

(i.e. the various media formats).

2.2 Construction Information

Table 1 indicates a list of items that can be

expected on a typical construction site. This table was inspired by the work of de la Garza and Howitt

[18].

Request for information

Materials Management

Equipment Management Cost Management Submittals Safety QC/QAInterperso

nal

Schedule means and methods

Jobsite record keeping

Future Trends

Design intent and

clarification Access to material management

Equipment

location Budget Test results

Accident

reporting

Initiate inspection

s Emails Schedule

Recording

timesheets

Positionin g data

Subcontractor

information Material location Fuel monitoring

Material cost accountingRevisions to submittalsReporting

violations

Report QC/QA

problems

Voice

Mails Schedule

updates

Progress

reporting Sensory

data

Contract

specifications Material order status

Equipment cost accounting Physical Artifacts Safety Plans

Reporting

inspection

s results

Meeting

Minutes

Delay

recordings

Exception

reporting

Contract drawings

Request materials to

site

Personnel cost accounting CAD ModelsTest

Artifacts

As-built records Visitor's log

Worl< package

information

Place material orders Purchase Orders Test PlansProductivity information

Daily Constructio n Reports Means and methods

Material Specifications QC/QA

Plans Images / Photos

Implementation problems

Table 1 - Typical documents of a construction project, by type

From the construction documents listed in Table 1 , a

Ust of digital data/file types was generated [Table 2]. File types are the digital representation of documents, as they

would be stored in a digital archive. It is essential for any

archival system to cover the breadth of these file types,

given that each may contain information that is only

referenced in that specific type of file.

Text

Digital Images

Application Data Files Voice Video

Formal

Structured Documents

ASCII BMP

MS-Project

Files VRML WAV MPEG XML

MS-Word JPG MP3 AVI CIM-Steel

PDF TIFF Pro-E

Real Audio

Real Videospread

sheets Word

Perfect GIF AutoCAD AU MOV

CIS/2 documents

ble 2 - Digital file types by application

A system must ehminate or mitigate all the fallacies, handle all the formats and document types would be a necessary requirement/criteria for successful implementation of a construction digital library.

3. COMMERCIAL SOLUTIONS

Several commercial products exist that provide

document management services, but do not pass muster as an automated archival tool. Yet these products are Ukely

to evolve over time, as the research described in section 4

matures. JobDocs.com [8] provides an image management

system for clients. While this service provides an engine

for storing digital imagery about a job site, it does not automatically link the images with other project

information, such as CAD models, product information, or meeting minutes. Additional storage of image versions is apparently handled by the user and not provided by the system.

Autodesk [1] provides a project collaboration

environment for the management of print materials. While

the environment does provide for managing document

versions, the service does not provide for searching the contents of the documents themselves. Meridian project systems [9] provides products for project management. The ProjectTalk [13] suite offers document management [14] functions. However, like Autodesk, this system is limited in its approach to searching for information. ProjectTalk behaves more like a file repository than a searchable archive.

60
In addition to the above systems, Amor/Faraj [17]

provides a look into some of the reasons that integrated

project databases (document management systems) fail. After some revision and simpUfication, we can identify 10

fallacies that may lead to a failure of integrated project databases:

1. An object-oriented system provides the complete solution;

2. A coordinated model solves representation

problems;

3. A complete model of reality required;

4. User views are reconcilable;

5. The Internet solves the communication

problem;

6. Printed documents will disappear;

7. CAD is the center of the archive;

8. No data ownership problems exist;

9. A database guarantees coordinated, consistent information;

10. The industry is ready to adopt such databases. We will address these points in turn.

may be proprietary, sensitive, confidential, or otherwise

restricted for legal or business reasons. A database guarantees coordinated, consistent information - Databases do not inherently solve the data consistency issue; by themselves databases do not guarantee the consistency and coordination of data, but respond to the data models with which they are designed.

The industry is ready to adopt such databases - Finally, the construction industry is notoriously IT poor;

end users may not be receptive or have the inherent computing capability to support and use these IT systems.

4. DIGITAL LIBRARY TECHNOLOGIES

Many universities are participating in the Digital

Library Initiative, however research at seven universities (Carnegie Mellon, Columbia, Cornell, Penn, Stanford,

Berkeley, and UC-Santa Barbara) is quite relevant to the development of a digital archive of construction projects.

These projects were noted because they directly answered one or more of the challenges presented in the previous

section.

An object-oriented system provides the complete

solution - From a computer science perspective, objectoriented system development is a method to develop

software systems, and in itself does not solve any

problems.

A coordinated model solves representation problems - Coordinated model(s) for very complex systems are

difficult to create as can be evidenced by the slow

development of industry foundation classes (IFC) [20] and

the standard for the exchange of product data (STEP) [19]

product descriptions; plus these representations, and

systems based on these representations, will need constant updating as building technologies change.

A complete model of reality require - Completely

modeling the reality of the site is not likely to be possible,

however, any candidate system should be able to operate

in a partial-information world. User views are reconcilable - User views may not be

reconcilable (certainly unless there is an information

model).

The Internet solves the communication problem - The

Internet does not, by itself, solve data communication

issues, but is a tool that can be used to build systems that solve the problem.

Printed documents will disappear - Paper documents

will likely still exist even with an easy access digital

system.

CAD is the center of the archive - While useful for laying out spatial problems, CAD also cannot serve as a

central data model for items such as equal opportunity

reports, administrative budget items, and other items may

not be Unkable directly to structures. No data ownership problems exist - In the business

world, not all data may be viewable to all users, as the data

4.1 Carnegie Mellon University

The Informedia-II Digital Video Library [6] project at Carnegie Mellon University (CMU) focuses on building

digital libraries from video sources. The project is automatically indexing and providing searchable interfaces

to video news media. These indices are built by

segmenting the video stream and using speech recognition

to automatically generate transcripts of the sessions. In addition to normal textual querying of the archive, visual interfaces are being developed to query the archive with an image as the key. This visual querying works by having

the user selecting a figure of interest in the video stream

(typically a face) and then asking for matches. This

provides a multi-media querying interface. In a related project at CMU CCRHE (Capturing,

Coordinating, and Remembering Human Experiences) [7], the video stream is augmented with sensory and position

data. In this case, querying for video can be done by

querying for the geographic position. As intended, this would be for looking for a memory of a trip; however in a construction appUcation this capability could be used to ask for video from the location of a specific building

feature.

4.2 Columbia University

PERSIVAL (PErsonahzed Retrieval and

Summarization of Image, Video And Language resources)

is a patient care digital library [10] being developed at Columbia. This library take a pre-existing user model of

health care professionals and provides an interface that attempts to predict the user's needs and interests. The

information presented is from an online collection of

patient records maintained by the hospital.

61
These records, in addition to information brought in from journal and web pages, are on distributed systems

covering many different media (voice, image, text, etc.). Attention must be given to fusing together potentially

conflicting information; methods such as automatically

identifying source type, quality, and level of intended

audience is needed so that the system can present

information appropriate for the type of user performing the query (from the user model).

Other component technology to be developed are multi-modal query input, automatically augmenting

queries based on current patient records, search and

presentation of multi-media resources, supporting

browsing over automatically constructed categories,

graphical layout of multi-modal material, presentation and

summarization of multiple relevant documents, merging

repetitive information, and generation of appropriate level summaries.

The user based model approach may be helpful in the construction context since different participants have very

different interests.

4.3 Cornell University

The Prism project [12] at Cornell focuses on digital

library research in many areas. Some areas that are most

relevant to construction project archiving are digital object

architecture, human-centered research, and poHcy

expression and enforcement.

The FEDORA (Flexible and Extensible Digital Object

and Repository Architecture) project focuses on reUable and secure means to store and access digital content. This

project seeks to address the creation of objects that aggregate heterogeneous types of data from distributed sources. Then the architecture allows objects to have

global and/or domain-specific behaviors. The architecture

is designed to support multiple viewing modalities, based on client access. The architecture utilizes a rights

management model to aid in the creation of a "view of an

object" contents. The human-centered research group has deployed a

field access system that utiUzes global position sensing

(GPS) and laser tracking (for indoor appHcations) to provide context-aware delivery of resources. On a construction site, this may be used to queue the plans to the room in which the person is currently located. Further,

the group has studied the search patterns of users based on

resource availability, relative expertise, and user

characteristics (such as gender), which can greatly help

deliver the right information in the field to individuals. The policy expression and enforcement group focuses on a suite of tasks to deliver automated policy enforcement

for digital Ubraries. The first task is generating a formal

definitions and declarations, which provides a poUcy

specification. Then, automated enforcement agents must

be capable of understanding and acting upon the

declarations. These behaviors manifest by the system

allowing and encouraging permitted actions and denying

unauthorized actions. The exact details of this behavior

can be complex when considering distributed, mobile ] objects with various methods available dependent on the security access of the user. This work is moving towards a formal logic for such security specification.

4.4 University ofPennsylvania

The PENN Database Research Group has undertaken

the exploration of data provenance [11]. Data provenance

is the path the data took to become in the form being

viewed. The provenance answers questions such as where

and how the information was produced, who has corrected

it, and how old it is. This tracking is essential to understand the past history of an item in the database, as well as fully appreciate and rely on the current state of the

item.

4.5 Stanford University

The Stanford Digital Libraries Project [15] is looking

into issues of interoperability, mobile access to digital

libraries, and archival. Interoperability thrust is focused on the SDLIP

(Stanford Digital Library Interoperabihty protocol).

SDLIP describes an interface for clients to request searches be performed over multiple clients by a library service proxy. This proxy would then communicate, using

protocols defined elsewhere (such as Cornell's FED0RA[12]) to contact the data sources and perform the actual query to the databases. This protocol is already past

its first release and is being refined through involvement

vvdth other, non-Stanford Ubraries. The mobile access to digital libraries thrust is spearheaded by the development of a power browser for personal data assistants (PDAs). This power browser

integrates automatic generation of indices of web pages

with the necessarily Umited resources of remote PDA

computing.

The archiving thrust is concerned with the development

of methods for local and wide-area archiving of file systems and replication of archives. Further, this thrust is concerned with the generation of cost/benefit analysis

tools, such as a simulator, to help guide the design of

archives.

4.6 University of California at Berkeley

The Digital Library Project at Berkeley [16] has three research areas of interest: computer vision in digital libraries [3] and a geodetic information system (GIS)

viewer [5]. The use of computer vision in creating a digital library

enables the creation of large, automatically annotated data

stores from digital images. Performing object recognition on images enables each image to be labeled with its contents. From here, interfaces for statistical based

queries on the data are being developed. Further work is being done to be able to query a database for images

62
relevant to a passage of text (such as one from another

document).

The GIS Viewer 4.0 is designed as a tool for displaying, manipulating, editing, querying, and otherwise

interacting with layered geo-spatial information. In construction, spatial information is normally presented in various layers, floors, electrical, plumbing, etc.

4.6 University of California at Santa Barbara

The Alexandria Digital Earth Prototype [2] project at UC Santa Barbara is seeking to develop a digital Ubrary

environment and service based on the digital Earth

metaphor. The focus of this research is to create and use

Iscapes (Information Landscapes), which are a

personalized digital information collection. These Iscapes

are intended to have layered services which organize,

access, and use different types of information. Currently,

the project is focusing on creating these Iscapes for learning/educational purposes in undergraduate classes.

5. CONCLUSIONS

From the survey of digital library technologies, there is much support for the argument that a digital archive, or

library, can be built for construction projects. Although

research is not currently directed at this specific domain,

the research of the many universities provide the key

technologies to solve most of the 10 issues in developing

an integrated project database brought forth by previously

[Table 3].

adopt such a system

Issues Technologies Universities

1 . 00 does not provide

complete solution

Developing paradigm

independent models

of archives

Cornell

2. Coordinated model

does not solve

representation

Do not assume

documents conform

to a single structure

Cornell, Stanford

3. Complete model of

reality required

Create reports and

views based on

partial information

Columbia

4. User views are reconcilable

Architectures to support multiple user views

Columbia,

Cornell, Berkeley, Santa Barbara

5. Internet solves communication problem

Specific digital library/archive protocols for communication

Stanford

6. Paper documents will disappear

Multi-media

archiving

CMU,

Berkeley, Santa Barbara

7. CAD is the center of

the database

Loosely distributed document structure

Cornell, Stanford

8. No data ownership

problems Data security, migration, and

ownership model

Cornell

9. Database guarantees

coordinated, consistent information

Data provenance

theories to aid in maintaining data

U Penn

10. Industry is ready to Not Addressed NA

Table 3 - Technologies to Address Issues of Integrated

Project Databases

Although object oriented systems are heavily promoted

to be the principal architecture upon which a library is built, there is no assumption of the structure of the underlying data components. Indeed, the systems that propose object structures for the digital Ubrary interaction assume no structure for the underlying objects, which are normally items such as web pages, digital books, or image

files.While all digital library systems propose a model of the

library, almost all research into searching the library and

structuring the Ubrary is by viewing the underlying

documents as "unhelpful." In this case, unhelpful means

that the document contains little or no meta-information

specifically designed to help a search engine, or to help

build links between different documents. On a higher

level, this means that no one model of underlying

documents is assumed.

Some research is being done to address answering

queries when incomplete information is available. Specifically the work at Columbia targets generation of

reports based on potentially incomplete information. Also,

the work at Penn on data provenance gives cUent

appUcations the ability to determine the sources, and thus

the potential gaps, in the knowledge available. In almost all systems, a single user view is not assumed, and a great deal of attention is being devoted to the creation of personaUzed user views. This will allow

disparate user views to be built from various user profiles

to suit the needs of the various users. The current architecture research being performed in

digital libraries understands that the internet is not a panacea that solves all networking problems. Indeed the current architecture projects appear to be very cognizant of

the need to develop reasonable protocols for interacting

with the digital Ubraries. Given the highly distributed nature of the digital

Ubraries being considered, no one data item appears to be

driving the structuring of the archives. Thus, there is no

misconception that CAD, or any other document type will be central to the archive. The data security work at Cornell is specifically

targeting the creation of ownership and access management technologies. With these technologies, a system can be envisioned which will allow contractors, subcontractors, architects, engineers, owners, and other

interested parties to be able to connect systems together

with each managing their own access rights. And upon

commissioning, the mobile Ubrary projects at several

universities can make sure that information allowed to be

mobile is automatically migrated to the owner's systems.

Peim's work on data provenance directly addresses the coordinated and consistent information issue. When the provenance work is combined with the Columbia work,

which focuses on ranking various input sources for appropriateness and handles inconsistencies among

63
sources, then there is the ability to generate a system that can recognize and handle coordinating information to present consistent information to the users. Two areas that are lacking in the current research are very specific to the conslrjction industry and must be

solved in the scope of developing a library specifically for construction projects: the issue of physical documents and

the readiness of industry to adopt such a technology. In order to successfully manage documents and ensure they

are entered into the system, a series of procedures and

field protocols need to be developed. To prepare the industry to receive this research will require economic

impact analyses that are outside the scope of the current

research. Overall, there is clearly a critical mass of technology

being developed that can support the creation of a digital

archive for construction projects. The next step should be

the formalization of requirements for such an application

and the development of a prototype based on the components already available and/or under development.

6. REFERENCES

[1] "Autodesk BCS: Project Collaboration and

reprographic print management for building, design and

management for building, design, and management

professionals", http://www.buzzsaw.com/, accessed on

2002-03-30

[2] "Award #9817432 - DLI Phase2: Alexandria Digital Earth Prototype",

https://www.fastlane.nsf.gov/servlet/showaward?award=98

17432, accessed 2002-03-30

[3] "Computer Vision Meets Digital Libraries",

http://elib.cs.berkeley.edu/vision.html, accessed 2002-03-

30

[4] "Digital Libraries Initiative Phase 2",

http://www.dH2.nsf.gov/, accessed 2002-03-30

[5] "GIS Viewer 4.0",

http://elib.cs.berkeley.edu/gis/index.html, accessed 2002-

03-30

[6] "Informedia Digital Video Library at CMU",

http://www.informedia.cs.cmu.edu/, accessed 2002-03-30

[7] "Informedia-II Digital Video Library", sub-Utle: "CCRHE - Capturing, Coordinating and Remembering

Human Experience",

http://www.informedia.cs.cmu.edu/ccrhe/index.html,

accessed 2002-03-30

[8] "JobDocs.com online construction documentation

image management system", http://www.jobdocs.com/,

accessed 2002-03-30

[9] "Meridian Project Systems - Comprehensive solutions

for organizations that rely on successful projects",

http://mps.com/. accessed 2002-03-30

[10] "PERSIVAL - A Panent Care Digital Library",

http://www.cs.columbia.edu/diglib/PERSIVAL/, accessed

2002-03-30

[11] "Penn Database Research Group: Data Provenance",

http://db.cis.upenn.edu/Research/provenance.htmI,

accessed 2002-03-30

[12] "Prism Home Page", http://www.prism.comell.edu/,

accessed 2002-03-30

[13] "ProjectTalk.com - where the project team meets",

http://www.projecttalk.com, accessed 2002-03-30

[14] "ProjectTalk.com | Project Management | Document

Management",

http://www.projecttaIk.com/MK/pm/doc.shtml, accessed

2002-03-30

[15] "Stanford Digital Libraries Project, The", http://wwwdiglib.stanford.edu/, accessed 2002-03-30

[16] "UC Berkeley Digital Library Project",

http://ehb.cs.berkeley.edu/, accessed 2002-03-30

[17] Armor, Faraj, "Misconceptions About Integrated

Project Databases", Electronic Journal of Information

Technology in Construction, Volume 6, 2001,

http://www.itcon.Org/2001/5/paper.pdf, accessed 2002-

03-30

[18] Garza, Howitt, "Wireless communication and

computing at the construction jobsite". Automation in Construcdon, Volume 7, Number 4, pg. 327-347

[19] "Industrial automation systems and integration - Product data representation and exchange". International Organization for Standardization, Standard 10303-1:1994

[20] "IPC Object Model Release 2.0", Industry Alliance

for Interoperabihty, CD-ROM, 1999

64
Jt-WUKK: ItUL JMi^Al 11 t^KA llUfN ir\ (JOINS I KUC l lOJN MA 1 EKlALti

MANAGEMENT SYSTEMS

Daniel Castro-Lacouture' and Miroslaw J. Skibniewski^

' Ph.D. Candidate, School of Civil Engineering, Purdue University, West Lafayette, Indiana, 47907-1294, USA

http://bridge.ecn.purdue.edu/~castrola

^ Professor of Civil Engineering, Purdue University, West Lafayette, Indiana 47907-1294, USA

http://bridge.ecn.purdue.edu/~mirek

Abstract: The initiative of implementing Internet-based solutions for the integration of the supply chain of materials

will not succeed if there is not assurance of collaboration and communication among the parties in the construction

business. Neither EDI nor web-based supply chain applications can facilitate both the process integration and flexibility required by the construction processes practiced today. E-work is a suitable concept for this endeavor because

it comprises principles that allow cooperation and collaboration in the organization. The research described in this paper follows upon recent publications on E-work models in order to propose a set of apphcations in construction

materials management systems. Expected benefits are related to conflict resolution and reduction of lead times and

subcontractor overhead costs. Implications of this work with respect to the initiatives based on lAI/IFC or STEP

models comprise the potential for prediction of materials requirements with the use of task administration protocols

and autonomous agents.

Keywords: E-work, materials management, protocols, agents

1. INTRODUCTION

1.1. Supply Chain of Materials in

Construction Processes

Construction processes rely in a great extent

in the exchange of information and permanent

interactions of entities and resources. Even

though the configuration and set up of machines is usually different than in the manufacturing industry, the interrelations of rele- vant participants in a construction process are considerable, and their management will have

a direct impact on the success of the project in terms of time, cost, quality and morale.

There are other considerations that need to be addressed when designing a construction

materials automation system, such as the effect of design in the construction process, the iso- lation of materials procurement from design,

differences in CAD formats, use of nonintegrated databases, brief and usually poorly

coordinated contribution of subcontractors in the design and procurement processes, etc [3]. These problems are well documented in the

construction literature, and have been in recent years a subject of study of several business or- ganizations such as the Construction Industry

Institute in the United States and related bodies worldwide. The initiative of implementing

a collaborative e-business solution for the in- tegration of the supply chain of materials, such

as steel reinforcement rebars, will not succeed

if there is no assurance of collaboration and

communication among the players in the construction business [3].

It is possible to deploy an e-commence

function with the objective of performing

transactions between contractors, suppliers and

clients. In fact, that can be done easily and is currently being utilized by construction material suppliers and contractors. Ordering, bill- ing and information-sharing functions are common in the form of Web-based applications [11]. However, by merely setting up a

transaction platform framed by e-commerce

principles, the success of the integration of

critical stages in the construction process is not

necessarily guaranteed. Moreover, it is needed

to consider a new concept that fosters effectiveness in the overall supply chain system in- tegration, that is, to achieve adaptability of re- sources throughout the supply chain of

materials in the overall construction process, or to rapidly adapt to changes in the required

product quantity and design [10]. This concept must integrate the general and specific

project design in order to avoid conflicts in the

subsequent stages of the project development.

The objectives of the materials supply

chain automation consist of minimizing processing costs, enhancing delivery and response

times and improving communication in order

to expedite conflict resolution. Although the
scope of this research is confined to describe

the use of E-work models, metrics associated

to these model objectives will be originated

from time studies, workflow simulation, ac- tivity-based costing and frequency of documented delays due to conflicts. The idea of

automating the supply chain of materials must

consider the multiple sources of disagreement

related to negotiation protocols among contractor, subcontractor, material supplier, designer and client, as a consequence of the

struggle to obtain better prices and product

quality. An electronic market system can re- duce customer's cost of obtaining information

about prices and product offerings of alternative suppliers, as well as supplier's costs of

communicating information and negotiating

about the prices and product characteristics

[2].

1.2. E-work and Autonomous Systems

E-work is composed of the collaborative,

computer-supported activities and communications-supported operations in highly distrib- uted organizations, and also investigates fundamental design principles for their

effectiveness [13].

The goal of E-work for this research is to integrate the components of the construction

supply chain of materials, from structural design to procurement and assembly. The utili- zation of this approach is justified by the as- sumption that construction processes are composed of highly distributed organizations

of autonomous systems. This assumption is based on the unique nature of the construction

industry in terms of interactions among busi- ness partners, clashing interests, isolated design and procurement, etc. In addition, every

construction project is different from another.

The materials, procedures, contractors, design

firms, or contracts in construction projects

may be similar, but the final product is evidently different. It is a customized product that has to evolve from the initial stages of client

briefing to the complex states of seismic re- sistance, fit outs and finishes. That is one

strong reason to consider this organization as complex and composed of autonomous sys- tems. These systems are composed of the

equipment, hardware or software utilized by

various designers, suppliers, subcontractors or

contractors in order to achieve the goal of

project completion [3].

Figure 1 shows a sample of the numerous

interactions among project stakeholders in or- der to approach the process of design, revision

and procurement of materials for the structural reinforcement division of a standard construction project.

Dg

S

ST

Revision

Dg Dt LA LA i i

SH SH ST

Revision <- -

Prep M Revision

SH

' H Correction

/

/

Procurement

\

i L i k

Dt Dg

ST: Structural Drawing

SH: Shop Drav^flng

Figure 1. Scheme of interactions during the

design, revision and procurement of materials on a standard construction project.

The terms C, S, Dg and Dt stand for Contractor, Rebar Supplier, Designer and Detailer.

2. MODELS OF E-WORK

2.1. Task Administration Protocol (TAP)

Task Administration protocols are defined

as the logical rules for the workflow control

that enable effective collaboration by communication and resource allocation among pro- duction tasks [14]. Effective collaboration, in

66
the context of a supply chain, stands for obtaining real-time information, minimizing cost, increasing levels of service, improving communication and enhancing delivery and re- sponse times [8]. Within the context of the

construction process and in particular for the case of construction materials management,

the following protocols are defined in Table 1.

Table 1 . E-work solution algorithm with Task

Administration Protocol [6].

Types Protocols

Inquiry A ^ B: request X

B ^ A: answer (X)

A R - ficpntQ

X - questions

Passing A ^ B: tell X

A R - ^itTf^ntQ X - message

Negotiating

(UA-> B.CtellX

(2) B A: If ValueB(X) OK,

Tell 'acceptB" else Tell X'

(3) C A: If ValueC(X) OK,

Tell 'acceptC" else Tell X"

(4) A B, C: If acceptB and acIf acceptB and X*', X=X'\ go to (I)

If acceptC and X", X=X', goto(l)

If X' andX'\X=(X',X'"), goto(l)

A,B,C - agents

X,X\ X" - alternatives Announcing

A B,C,D: tell X

A.B,C,D - agents

X - message

Approving (1) A ^ B: request X

(2) B A: If ValueB(X) OK,

tell 'approveB' else X'

(3) A ^ B: If approveB, end.

If X=X" goto(l)

A,B - agents

X,X" - alternatives, where X' is lacking approval

In order to improve performance, the protocol can trigger and initiate necessary and

timely interaction tasks under coordination

logic. In order to explain and illustrate an E- work solution with task administration protocol (TAP) it is important to clarify the concept

of agent. An agent is a 'program* (autono- mous entity) that represents a group of parties

[6]. Parties may include 'resources', e.g. humans, machines and computer systems. The

role of the agents is to cooperate with each

other through protocols to perform specific

tasks and to achieve the system's goal. Along

the lines of this definition, the active tasks administration protocols (TAP) control rules that tenable effective collaboration among agents

and tasks. Protocols provide the rules for

agents to procure information [6]. A typical

scenario of material procurement, illustrated in Figure 2, may involve a contractor and several

steel suppliers. The contractor inquires two

rebar supplier agents (ai and a^) about quantity

take-off of some rebar material. The two supplier agents respond the request. Based on the responses, ao does some checking and sends

the decisions and approvals to the three supplier agents.

Message Types:

[ 1 ] Inquiry

[2] Tell

[3] Internal Decision Process

[4] Broadcast

[5] Approve

Figure 2. Task administration protocol applied to construction materials management automation.

2.2. Multi-agent Model

Agents are defined as a hardware or soft- ware system that can act, interact and respond

according to given goals [14]. For the particular case of construction materials management networks, the agents need to feature

autonomy and flexibility. Software agents developed specifically for the supply chain may

support the ability to closely integrate buyer

and seller processes as well as to provide sufficient flexibility to keep up with changes to supply chain operations [12]. As a requirement to be autonomous, the agents need to have [6]: database and protocols, sufficient capability for anticipating their long-term viability domain, measurable output (processing

67
time, waiting time, etc.), ability to learn and a sensorimotor apparatus (protocols, databases

and human observation can serve to this purpose). A similar case takes place in construction processes, where the final decision on

material quantities is not final until the material suppliers (for the case of steel reinforcement rebars) provide the estimation based on

the structural design drawings. Therefore the

system of materials procurement has to be ini- tiated without the benefit of planning, which is what happens in most of the cases. An archi- tecture consisting of four agents will be used

to illustrate an E-work model for the construction materials management automation on the

Internet. Agents to be considered are a fore- caster agent, a recorder agent, a planner agent

and a reviser agent. The flow diagram for

these interactions is shown in Figure 3.

Agents

[aj Forecaster Agent

[aj Recorder Agent

[aJ Planner Agent

[a+] Reviser Agent

lenge consists of managing the distributed

material and information flow. The construction process, due to its diverse and almost unlimited source of ideas and methods for materials procurement, handling and procurement,

qualifies to be treated as a flexible process.

2.3. Parallelism Model

An E-work model of parallelism to ensure

effectiveness in the Internet deployment of a construction material management automation

system must have into account that there are several e-activities present. It is possible to obtain improvements in time and accuracy

through the utilization of a client-server model

and the assignment of tasks to the available re- sources, i.e. material suppliers, designers, subcontractors or delivery entities. There will be

a coordination agent that allows the parallel

execution of tasks, thus having earlier progress

or even completion dates. Parallel processing

in supply chains has an explicit focus on col- laborative problem solving between multiple

processors. This problem solving is usually

focused more on numerical processing than

intelligent reasoning [12]. Figure 4 displays

the structure of a parallel tasking, using master-slave architecture.

Master

Slaves Processor 0

Decision Boundaiy

All agents involved e xcept 84

Figure 3. Multi-agent model applied to construction materials management

However, an E-work model of multi-agents can help predict the requirements of materials

using knowledge of the supplier past estimations for standard or special cases, in addition

to recent observations of other projects in progress or completed. These predicted job re- quirements can then be used for better planning [14]. In an effort to find the solution to a problem in a flexible manufacturing system,

Esfarjani and Nof [4] found out that the chalI I - I I - I I _j

I I

Prcicessor 1 Processor 2 Processor 3 Processor p

Figure 4. Master-Slave architecture in parallel

multitasking.

In order to communicate and cooperate in the Internet, certain procedures must be established to coordinate the interaction of participants in order to effectively accomplish the

tasks [16]. In this case there are various types

of inquiry, approval or negotiation protocols

that are presently used.

68
There is a need for a coordination protocol

that will guide and support the interaction of

participants in order to successfully perform

the necessary tasks. The ultimate goal of the

coordination-related research is to find the

most effective coordination scheme that maximizes collaboration effectiveness among

participants. The effectiveness in the collaboration among material suppliers, subcontractors, designers and contractors will have a dramatic impact in the overall success of the

construction project.

The interaction diagram of a typical

workflow for construction materials management shows the different interactions among

resources. Figure 5 displays the interaction

diagram for a typical supply chain of materials.

Stalieholder RCC Suppliers Des^ners Procurement Jobsite

Msterial mfo

Material

info

Shop

Quantity

^quoted

Q

Negotiatior

iQ Decision on

purclriase Anruounc^ Confum

Q

Procurement

option

Structural

re^/ision

Quantl^/ k Inquiry

appro^/ed app processing

Announce

Initiate Unload

Info fbi; Material

flowFigure 5. Interaction diagram for a typical supply chain of construction materials.

Interaction diagrams are tools that characterize the elements in the supply chain of in- formation and materials. These tools may be

utilized when deploying an e-business solution

for the integration of the supply chain. For in- stance, any request by the contractor of information regarding quantity take-off from shop

drawings will flow from the material supplier

to the designer for revision and approval. Subsequently, the designer will send the approved

drawings back to the supplier for delivery

through a web operation center. This e- business approach is aiming to integrate the

process of design, estimation, revision and

procurement of materials from the early stages

of the construction project. The interaction

diagram also indicates the decision nodes in the overall process, i.e. inquiry processing, negotiation, decision on purchase and procurement option.

The research developed by the PRISM Lab

at Purdue University [14] uses parallel computing to simulate autonomous agents. This

tool, called Teamwork Integration Evaluation

(TIE), focuses on measuring the coordination

performance of all participants [1]. Figure 6

shows an adaptation of the original

TIE/Protocol, with outputs relevant to the new

application in the construction material auto- mation process.

Simulation Model

Team

Paiamieters

Task Given Component^

Librarr Simulator

Platfomi

^ ^

Oi^anization Workflow

CollaboratiDn/ Communication —Protocols

Parallel Computer

Performance

Supplier Select. Design revised

Procurement Task 0 Ai/ailable ^ Processing ^ Wailm?

Figure 6. TIE/Protocol for construction material automation (adapted from Anussomnitisam and Nof [1]).

2.4. Conflict Resolution Model

The inherent nature of construction processes

plagued with conflicts, create an area for improvement. An E-work model of conflict

resolution will be of great benefit for the

automation of construction materials management systems deployed on the Internet. A collaborative method for facility design is needed in order to increase design quality and

shorten the design process development [14].

The process of design, estimation, revision and

procurement of construction materials displays

lots of conflict situations, which result from

the interaction of cooperating designers, sup69
pliers, subcontractors or contractors. The new

method of conflict resolution, MCR, developed by Lara [9] and Lara et al. [10] comprises

rational execution of pre-ordered conflict

resolution approaches: direct negotiation, third

party mediation, incorporation of additional

parties, persuasion and arbitration or settle- ment of claims.

The main cost-differentiating factors influ- encing choices in conflict resolution architec- tures are: intensity of processing (measured by

task complexity), intensity of communication

(measured by quantity of exchanged communication) and extent of communication (measured by the level of networking in the process)

[5]. This study points out that previous analyses in the area have failed to consider management costs, which can be dissimilar across

different IT architectures. As it can be seen in Figure 7, the costs for conflict resolution in- crease as stages escalate from a direct negotiation to arbitration.

Cost Progression

Stage 1 : Direct negotiation

Stage 2: Third party mediation

Stage 3: Incorporation of additional

parties

Stage 4: Persuasion

Stage 5: Arbitration

Figure 7. Cost of conflict resolution stipulated

in MCR [9].

This multi-approach method facilitates computer-supported conflict resolution. Its per- formance is improved through the inclusion of

principles for prevention of conflict perpetuation. Along the same line of logic, the implementation of computer-based learning in- creases the usefulness of the method. As

expected, the integration of conflict detection

and resolution results in an increased effectiveness of the facility design process. The facility design language (FDL) provides a uniform support framework for communication

among facility designers in a distributed environment, thus allowing distributed users to develop, evaluate, reconcile and modify CAD

system models of the facility. This language

fits the needs of the construction process due

to its strong dependency on CAD drawings for

information exchange and quantity take-off re- vision.

Figure 8 shows the arbitration steps to be

included in the construction material process

in order to incorporate prevention, therefore

the system will be continuously providing

feedback to the parties in order to learn from

previous experiences.

Figure 8. Sequence of steps in the prevention

stage.

2.5. Model of Next Generation of ERP Systems

An E-work model that incorporates design

considerations is desirable for the successful

practice of construction materials management

automation. As indicated by Nof and Anussomnitisam [15], the key for the successful

implementation of ERP systems is to be able to anticipate the problems.

For the particular case of construction materials management, some considerations need to be addressed in order to fit the purposes of the

new generations of ERP systems. Firstly,

when material suppliers are required to pro- vide a take-off of a structural drawing, the design process should be able to detect, synthesize and prioritize the problems that might

occur with the interacting participants. Secondly, the design should be able to provide the

grounds for the protocols to be used and what

and when to communicate. Priority schedules

for the different participants of the construction process (contractor, subcontractor, supplier and designer) must be kept active. Third,

the independent entities should be able to par70
ticipate in the design process. This is an ambitious goal, but this way coordination with

other agents will be possible, therefore problems can be anticipated and dealt with in a timely manner. Finally, the new ERP system

will recognize conflicting intentions among

distributed entities. If there is a pattern of

miscalculations by a designer that is being re- jected by the materials supplier, the ERP sys- tem should be able to trigger an action (agent) on the contractor, allowing the system to fore- see an upcoming conflict therefore evaluate

the design. A similar case may be encountered

the other way around. If the material supplier

is not providing an accurate take-off of materials, the ERP system triggers an action framed

by an active protocol, anticipating the conflict

and informing the supplier about the possible

solution to the inconvenience. Figure 9 shows

the concept of the next generation of ERP

systems.

Supplier Designer

Internet

Decision support systems A (DSS) .

Multi-Agent

System

Workflow

4 +

Task&

Activity, databases

CoordmatiQn

^protocols

Modeling

Tools

Entity

Interface

Figure 9. Next generation of ERP systems

[15].

The communication infrastructure of parties

involved in an integrated ERP system for the

construction industry will depend on models

such as the STEP, EDI or lAI/IFC. A subset

of these models, SUMMIT, can be used to support the integration of supply chain management applications [7]. This approach developed a framework to automate the tendering, ordering, delivery, invoicing and payment

processes of house systems, equipment and

services in their supply chain, and where

members have different backgrounds regarding

information and communication technologies.

3. CONCLUSIONS

The supply chain of materials in construction

processes remains a critical competency for

the success of the construction business. Even

though fast developments in communication

infrastructure through models of EDI, STEP or lAI/IFC, the management and control of entities in the supply chain of materials are very

often not carried out automatically. With the

incursion of the Internet and its e-business capabilities, new approaches for the automation

of supply chains of materials have been developed. However, the construction industry has

yet to utilize intelligent tools for the resolution

of common conflicts in the planning, design,

procurement and delivery of materials.

E-work is a suitable concept for this en- deavor because it comprises principles that allow cooperation and collaboration in the or- ganization. E-work has provided benefits to the exchange of information and collaboration

among autonomous systems in manufacturing

organizations. The nature of construction pro- cesses in terms of occurrence of conflicts,

autonomy of interacting systems, distributed

organization and sequencing of tasks in the

supply chain provides areas for applicability of

E-work models. The research described in this paper builds upon recent work and publications on E-work models applied to systems of

manufacturing organizations.

Autonomous agents can help predict the re- quirements of materials using knowledge of

the supplier past estimations for standard or

special cases, in addition to recent observations of other projects in progress or completed.

The sequencing of tasks for the exchange of

information prior the procurement and delivery

stages can be achieved via task administration

protocols, whose defined steps convene more

complex intentions than single communication

acts.

71
Interaction diagrams provide information on

different interactions among resources, allowing stakeholders to consider parallel processing for an effective automation of supply chain

processes focusing on characterization of entities and decision nodes.

Finally, the process of design, estimation,

revision and procurement of construction materials displays conflict situations that can be

resolved with the implementation of multiapproach methods facilitated by computersupported conflict resolution.

4. REFERENCES

[1] Anussomnitisam, P. and Nof, S.: "Evaluator TIE/Protocol, a teamwork integration

for coordination protocols". Proceedings

of ICPR-2000, Bangkok, Thailand,

August 2-4, 2000.

[2] Bichler, M. and Segev, A.: "Methodologies

for the design of negotiation protocols on

e-markets". Journal of Computer Net- works, 37: pp. 137-152, 2001.

[3] Castro-Lacouture, D. and Skibniewski, M.:

"Development of an e-business solution

for the integration of steel reinforcement

supply chain in construction projects".

Proceedings of the First International Conference on Construction in the 21st Century (CITC2002), Miami, Florida, USA:

pp. 197-204, 2002.

[4] Esfarjani, K., and Nof, S.: "Client-server

model of integrated production facilities". International Journal of Production Research, 36(12): pp. 3295-3321, 1998.

[5] Francalanci, C, and Piuri, V.: "Designing

information technology architectures: a

cost-oriented technology". Journal of In- formation Technology, 14: pp. 181-192,

1999.

[6] Huang, C, and Nof, S.: "Formation of

autonomous agent networks for manufacturing systems". International Journal of

Production Research, 38(3): pp. 607-624,

2000.

[7] Jardim-Gongalves, R., Tavares, R., Grilo,

A., and Steiger-Gar^ao, A.: "A framework

for integration of supply chain management applications based on the lAI/IFC

model". Journal of Automation and Robotics in Construction, Vol 17: pp. 745-

750, 2000.

[8] Lancioni, R., Smith, M., and Oliva, T.: "The role of the Internet in supply chain

management". Industrial Marketing Management, 29: pp. 45-56, 2000.

[9] Lara, M.: "Conflict resolution in collaborative facility design", Ph.D Dissertation,

School of Industrial Engineering, Purdue

University, 1999.

[10] Lara, M., Witzerman, J., and Nof, S.: "Facility description language for inte- grating distributed design". International

Journal of Production Research, 38(11):

pp. 2471-2488, 2000.

[11] Lin, Y., and Tsemg, H.: "A model of supply chain management for construction

using information technology", 18th Inter- national Symposium on Automation and

Robotics in Construction, Krakow, Poland,

pp.141-146, 2001.

[12] Nissen, M.: "Supply chain process and

agent design for e-commerce". Proceedings of the 33rd Hawaii International

Conference on System Sciences: pp. 1-9,

2000.

[13] Nof, S.: "Intelligent collaborative agents",

Research Memorandum, No. 99-8, March

1999, School of Industrial Engineering,

Purdue University, 1999.

[14] Nof, S.: "Models of e-Work", Proceedings of the IFAC symposium on Manufacturing, Modeling, Management and

Control, Rio, Greece, pp. 521-526, 2000.

[15] Nof, S., and Anussomnitisam, P.: "E- Work: The challenge of the next generation ERP systems". Production Planning

and Control, 2002.

[16] Nof, S.Y., and Ceroni, J.: "E-Work models and systems: Modeling manufacturing

and service in the Intemet Era", Elsevier

(Forthcoming).

72
Capitalizing on Early Project Opportunities to Improve Facility Life-Cycle Performance

by

Calvin Kam\ Martin Fischer", Reijo Hanninen\ Seppo Lehto'*, Jarmo Laitinen^

ABSTRACT: This paper presents the findings from the design and construction of

the Helsinki University of Technology Auditorium Hall 600 (HUT-600) in Finland.

Running simultaneously with the construction project, an international research

partnership extensively documented and analyzed the use of product modeling and

interoperability standards for information exchange. The project team improved

design cycle times and minimized data re-entry through an array of design,

visuahzation, simulation, and analysis tools. Building on the resulting efficiency

and time-savings during the early conceptual phase, the project team conducted a

variety of in-depth life-cycle studies and alternative comparisons on thermal

performance, operation costs, energy consumption, and environmental impact.

Such unconventional practices empowered the building owners to better align the

long-term facility values with their strategic plans.

REWORDS: Life-Cycle Analysis, Pilot Project, Product Model

' Graduate Research Student, Civil & Environmental Engineering, Stanford University, Stanford, CA.

94305-4020, U.S.A. <ckam@stanford.edu>

" Associate Professor, Civil & Environmental Engineering and (by courtesy) Computer Science,

Director of the Center for Integrated Facility Engineering, Stanford University, Stanford, CA. 94305-

4020, U.S.A. <fischer@stanford.edu>

^ General Manager, Olof Granlund Oy, Helsinki, Finland <reijo.hanninen@granlund.fi>

Senate Properties. Helsinki, Finland <seppo.lehto@senaatti.coni>

^ Ph.D, Customer Solutions, SoUbri Inc., Helsinki, Finland <jarmo.laitinen@solibri.com>

1.0 INTRODUCTION In autumn 2000, the Helsinki University of

Technology requested its property owner,

Senate Properties of Finland, to build a new

multipurpose auditorium that would be capable

of accommodating 600 people. Running on a

fast-track design and construction schedule.

Senate Properties assembled a team of

designers, consultants, contractors, and

researchers early during the conceptual

planning phase. This partnership received

financial supports from the Finnish National

Technology Agency (TEKES), which

sponsored the testing of state-of-the-art technologies and data standards in HUT-600.

Since HUT-600 is the first institutional application of the Industry Foundation Classes

(IFC) interoperability standards, it is also a

construction pilot.

The design and construction of the Helsinki

University of Technology Auditorium Hall 600

(HUT-600) adhered to the Level of Influence on Project Costs concept (Paulson 1976) that making a decision during the early project

phase has a relatively high impact and low

cost. This paper explains the Product Model

and 4'*' Dimensional (PM4D) Approaches and

PM4D Processes that were developed in the

HUT-600 project. We document the life-cycle

studies made during the early schematic design

phase of HUT-600, highlight their relationships with PM4D Approaches and

Processes, and analyze their implications on

the long-term performance of the capital

facility.

73
2.0 THE PM4D APPROACHES

The HUT-600 project team followed the

PM4D Approaches in which they relied on

product modeling and interoperability standard

to eliminate the inefficiency and risks of data

re-entry in conventional practices. The

approaches aimed at leveraging upon state-of- the-art analytical and visualization tools to optimize the design, construction, and

operation of the proposed facility during early

project phases (Kam et al 2002).

The approaches recognized the importance of

having cross-disciplinary expertise to improve

design and construction integration. With the

goal of improving the quality of design and

construction services, the approaches called for

utilizing intelligent object-oriented product

models and the IFC interoperability standard

that supported data sharing. Furthermore, the

approaches adopted various visualization tools and analysis tools to additional life-cycle

performance data to support the decisionmaking processes.

3.0 THE PM4D PROCESSES

The PM4D Processes explain the software

applications, data standards, and information

flow that took place in HUT-600. During the

early schematic phase, the architects and

mechanical engineers designed with objectoriented modeling software such as Graphisoft's ArchiCAD'^ and Progman Oy's

Magicad'. IFC release 1.5.1 interoperability

standard reduced the needs to re-enter geometric data, thermal values, and material

properties (Kam et al 2002). Efficient model

and data sharing during the schematic design

phase allowed the building-systems consultants

to simulate various cooling and heating

requirements based on the architectural

product model. These thermal values were

directly imported to the Heating, Ventilating,

and Air-Conditioning (HVAC) design

application, where the mechanical consultants

directed the distribution path. The software

* URL: http://www.graphisoft.com

' URL: http://www.progman.fi/english/e_index.htm

then automatically sized and balanced the

mechanical components. The object-oriented

HVAC application then exported the geometry

of ducts and air handling units for the

architects to incorporate into the architectural

model and generated a bill of materials for the

general contractor.

Synthesizing the readily available bill of

materials from the mechanical consultants and

the three-dimensional geometry from the

architects, the general contractor for HUT-600

utilized an automated cost estimating and value

engineering system, again object-oriented and

IFC-compliant, to match design components

with the contractor's database for cost estimation, scheduling, and resource leveling.

Compared to a conventional approach, this relatively seamless data exchange and the

related automated tools tremendously

expedited design time and improved the

quality of interdisciplinary collaboration (Kam

et al 2002). As a result, the project team

quickly generated three design and two

building system alternatives and was ready to take advantage of the time savings to perform

further value-added work.

4.0 LIFE-CYCLE ANALYSES

The PM4D Approaches and PM4D Processes

called for an enhancement of the facility

performance over its total life span. Hence,

HUT-600" s project team conducted a series of

life-cycle analysis to evaluate the thermal

performance, cost implications, and

environmental impacts of project alternatives.

In the following subsections, we explain how

the project team evaluated two air-conditioning

system alternatives—mixed cooling versus displaced cooling systems. In mixed cooling,

the system supplies high velocity cold air from

the ceiling. It is simpler in design and cheaper

in cost when compared to a displaced cooling

system, which slowly cools the space from the

floor and displaces the warm air up to the

exhaust in the ceiling.

74
4.1 Thermal Performance

The mechanical engineers utilized Olof

Granlund Oy's^ RIUSKA" for thermal

simulations and AEA Technology's CFX'° to conduct computational fluid dynamics (CFD)

analyses. Since the auditorium space was a

critical room with heat emission from 600

users and more than 200 light fixtures,

RIUSKA's predictions and CFX's analyses

enabled the engineers to quantitatively

compare the profiles of temperature and air velocity stratification between the mixed and

the displaced cooling schemes.

RIUSKA accounted for the dynamic behavior

of thermal masses in response to the changing

exterior temperamres through an hourly

increment over a 12-month period. Thus,

engineers could combine different spaces and

building systems to test various insulation and

construction assembly options. Once the

indoor air temperature target was specified, the

program took a few minutes to analyze the

thermal loads from the occupancy, the

occupants" schedule, the equipment, and the

exterior temperature conditions against the

different insulation schemes, window

transmittance, and louver systems.

Taking RIUSKA's analysis results as its target

range and boundary conditions, CFX took

about 10 hours to iteratively solve for the finite numeric values of air temperature and supply

air velocity across the sectional profiles of the

auditorium space. The CFX results illustrated that in spite of a supply of lower air temperature of 17 degree Celsius, the mixed

cooling system was not as efficient as the

displaced cooling system (required supply air temperature of 19 degree Celsius) in the

occupants' zone—the area that mattered most. Hence, the engineers learned from numerical

values and vivid graphical profiles (see Figure

I) that the mixed system had to supply cooler

air at higher velocity in order to balance the

URL: http://www.granlund.fi/English/runko.htm

^ URL: http://www.eren.doe.gov/buildings/tools_

directory/software/riuska.htm

URL: http://www.software.aeat.coni/cfx

warmer air around the lighting fixtures in the

ceiling level.

4.2 Cost Analysis

The HUT-600 project consultants employed

Olof Granlund Oy's BSLCC software to project the operation and maintenance costs of

project alternatives throughout the facility's

expected life-span. The consultants and the

construction managers shared their respective

knowledge from past projects, facility

management data, and the manufacturers'

catalogues to estimate energy consumption

costs, maintenance costs, and immediate

investment costs (see Figure 2), which all together provided reliable quantitative decision

supports for selecting mechanical system,

choosing electrical lighting and maintenance

methods, and qualifying bid packages from air handling unit manufacturers.

In the mixed versus displaced cooling analysis,

HUT-600 consultants assumed the systems had

a 50-year service life span. For both

alternatives, BSLCC read the automatically

generated bill of materials from the objectoriented applications, estimated the cost of

initial investment, and projected operation cost based on energy consumption and system

efficiency. With the analysis tool, the

consultants also accounted for the maintenance

cost, replacement cost, financing cost, as well

as inflation cost. The in-depth comparison

results informed the decision makers that the

equivalent annual cost of the displaced air- conditioning system was 6% higher than that of the mixed air-conditioning system.

4.3 Environmental Impact Analysis

With Olof Granlund Oy's BSLCA software,

the building system consultants conducted

environmental impact assessments to evaluate

the environmental influences of the building

materials and the estimated energy consumed

by the facility. In particular, the consultants

extracted the material properties and quantity

information from the product model of the

alternative designs. They deduced the level of

environmental impacts to air and water and

75
subsequently, they quantified the amount of

pollution emission, global warming,

acidification, etc. in support for material and

system comparison (see Figure 3).

Iteratively, the designers, consultants, and

construction managers evaluated and counter- proposed materials, structural systems, and

building systems among themselves to balance

aesthetics, performance, cost, and

environmental impacts during the project

design phase.

5.0 IMPLICATIONS

Kam et al (2002) reported that in HUT-600 the use of object-oriented product models and

interoperability standard resulted in about 50%

time savings in design documentation, as a

result of object-oriented library, parametric

properties, knowledge reuse, and data sharing.

PM4D Approaches and PM4D Processes expedited the traditional schematic design

services. As a result, the project team shifted

their attention from performing routine jobs to conducting life-cycle analyses. Such analyses

added project values while reducing the risks of cost overrun or dissatisfaction of long-term

performance.

Had the HUT-600 project team not conducted

life-cycle analyses on mixed versus displaced

cooling systems, risk-adverse decision-makers

would probably select the mixed system rather

than the displaced cooling system. Since the

latter system required an expensive under-floor

distribution system, the lack of its performance

evidences and operating cost information

projection would have posted skepticisms to decision makers. While in HUT-600, not only

did PM4D Approaches and analysis tools ensure the early availability of life-cycle

analyses, they also improved the quality of the

decision factors. For instance, the dynamic

thermal behaviors that RIUSKA analyzed for

the thermal performance are usually

approximated or omitted in conventional

design approaches.

HUT-600 consultants noted, and conferred by

the project construction managers, that in the

total spending on a capital facility, 80% of the

total cost is spent on the operation and

maintenance, whereas the remaining 20% goes

to planning, design, and construction. Hence,

it is crucial to capitalize on early project

opportunities to optimize the facility design for

long-term performance.

By March 2001, only three months into the

design phase, the abovementioned analytical

results were available to the owner and the

project team members. Subsequently, the owners evaluated various project alternatives

(e.g., architectural features, mixed versus displaced cooling systems, etc.) based on their

functional performance, projected operating

costs, maintenance costs, and environmental

impacts and chose the most efficient designs

and systems that best met their long term

strategic goals. In the selection of air- conditioning system, the owners were

confident to invest in the more energy

efficient, environment-friendly, slightly more

expensive, and better performance system

the displaced cooling system.

Furthermore, the HUT-600 project team also

explored various visualization tools, such as

virtual reality-EVE", 4D CAD'\ virtual

animations, etc., to foster early and effective

communications among the end-users, owners,

and project team.

While all the HUT-600 project stakeholders

enjoyed the benefits that we documented in

this paper, there were still barriers and wishlist items that could have further improved the

design services and better expedited the data

sharing process. Such wish-list items included

simpler data conversion processes, stronger

interoperability, and better supports for

revision handling (Kam et al 2002).

6.0 CONCLUSION

Shared among the owners, project team, and

research partner of HUT-600 was a committed

belief in capitalizing on early project

URL: http://www.tml.hut.fi/Research/HUTVE

URL: http://www.commonpointinc.com

76
opportunities to make a lasting and positive

effect on the facility over its total life-span.

Leveraging upon the reduced design time and

improved data exchanges, enabled by the

PM4D Approaches and Processes, HUT-600's

project team was able to complete a series of

life-cycle studies within the original design

schedule. Pertinent decision factors and

project alternatives were available during the

early schematic design phase when making a

decision had a relatively high impact and low

cost.

In the nutshell, modem technologies are capable of expediting conventional design

practices and promoting life-cycle approaches.

Project experiences from HUT-600

construction pilot demonstrated that owners

are empowered to choose among

comprehensive life-cycle alternatives and to align the long-term facility values with their strategic plans, whereas project team members

could differentiate themselves from their

competitors with higher efficiency, better

quality, and more effective application of their

expertise.

7.0 REFERENCES

Kam, C. and Fischer, M. (2001). "Experiences

from HUT-600 Auditorium Project."

Presentation at VERA Seminar, Helsinki,

Finland, November 20.

Kam, C; Fischer, M.; Kunz, J.; Hanninen, R.; Lehto, S.; and Laitinen, J. (2002). "PM4D

Final Report" Working Paper, Center for Integrated Facility Engineering, Stanford

University, Stanford, CA, in press.

Paulson, B. (1976). "Designing to Reduce

Construction Costs." Journal of the

Construction Division, ASCE, Vol. 102, No.

C04, Proc. Paper 12600, December, pp. 587-

592.

77
Figure 1. CFX provided CFD cross-sectional profiles of air velocity, which scales from 0.02m/s (blue) to 0.20m/s (red), in the displaced cooling scenario (Left) as well as the mixed cooling scenario (Right).

Figure 2. RIUSKA projected the annual heating and cooling energy consumption for HUT-600.

Level: Property Case 1: Displacement ventilation (supply air from flo Life Cycle Period, 50 Case 2: Mixing ventilation (supply air from ceiling) EMISSIONS TO AIR

Carton Dioxide - C 02 ft Carbon Dioiride - C02 t Sulfur Dioxide - S02 kg

Sulfur Dioxide - S02 B<g Nitrogen Oxide - Nox pg

Nitrogen Oxide - Nox Kg

Others g

Others Carton Monoxide CO " Carbon Monoxide CO

\A3C

\/0C Methane - CI-14 Methane - CH4

Particle

Particle Heavy Metals (all) Heavy Metals (alh

1DDD 20D0 30m 40DD 6000

Figure 3. Charts from an environmental impact analysis showing the weight of emission (units in y- axis brackets) from energy consumption (blue) and the building materials (green) over a 50 year period

in HUT-600.

78
SESSION 2

CONSTRUCTION PROCESS

MODELING AND SIMULATION

79
1

t

I

I

I

i
Dynamic Change Management for Fast-tracking Construction Projects

by

Moonseo Park'

ABSTRACT: Uncertainties make construction dynamic and unstable, mostly by creating non value-adding change iterations among construction processes. Particularly, when a

project is fast-tracked without proper planning, those change iterations can cause the disruption of the construction process. For this reason, to effectively handle fast-tracking

change iterations involved in fast-tracking need to be identified, and the dynamic behavior

of construction resulting from those change iterations must be dealt with in a systematic manner. As an effort to address some of these challenging issues in fast-tracking

construction, this research paper identifies different change iteration cycles involved in fast-tracking construction and observes the characteristics and behavior patterns of change.

All of research findings are incorporated into a cohesive system dynamics model and the model simulation confirms that managerial decisions on change or rework should be made

based on the proper assessment of their tradeoff. In addition, a case study of highway and

bridge construction projects shows the potential of how fast-tracking construction can

benefit fi-om dynamic change management in real world settings.

KEYWORDS: Change, Fast-tracking, Feedback, Rework, Simulation, System Dynamics

1. INTRODUCTION

Shortening time-to-market has been one of the most critical factors to the success of

businesses in many industries. As a result, companies have sought a method that can

ensure a faster product development, most

commonly focusing on product cycle time

reduction through concurrent development.

The construction industry is not an exception.

The increasing preference of project owners and managers to fast-track construction proves

the popularity of concurrent development in construction. In addition, many success stories of fast-tracking have demonstrated that the popularity of this delivery' method is warranted

[Huovila et al.. 1994: Williams, 1995].

However, concurrent construction also has

greater potential to impact the project

development process than the traditional more

serial method [Pena-Mora and Park, 2001].

In the literature, these potential problems are mainly attributed to the increased level of

uncertainty and research efforts on fast- tracking have focused on uncertainty reduction.

However, in dealing with uncertainties, most

of the previous researches have not explicitly

addressed how they impede construction

processes, nor identified the different patterns

of their impact on the project performance.

Closer observations of the design and

construction process indicate that uncertainties make the construction dynamic and unstable,

mostly by creating non value-adding change

iterations among construction processes.

Particularly, when a project is fast-tracked without proper planning, those change

iterations can cause the disruption of the construction process. In addition, people's

preference of change to rework can reinforce the change impact. Since construction has a

physical manifestation, construction rework is normally perceived to have a bigger impact

than change. As a result, construction

managers tend to avoid rework on problematic

tasks by changing the scope of work, in particular under time constraints. However,

' Assistant Professor, Department of Building,

School of Design & Environment, National

University of Singapore, Email:bdgmp@nus.edu.sg

81
construction sequence by triggering

subsequent changes on other tasks, which often

contributes to unanticipated schedule delays

and cost overruns in fast-tracking construction.

For these reasons, to effectively handle fast- tracking change iterations involved in fast- tracking need to be identified, and the dynamic

behavior of construction resulting from those

change iterations must be dealt with in a systematic manner.

2. CONSTRUCTION CHANGES

Non-value adding iterations in construction are mainly associated with construction changes.

Accordingly, reducing wasteful construction

iterations requires effective change

management, which should start with the understanding of different characteristics and

behavior types of construction changes.

2.1 Types of Changes

Normally, construction changes refer to work

state, processes, or methods that deviate from

the original construction plan or specification.

They usually result from work quality, work

conditions or scope changes. Meanwhile,

changes that have been already made (denoted

as Changes as Result in Figure 1) can be the source of subsequent changes in other tasks (denoted as Changes as Source in Figure 1). For example, changes in the design work that have been made by mistake can cause subsequent changes in construction, hi this case, the design changes are a resuh to the

designer, while they can be a need for changes

to the construction crew. In addition, change

can be also seen as an action of making a change (denoted as Change as Behavior in Figure 1). which is further categorized into unintended change and managerial change.

Unintended changes occur without the intervention of managerial actions. The arrows

labeled E, F, and G in Figure 1 illustrate the unintended change process. Meanwhile,

managerial changes are made by managerial

decisions during quality management or

project monitoring and control. As illustrated in Figure 1, once changes occur during

construction {A and 5), changes result in either subsequent changes (Q or rework (D),

depending on managerial decisions.

2.2 Differentiating from Rework

Both change and rework are done in the form

of either 'adding*, 'deleting' or 'replacement

(deleting and adding)*. However, given the same problem, they have different behavior

patterns, since change and rework have

different characteristics, as summarized in Table 1. For example, in Case I on Figure 2, given the problem (a hump on the concrete

surface), rework would be done by deleting the problem, while change would be done by

adding some more concrete. In addition, in Case IV where floor tiling has been finished

with less than the required height, although

both change and rework have the same

behavior pattern (replacement) in solving the problem, the object would be the problem area

in rework, while the previous work would be

the object in change.

2.3 Tradeoffs

In construction, the change option is more

general. Since construction has a physical

manifestation, construction rework is usually

accompanied with the demolition of what have

been already built, which normally has a bigger direct impact on the construction

performance than the change option. By

adopting the change option, it is possible to avoid rework on problematic tasks that may

require more resources. However, as previously discussed, changed tasks can also become a change source that can cause other

subsequent changes, which might have more

impact on the construction performance than

the rework option in certain conditions. For

example, the increased concrete height in Case

I and Case III on Figure 2 may trigger

subsequent changes in succeeding tasks, i.e., reducing the size of ventilation ducts. In

addition, in Case V on Figure 2 where some of

piles have not been correctly positioned, it may

be possible to proceed with the superstructure

without correcting the position of the piles by

changing the position of columns. However,

this change option may necessitate unplanned

cantilever construction in order to keep the

original floor layout, which needs to be

evaluated as compared to re-driving the piles.

Consequently, a decision on the change option

needs to be carefully made based on a good

understanding of how changes evolve to nonvalue adding iterations, which can create

82
unanticipated and indirect side effects of the

decision.

3. DYNAMIC PROJECT MODEL

The dy namic project model to be presented has

been developed taking into consideration

effective change management and operation

level construction policy making. To develop

the model feedback processes involved in fast- tracking construction were identified focusing on how they can trigger non-value adding

iterations in the form of construction changes.

Having identified feedback processes, the generic construction process, which constitutes the skeleton of the project model, was modeled.

3.1 Feedback Processes in Construction

Normally, construction involves feedback

processes represented in the causal loop

diagram on Figure 3-a, 3-b, 3-c, and 3-d. When

tasks and resources are available, first, the upstream work, based on which the available

tasks will be carried out, is reviewed before

commissioning resources for the tasks. During

the review process, problems made in the upstream work can be discovered. Once they

are found, depending on managerial decisions,

workers may request the upstream worker to correct the problematic work. More upstream

hidden changes can cause more requests for the upstream work reprocess, which results in more pending tasks (A) and schedule delays (B)

in the downstream work. Otherwise, workers

construct tasks not having problems in the associated upstream tasks, with given

resources. Once tasks are completed, the construction performance on the tasks is periodically monitored or inspected to see whether or not the target quality is met and the intended functions are achieved. Through this quality management process, a decision on

whether releasing the completed tasks or not can be made.

Unintended changes resulting from low work

quality, bad work conditions or frequent scope

changes can cause managerial changes (Q,

rework (D), or hidden changes (£), depending

on managers' willingness to adopt the change

option and quality management thoroughness.

The more construction is delayed the more

often the change option tends to be adopted (F),

in order to avoid rework, which is normally

perceived to have a bigger impact on the schedule performance. However, such

managerial efforts can create unplanned and/or

indirect side effects. As a result of feedbacks

involved in the processes (F, G, H, /, J), managerial changes can trigger further delays

as well as rework. As diagramed in Figure 3-a,

managerial changes trigger reprocess iterations of tasks that have been already released (refer to the definition of managerial changes in Table 1), while rework delays the construction progress by creating reprocess iterations of

tasks that have not been released.

In addition, delays also may make quality

management efforts less thorough (AT), which

results in more hidden changes (Z). During the downstream review process, hidden changes

released from the upstream work can be

discovered. Once they are found, depending on

managerial decisions, downstream workers

request the upstream worker to correct the hidden changes. As a resuU. more hidden

changes can cause more correction requests

from the downstream (M), which also can

delay the construction progress as a resuU of

subsequent feedback processes {N, I, J)

diagramed in Figure 3-b.

Furthermore, increased willingness to adopt

managerial changes also can increase

subsequent changes in the downstream work

(O), which delays the downstream work

process. Consequently, reprocess requests

from the downstream work are also delayed

(/?), which again impacts the schedule

performance of the activity that has originated

changes (A'^, /, J). Meanwhile, lowered quality

management thoroughness creates more

hidden changes (I). Increased hidden changes

can deteriorate the work quality of the downstream work, which creates more

reprocess iterations of the downstream tasks. This also impacts the upstream schedule

performance through {R, N, I, J). All of these feedback processes can impact the construction

performance, combined with resource

availability, construction policies, and people"

reactions to work conditions and policies.

3.2 Model Description

Based on feedback processes and relationships

among construction variables in the causal loop diagrams on Figure 3. the quantitative

83
representation of the generic construction process has been modeled using system

dynamics modeling techniques. In addition, other supporting model structures for resources, scopes, and quality have been also developed.

Detailed model descriptions are found in Park

(2001).

4. CASE STUDIES

The developed dynamic project model is being

applied to the construction of 27 bridges in order to help effectively manage changes and

prepare a robust construction plan. The

construction is a part of a $400 million

Design/Build/Operate/Transfer project for roadway improvements along State Route 3 from its intersection with State Route 128 in Burlington. MA north to its terminus at the New Hampshire border. The development

process is expected to span 42 months with the

project completion achieved in February, 2004.

The project scope includes widening the 21- mile of the state roadway and the existing 15 underpass bridges, and renovating 12 overpass

bridges. This paper presents a case study of the Treble Cove Road Bridge Construction, one of

bridge renovation projects, demonstrating how

the case project has suffered from changes and

providing construction policies to minimize

change impact on the project performance

including labor policies and schedule buffering.

4.1 Simulating the Actual Performance

The simulated actual duration is 559 working

days. This is 168 days longer than the CPMbased duration of the base case, which is 391

working days. The difference in the completion time is mainly caused by a lot of

non-value adding iterations among design and

construction activities. Actually, the construction team is working to address such

issues that the design development of the Treble Cove Road Bridge project was already

shown significant delay and construction has

not been yet started. Some of these issues are due to the fact that this project was awarded to the contractor before the detailed scope of the project has been established. As a result, changes on the design work were frequently

requested from the owner side during sketch

plan, final plan, and shop drawing submittal,

which resuhed in a lot of design iterations. In

addition, this case project was the first design/build contract for the members of

development team in the owner side, expected

level of coordination among the owner,

designer and constructor has not been met to date and design iterations encountered were

difficult to handle. Based on interviews vAth

the design and construction team, these challenges in the design development were

represented as 'Highly Unreliable' in the

project model and the simulated actual durations for those activities show how much

non-value adding iterations caused by changes

can affect the project progress in a quantitative manner.

4.2 Policy Implications

In order to examine the effectiveness of

different construction policies, simulations were done adapting the actual case with

different scenarios for managerial decisions on

change or rework, labor control, buffering, and some important time variables. As a result of

the simulations, the following policy

implications were obtained (refer to Figure 4 to see the model simulation).

First, a higher managerial change ratio tended

to reduce costs but lengthen the project

duration. However, it is hard to generalize this

result, since the tradeoff of change and rework

is highly dependent on construction system

conditions at the time when a decision is made.

This implies that effective change management

requires an operational level approach rather than a long term policy, and it should be

accompanied with well preparation of

relatively long-term policies such as labor

control policies, schedule buffering and

delivery methods.

In connection with labor policies, flexible labor control was found to be effective for the case project in terms of schedule and cost reduction. In contrast, overtime contributed to

facilitating the project schedule to some extent but its effectiveness is questioned, once

increased project costs are considered.

Overtime applied for the case project lowered

productivity and increased change rate, as workers" fatigue was accumulated. In fact, the effectiveness of labor control policies can vary depending on the nature of a project. However,

84
many success stories of concurrent

construction projects like our case project

confirm the above policy implications,

demonstrating that having flexibility in labor

control contributes to reducing the project

duration and costs by assigning workforce in a timely manner.

In addition, the case project has been simulated

with various buffering scenarios; not having

buffer, having uniform buffer, and having

buffer based on activities* characteristics. The

simulation results showed that applied buffers

contributes to reducing the upstream change

impact and non-value adding iterations. As a

result, the resource idle time and waste were

reduced, which made it possible to more

effectively utilize given workforce. In

particular, buffering based on activities' characteristics turned out to have most

effectively enhanced the schedule and cost performance.

Lastly, the simulations done with different time variable scenarios demonstrate that shortening a required time for labor hiring and

RFI reply contributes to enhancing the project

schedule and cost performance. In particular,

RFI reply time greatly affected the project

performance. Shortening RFI reply time by

half could facilitate the project progress by

12% and reduce the project costs by 10%. In

contrast, when RFI reply time was doubled,

duration and costs were increased by 29% and

24% respectively. These simulation results imply that for this case project, coordination

among the project functions is crucial to the success of the project. Consequently, the decision-making process in design and

construction should be shortened and

information flow among project functions

should be streamlined to assist in reducing the decision-making time.

In conclusion, although the obtained

simulation results can vary depending on

project settings, they well demonstrate how the dynamic project model can contribute to enhancing the project performance in a real world setting by providing effective change

management plans and policy guidelines.

Additionally, the simulation results also imply

that model-based construction policies can be more effective, when combined with other managerial efforts such as reducing a process time and increasing the level of coordination

among project functions.

5. CONCLUSIONS

Construction involves a lot of non value- adding change iterations due to its structural problems, in particular when construction is performed concurrently. This has necessitated

the development of a tool that can effectively

manage construction changes. This paper

addressed the challenging issue by introducing

the concept of dynamic change management to construction planning and management.

Although the research results discussed thus

far need to be further refined and developed,

they demonstrated that the dynamic change

management approach and the developed

project model would help prepare a more

robust construction plan against uncertainties and provide policy guidelines, by taking into consideration the context in which a construction project is being developed.

6. REFERENCES

Fazio, P., Moselhi, O., Theberge, P. and

Revay, S. (1988), Design Impact of

Construction Fast-Track, Construction

Management and Economics, Vol. 6, No. 2, pp 195-208

Ford, D and Sterman, J. (1997), Dynamic

Modeling of Product Development Processes,

Sloan School of Management, Working Paper

3943-97, MIT, Cambridge, MA

Huovila, P., Koskela, L., and Lautanala, M.

(1994), Fast or Concurrent: The Art of

Getting Construction Improved, Proceedings,

pp 143-158, The second workshop on lean

construction, Santiago

Kwak, S. (1995), ^''Policy Analysis ofHanford

Tank Farm Operations with System Dynamics

Approach", Doctoral Thesis, Dept. of Nuclear

Engineering, MIT, Cambridge, MA

Lyneis, J. (1999), "Dynamics of Project

Performance", Course Material, Dept. of Civil and Envr. Eng. at MIT

85
Park, M. (2001), "Dynamic Planning and

Control Methodology for Large-Scale

Concurrent Construction Projects",

Doctoral Thesis, Dept. of Civil

Engineering, MIT, Cambridge, MA

Pena-Mora, F and Park, M. (2001),

"Robust Control of Cost Impact on Fasttracking Building Construction Projects',

Journal of Construction Engineering and

Management, ASCE

Tighe, J (1991), Benefits of Fast Tracking

are a Myth, International Journal of

Project Management, Vol. 9, No. 1, pp

49-51

Williams, G.V. (1995), Fast-Track Pros

and Cons: Considerations for Industrial

Projects, Journal of Management in Engineering, Vol. 11 No 5, pp 24-32,

Sep/Oct. 1995

A

Cliangcis: as Source

(intormalion)

Managerial

Decisions

Rework r

'

External

Scope Change*

.1, E

Changes as

(Slate) G ) j^

"

Figure 1 : Changes as Iteration Trigger

Work

Cottditioiis

Process

Quality

(c

y-- Chimge as Behavior

Achieving

Original Plan

Quality

\ Pertbrmance

Workmanship /

Prodnct

Onalin-

^

* Note

Managerial Change Processes: ( ) ( B ) i C }

Unmterided Change Frovesses: ( £ ] { ( (y)

Table 1: Characteristics of Change and Rework

Ob|«ct

W#rk

'IViggfS-riag AttolheJ- ChaHg«s

Managt'iia!

Clianges

Minimi/,in« Iht' impact uf changes that have ah'eady

octurred by adoptiii» a different method or process than in the orioitial phut and

.spectltcation.

Precedin<> or succeeding

tasks depending onsensitivity

May tri«iger

Rfwork Acliievuig what are

orioinaiiy intended in the plan and specification.

The

problematic

tasks

Same as the scope of probk'inatic

tasks

None

86
Planned

Performance

Change

(Unintended)

Rework

Work Alfcady 1

Floor

FUine

o o oo \

Additt

Change

(Managerial

, A<l<):in J

:| . =n

Figure 2: Behaviors of Change and Rework

Possible

Substquenl

Changes

Ventftrtio

{1>0>lg!(lg ill V«iiti!ati<>

Chan£«i in I Position an't

|

Figure 3a: Change Option Loop

87
Reprocessof

WorkReleased

Figure 3b: Quality Management

Thoroughness Loop

Delav

TotalReprocess

ReprocessRequest

FroiiiDowiistreaiii

HiddenChanges

QualityMaiiageinent

Thoroughness

Figure 3c: Downstream

Reprocess Iteration Loop

WiilingnesstoA clojit

Maiia gerialC liaiige

Reprocessof

WorkReleased

ReprocessRequest

f roittDownstream

r^*,.ii> HiddenChanges

I otalReprocess j \ ^

Quality Management Downsti eani

Thoroughness Quality

Downslieam^

Reprocess

88
stream

ManagerialC;: hange

MaiKigerfeil + Reprocessof

/ +

Reprocess Ciiange

^ « WIllingnesstoAdopt Uninteiuied

ManagerialCliange Clianac

ReprocessofWorkW Reproct>.t$Requc-$t

NotReieased / FroniDo\mstream

lIpstreamDeiay

Work

Pendingduelo

I'pstrcamC'han

PrqjectDela;^

DownstreamDela^'

Delay

DowTistrea

Reproces));

Figure 3d: Feedback Processes in Construction Activities

89

AUTMOD3: A PLANNING TOOL FOR MODULAR BUILDING SYSTEM

by

V.M. Padron, O. Cardenas, R. Diez, M. Abderrahim, C. Balaguer '

ABSTRACT: High quality modular construction is one of the solutions for the fast growing

need for affordable high quality housing in Europe, which can not be solved by conventional

building technology. The software environment for automatic modular construction

AUTM0D3 has been developed, by University Carlos III de Madrid, in the frame of the

European Union project FutureHome. The environment integrated in the Computer Integrated

Construction (CIC) concept is composed by several tools: design, planning and simulation,

which are linked and able to interchange their data. The tools have been integrated in a well

known CAD system and the their work has been tested on an automatic crane for the assembly

of pre-fabricated modules on the construction site. This paper describes the AUTMOD3

planning tool. KEYWORDS: Automatic modular construction, CAD/CAM Integration, CIC, Robotics

1. INTRODUCTION

FutureHome is an European Union funded

research project, which is aimed to the

development of high quality modular

construction and its required Information

Technology infrastructure for the european

construction industry. High quality modular

construction is one the solution for the fast growing need for affordable high quality

housing in Europe, which can not be solved by

conventional building technology. Modular

construction states building process as the

assembly of pre-fabricated modules i.e. initially a modular design of the construction project is obtained, then these modules are produced in a

factory, and finally, they are assembled on the

construction site. The use of pre-fabrication

leads to the following advantages: a) structuring

of the construction process allows to apply

automation, robotics and computer integrated

construction methods (computer-aided design,

planning, control, supervision tools and

automation systems), b) reduction of the health

risks of workers and improving their working

conditions, c) increasing building process

predictability (building process is less affected

by weather conditions, there is a greater control on materials use and the supply chain) and d)

decreasing waste and increasing productivity.

The participants of the project are steel and

building companies, research centres and

universities from Finland, Sweden, Germany,

The Netherlands, United Kingdom and Spain. In the frame of the FutureHome project Carlos III

University of Madrid has developed an

automatic modular construction software

environment, AUTMOD3, realised in the

Computer Integrated Construction concept

[1,13]. The system consists of a design tool [5], a planning tool and a simulation tool. This paper

presents the planner tool, which links the design

tool with the simulation and the execution of the

real assembly employing a robotized crane, it takes as input a finished design and obtains the

sequence in which modules should be produced,

transported and assembled on the site, as well as the robotized crane commands needed for the

automatic assembly of the building. The second

section of this paper presents the main concepts,

the state-of-the-art and the solutions applied for the assembly sequence and the motion planning,

third section shows the work of the planner and

the results of its application on the robotized

crane, finally conclusions are presented.

2. AUTMOD3 PLANNING TOOL

The production sequence and the on-site

modular assembly planning are the objectives of

the AUTMOD3 planning tool. This planner will define the sequence, in which pre-fabricated

modules should be produced, transported and

finally assembled on the construction site. Also,

it will generate programs for the automated

devices involved in the on-site assembly.

' Robotics Lab, Carlos III University of Madrid

CI Butarque 15, 2891 1 Leganes, Madrid (Spain)

e-mail: vmpadron@ing.uc3m.es

91
Assembly planning is a very complex problem

when it is viewed in the context of robots and

other automated devices programming (Figure

1). Assembly planning defines the assembly

operations and their sequence, the fixture

design, the tool selection and the workspace

layout, satisfying a set of technical and

economical requirements. This process produces

the assembly sequence, which is executed by an automated device. In order to do this, it is necessary to plan the grasp points selection and

the grasping of each module, the path planning

from the module initial position to the

destination position and the execution of the

fine motion to insert the module, making a

suitable use of the device sensors during all these operations [14].

Assembly Planning

• Assembly Operations.

• Fixture Design.

• Tool Selection.

• Workspace Layout

r

C^^^^^^^^^^^ Assembly Sequence

^^^^^^^^

r Hish Level Programming

• Grasp Planning.

• Path Planning.

• Fine-Motion Planning.

• Sensory Planning.

i

Automated devices commands

Figure 1 . Assembly planning in the context of

automated devices programming.

A key concept to obtain a successful automated

assembly system is the integration of the

planning process with the design and execution

processes [2]. This concept has been applied in FutureHome. On one hand, specially developed

assembly connectors has been added to the pre- fabricated modules to allow a bigger tolerance

of robotized crane movements and to help the

insertion of modules (Figure 2-a). On the other

hand, the crane has been provided with a

platform carrying electromagnets and an

artificial vision system that allow to locate,

grasp and insert modules in an automatic way

(Figure 2-b). This approach permits the

simplification of the high level programming

allowing to decompose assembly planning in two simpler processes: assembly sequence

planning and motion planning. Assembly

sequence planning searches the order and spatial

direction in which the insertion of each module

should be done. Motion planning defines the

spatial trajectories of the modules during the

assembly and the automated devices commands

needed for their execution.

Figure 2. a) Cones connector, b) platform

artificial vision system.

2.1 Assembly sequence planning

Assembly sequence planning searches the order

and spatial direction in which the insertion of

each module should be done. This sequence

should satisfy the following types of restrictions and criteria: a)geometrical restrictions,

b)physical restrictions, and c)assembly process

related restrictions and criteria. Geometrical

restrictions are those related to the collision

between parts in the assembly process. Physical

restrictions are those related to the unwanted

changes due to gravity, unwanted motion, etc. (these restrictions are also defined as the

assembly stability). The assembly process

92
(available fixtures, tools and workspace) can be

specified to the assembly sequence planer by means of a set of restrictions and criteria. A

criterion, unlike a restriction, is a measure for evaluation. This kind of restrictions and criteria allow the generation of different sequences and

the selection of the most suitable one.

Assembly sequences search is a NP-complete

computational problem [8], that is the time

needed to determine the optimal assembly

sequence grows exponentially with the number

of parts. Due to this complexity most of the

existing planners are interactive systems, which

generate two-handed monotone assembly

sequences in reverse, starting from the more

highly constrained, full assembly state [15].

Some of the most known assembly planners are: DFA 8.0 and DFA/Pro, this is a very useful

advisory system, widely used in the industry,

and Archimedes 4.0 an ACIS enabled automatic

planner with an interactive user interface and a

library of restrictions, that allows assembly

planning in a very pragmatic way. The authors

of the system have reported the assembly

planning of a Hughes Aircraft air-to-air missile

guidance section with 472 parts in 22 minutes

[6].

In the FutureHome project, pre-fabricated

modules are vertically assembled using a cones

connector system (Figure 2-a). This system

allows the auto-centring of the modules during

the insertion, as well as a bigger tolerance in the

precision of the crane movements. The

assembly by means of cones connectors can be

considered a stack assembly (i. e., one in which

all the assembling motions occur in a single

direction, usually up-and-down.). In a

construction work, assembly is always

performed on a structural basis. This leads to

sort assembly sequence inserting first those

modules of bigger "structurality" i.e. modules

that support another modules. This sort according "structurality" is performed on levels,

and inside the same level, it is performed on coordinates. Therefore, if these attributes: "structurality", level and co-ordinates of the

insertion point, are assigned to each module,

then it is only needed to sort the modules

according to these attributes to obtain the

assembly sequence. In addition, a special

attribute, grouping, is provided to take into

account custom planning criteria. This attribute has the biggest priority allowing the division of

a given work in smaller tasks. The sorting time

for a building containing 70 modules using this method is instantaneous. The tool is also

provided with a manual sorting feature to face

unexpected events during the execution process.

2.2 Motion planning

Motion planning defines the spatial trajectories

of the modules during the assembly and the

automated device or robot commands needed

for their execution. Motion planning is defined

as follows: given the initial and the final configuration of the module, find a joining path

that avoids collision with the obstacles. There

are many techniques and algorithms for motion

planning, but they are generally classified in three groups: roadmaps, cells decomposition

and potential fields [10].

Though motion planning has been solved

exactly [3], the obtained algorithms are slow

and complex. The complexity of the motion

planning problem grows exponentially with the

number of degree of freedom (DOF) of the

robot and in a polynomial way with the number

of obstacles. Nevertheless, there are many

problems in practice that are not really complex

and that can be solved exactly or in a approximated way. For robots with four or less DOF of freedom it is possible to solve motion

planning problem, using roadmaps or approximated cells techniques in C-space,

within a few seconds or a few minutes,

depending upon problem complexity [7]. Motion planning for robots with more than four

DOF is an active research area. Some of the

outstanding motion planners in this area are: the

Probabilistic Roadmap Planner (PRM) - this planner generates a roadmap based on random,

but properly selected, collision-free

configuration nodes, and uses this roadmap to find paths [9], SANDROS - a hierarchical,

multi-resolution dynamic-graph search planner

[4] and AMROSE - a multi-agents, artificial potential based system applied to off-line high

level programming of welding applications [12].

93
+ 0,5 m

+ 1 floor + 0,5 mj~

Free plane

Floor 2 Level

Assembly

Plane

Floor 1 Level

Figure 3. Working planes of the AUTMOD3 motion planning tool.

In order to reduce the motion planning

complexity, AUTMOD3 motion planner

basically works on two planes. These planes are

called assembly plane and free plane (Figure 3). Assembly plane is defined at 0,5 m of height

with respect to the current assembled level. Free

plane is defined at 0,5 m of height with respect

to the next (higher) level than the currently

being assembled. Initially, the planner looks for a path free of collisions in the assembly plane

using a variant of the tangent graph algorithm

[4]. If this path does not exist, its distance is very large or the execution time of the algorithm

is large, the planner rises the module to the free plane, carries it directly over the insertion point,

lowers the module and proceeds to the insertion. In addition, the tool is provided with a manual

planning function allowing the modification of

the obtained trajectories or the generation of

other types of paths. This method trades-off

optimality versus complexity producing a simple algorithm.

Grasping operations are automatically

performed by means of the electromagnets and

the artificial vision system installed in the crane

platform, while insertion operations are also

automatically realised using the cones

connectors and the crane platform artificial vision system.

3. APPLICATION TO THE FUTUREHOME

ROBOTIZED CRANE

The AUTMOD3 assembly planning tool is integrated in the AutoCAD environment. It is accessible from the menu bar and communicates

with the design tool through the AutoCAD

database.

Figure 4. a) Calling the AUTMOD3 assembly planner, b) visualising modules assembly properties.

94
Figure 4 (cont.). c) Sorting modules according to their properties, d) visualising the assembly, e) automatic

motion planning: a trajectory for the assembly of the Facade 1 module, f) visualising robotized crane commands.

The planning tool is presented as a single

dialogue box in which the planner can chose the

needed functionality: a) general manipulation of

sequences (creating, destroying and selecting

sequences), b) visualisation and manipulation of

modules assembly properties, d) automatic and

manual sorting according to these properties to obtain an assembly sequence, d) visualising the

assembly, e) motion planning for each module

in the sequence and f) exporting the robotized

cranes commands (see Figure 4). Once the

assembly sequence and the robotized crane commands has been obtained, the assembly can be simulated in the AUTMOD3 simulation tool or the commands can be sent to the robotized crane for their execution. This crane is used to assembly modules in a demonstrator with 1:3 scale modules (see Figure 5). The AUTM0D3

software environment jointly with the robotized crane control system permits the automatic

modular construction of the designed building

in the demonstrator (Figure 6).

4. CONCLUSIONS

The AUTMOD3 planner, dedicated to obtain

the assembly sequence and the motion planning

for the automatic assembly of modules, has been

presented. The key concepts that make

application of this automatic planner feasible are exposed: a great integration of the assembly

planning with the real assembly process has

been achieved, and a suitable strategy of

movement for modular assembly has been

defined. This methodology allows to avoid

algorithm complexity obtaining a fast and

practical procedure. Finally, the automatic

assembly of the modules employing

AUTMOD3 tool and the robotized crane has

been shown.

95
Figure 5. Carlos III University of Madrid

robotized crane.

Figure 6. Robotized crane assembling a module.

5. REFERENCES

[1] Tracey, A., Child, T., Aouad, G., Brandon,

P. and Rezgui Y., "Developing integrated

applications for construction: the OSCON

Approach", / International Conference on Computing and Information technology for

AEC, Smgapore, July, pp. 361-368, 1996.

[2] Boothroyd, G. and Alting, L., "Design for assembly and disassembly". Annals CIRP,

41(2), pp. 625-636, 1992.

[3] Canny, J., The complexity of Robot Motion

planning, MIT press, 1998.

[4] Chen, P.C. and Hwang, Y. K., "SANDROS:

A Dynamic Graph Search Algorithm for motion

planning", IEEE Transactions on Robotics and

Automation, 14(3), pp. 390-403, 1998.

[5] Diez, R., Abderrahim, M., Padron, V.M.,

Celorrio, L., Pastor, J.M. and Balaguer, C. "AUTMOD3: An automatic 3D moularization

system", 17th ISARC, Taipei, (Taiwan), pp. 1033-1038, 2000.

[6] Halperin, D., Latombe, J. C. and Wilson

R.H., "A General Framework for Assembly j Planning: ITie Motion Space Approach."

Algorithmica, 26(3-4), pp. 577-601, 2000.

[7] Gupta, K., "Overview and State of the Art",

Practical Motion Planning in Robotics: Current

Approaches and Future Directions, Eds. Gupta,

K. and del Pobil, P., John Wiley, pp. 1-8, 1998.

[8] Kavraki, L., Latombe, J-C. and Wilson R.H., 1 "On the complexity of assembly partitioning".

Information Processing Letters, 48(5), pp. 229-

235, 1993.

[9] Kavraki, L., Latombe, J.-C, Motwani, R., and Raghavan, P., "Randomized Query

Processing in Robot Path Planning", Journal of

Computer and System Sciences, 57(1), pp. 50-

60, 1998.

[10] Latombe, J. C, Robot Motion Planning,

Kluwer Academic Publishers, 1991.

[11] Liu, Y-H. and Arimoto S., "Computation of

the Tangent Graph of Polygonal Obstacles by

Moving-Line Processing", IEEE Trans, on Rob.

and Automation, 10(6), pp. 823-830, 1994.

[12] Overgaard, L., Larsen, R. and Jacobsen, N.,

"Industrial Applications of the AMROSE

Motion Planner", Practical Motion Planning in Robotics: Current Approaches and Future

Directions, Eds. Gupta, K. and del Pobil, P., John Wiley, pp. 155-183, 1998.

[13] Peiiin, L.F., Balaguer, C, Pastor, J.M.,

Rodriguez, F.J. and Barrientos, A., "Robotized

Spraying of Prefabricated Panels", IEEE

Robotics and Automation Magazine, September,

18-29, 1998.

[14] Wolter, J.D., On the automatic generation

ofplans for mechanical assembly, PhD Thesis,

The University of Michigan, 1988.

[15] Zha, X.F., Lin, S.Y.E. and Fok, S.C.,

"Integrated Intelligent Design and Assembly

Planning: A survey". Int. J. Adv. Manuf.

Technol. 14, pp. 664-685, 1998.

6. ACKNOWLEDGEMENT

This work has been supported by the EU

FutureHome project (BRITE n° ER4-29671)

96
SIMULATION-FACILITATED FACTOR-BASED APPROACH FOR

COST CORRELATION EVALUATION

Wei-Chih Wang

Associate Professor, Department of Civil Engineering

National Chiao Tung University, Hsin-Chu 300, Taiwan;

(886 )3-5712121 ext. 54952; weichili @cc. nctu. edii. tw

ABSTRACT: Project cost becomes increasingly variable if many cost items for a construction project are correlated, and this can increase the uncertainty of

completing a project within a target budget. This work presents a factor-based

computer simulation model for evaluating project costs given correlations among

cost items. Uncertainty in the total cost distribution of an item is transferred to several factor cost distributions according to qualitative estimates of the sensitivity

of each cost item to each factor. Each cost distribution is then decomposed further

into a family of distributions (children; costs given factor conditions), with each

child corresponding to a factor condition. Correlations are retrieved by sampling

from the child distributions with the same-condition for a given iteration of the

simulation.

KEYWORDS: Computer Simulation; Cost Estimating; Risk Factor; Uncertainty

1. INTRODUCTION

Accurately estimating costs is an essential task

in effectively managing construction projects.

Each cost component, and thus project cost, is variable or probabilistic since future events are always uncertain [1]. Project cost becomes

increasingly variable if several cost items are

correlated, increasing the uncertainty of

finishing a project to a target budget. Current

research on correlated costs deals with

theoretical issues concerning in the accuracy of

correlations. For example, Touran and Wiser

used a multivariate normal distribution to generate correlated cost variables for a precise

simulation analysis, assuming that the

correlation coefficients between variables are known [2]. The simulation model of Chau

employed a percentile-based sampling

procedure to influence the probability of

sampling the same quantiles from two

correlated probability density functions,

according to whether the given correlation

coefficient is positive or negative [3]. Finally,

Ranasinghe highlighted some theoretical

requirements, such as the conditions required to achieve a positive definite correlation matrix

and the possibility of using an induced

correlation to define the correlation between

derived variables [4].

This paper presents a simulation-based cost model that considers correlations between cost items [5]. In contrast to existing cost related models in incorporating correlations, the proposed model is designed to meet the following three requirements which are considered practical in a cost management tool,

namely: not requiring excessive input from

management, introducing correlations

indirectly (since this correlation information is not readily available) [2], and recognizing

factor-based correlations when they occur in the field.

2. THE PROPOSED MODEL

2. 1 Breakdown of uncertainty

The proposed model treats the cost of a bill item as a random variable. The cost variable is represented by a total cost distribution (that is, "grandparent" distribution) that combines a base cost with variations resulting from various

97
factors. Variations owing to a particular factor are represented by a cost distribution, a

"parent" distribution. The base cost is assumed

to be deterministic, while the cost distribution

for each factor is assumed to be a zero-mean random variable. Figure 1 schematically

depicts this approach to break down the uncertainty. The base cost is taken to be the

user's best estimate of an item's cost under

expected factor conditions, and is the expected

value of the total cost distribution for the item.

Deviations from the expected value caused by

various factors are introduced through the cost

distributions.

mean = base cost

variations owing to all factors

Total cost distribution

base cost

mean = base cost

variation = 0

cost

*

distribution 1 / (parent 1 ) /

mean = 0

\ variations owing

\ to factor 1

cost

.jf mean = 0

distribution variations owing

2 (parent 2)/j\ to factor 2

;i

lE'iE'iE

Figure 1 . Breakdown of uncertainty

The model captures correlations by drawing

cost samples from related portions of the cost

distributions for cost items that are sensitive to a given factor. For example, the upper part of

Fig. 2 classifies weather conditions into "better

than expected," "normally expected," and

"worse than expected." Based on these three

different weather conditions, the weather

related cost distribution is disaggregated into

three corresponding child distributions

(illustrated in the lower half of Fig. 2), namely,

cost given better than expected weather (that is, better than expected weather child), cost given

normally expected weather (that is, normally

expected weather child), and cost given worse

than expected weather (that is, worse than

expected weather child). Child distributions

may also overlap, as presented in Fig. 2. Restated, the cost of an item may be the same

under both better than expected and normally

expected weather conditions; or the cost with

normally expected weather conditions may be

less than the cost with better than expected

weather.

Cost distribution given weather

conditions

Better than expected weather

Worse than' expected weather

Cost given

better than

expected weather

Cost given worse than expected weather

Child Distributions Figure 2. Decomposition of cost distribution

into costs, given particular factor conditions

A cost model, in which the effect of uncertainty

is broken down by factor, is derived from the

unit cost perspective [5]. Following a series of

derivation [5], Ci the cost of item i, may be

expressed as

J

(1)

where ci(0) is the estimated (or base) cost and

the random variable ci(j), j = 1,..., J, is the cost

(parent) distribution of cost item i due to factor

j. Restated, Equation (1) displays the variations

in the cost of an item, as a base cost and a

series of cost distributions for various factors.

The model assumes that the costs of items are correlated only through the impact of shared

factors. Different factors are assumed to cause independent effects. For example, assume that cost item 1 is sensitive to weather and labor,

and cost item 2 is sensitive to weather and

equipment. Only the weather-related cost

distributions are correlated; the variations

caused by labor and equipment are assumed to be independent. Then, regardless of the type of

the marginal distribution of ci(j), the mean and

variance of the cost of cost item i can be

derived as [5] Mj =mi,o) +m,(i) +mi,2) +... + mi,j) mi(0)

(2)

98
-SD.^o, +SDi^„ +SDr,3, +- + SDf(j) = SDi;„+SD;^,,+... + SDi;j,

(3)

in which Mi and aj are the mean and standard

deviation for C[ (the total cost distribution for

item i), and mi(j) and SDi(j) are the mean and

standard deviation for ci(j), with SDi(O) = 0. The model finds Mj and a{ for cost item i, and

then determines SDi(j). In the example project

presented herein, the three-point estimates of

PERT are used to calculate Mj and Cj.

In constructing a family of child distributions to represent changes in cost due to factor

conditions, one goal is to preserve the mean

and standard deviation of the cost distribution. In other words, the mean and standard

deviation of the combination of the child

distributions for a family should be the same as

the mean and standard deviation of the cost

distribution. Mathematically, this relationship can be represented [5] H

h=l (4) H

^^Uj) =ZPj(h) ^(sdjj(h,] +of(j(h,])

h=l (5)

in which H = number of child distributions;

pj(h)= probability of occurrence for child

distribution h of factor j; and oi|j(h)] and

sdi[j(h)] = mean and standard deviation,

respectively, for child distribution h of factor j for cost item i. Equations (4) and (5) are valid

for any type of statistical distribution. Steiner's

theorem can be directly applied to justify (5)

[6].

The mean of the child distribution for a given

condition is the expected deviation from the mean of the cost distribution when the cost item

is performed under the given condition. Means

of child distributions are expressed through a variable x, the mean placement. The mean of

each child distribution should be confined to a range that maintains the variance of the cost

distribution. When x is equal to the limit, the

child distributions will have zero standard

deviations [5].

To construct a family of child distributions is to

determine their means and standard deviations.

Consider a cost distribution that is sensitive to factor j and has a variance of $4 K. Assume

that the user chooses the categories of better than expected, normally expected, and worse

than expected conditions to describe the

conditions of the factor. Then a family of three

child distributions should be constructed.

Assume that the probabilities of occurrence for

the child distributions are equal; that is, pi = p2 = P3 = 1/3. Thus, based on (4) and (5), the mean and variance, respectively, of the

combined child distributions are —

1 1 1 A o, + — 0-, + — o, = 0

3 3 - 3 (6)

j(sdf +of )+-j(sd; +o;)+-j(sd5 +o^) = 4

(7)

Assume -oi = 03 = x and 02 = 0 so that (6) is

satisfied, and let the child distributions have

equal standard deviations, then (7) can be

rewritten as sd- +(2/3)x- =4

(8)

The limit of the value of x is found by requiring

that the variance of the child distribution be

non-negative. Namely,

sd- =4-(2/3)x^ >0

(9)

Thus, the limit in this case is x ^^/6 = 2.45

(limit = 2.45). In other words, the values of

2.45 and -2.45 are the two extreme means for

Child Distributions 1 and 3, respectively. The

next step is to select the value of x between 0

and 2.45. Instead of specifying the exact value

of X, the proposed model suggests that the

value of X be selected according to the level of

influence of the factor under consideration on

the cost item under consideration. In this example, assume x is set to one-half of the

limit. Then x is equal to 1.27. The properties

of this family of three child distributions are thus Child 1 (pi = 1/3, 01 = -1.27, sdi = 1.71),

Child 2 (p2 = 1/3, 02 = 0, sd2 = 1.71), and

Child 3 (p3 = 1/3, 03 = 1.27, sd3 = 1.71).

2.2 Qualitative estimates

Cost distributions are derived according to subjective information. Project planners are asked to estimate qualitatively the extent to

99
which each factor influences the cost of each

item. For example, a cost item would be

considered to be highly sensitivity to weather if

its cost varies greatly depending on the

weather. This approach of qualitative estimates

is practical because the impact of uncertainties

is easily expressed linguistically. No inherent

restriction is placed on the number of levels of

influence used for each factor. The example

included herein use four levels of influence,

high, medium, low, and no influence.

2.3 Scale system

A scale system is used to transfer the

uncertainty associated with total cost

distribution to the cost distributions based on

qualitative estimates of the uncertainty

sensitivity of cost item i to factor] [5] [7]. That

is, ar=SD;;„+SDi^2,+- + SD5j) = (w,[Qi(,)] + w,[Qi,2, ] + ••• + w J [Qi(j)])xKi

j=i (10)

SDf,j, -Wj[Q,i,]xKi

(11)

where QiQ) is the qualitative estimate of the

sensitivity of cost item i to factor j, and

wj[Qi(j)] is a scale for each level of influence.

For example, the values of the estimates of

high, medium, low, and no sensitivity for factor

j can be represented by wj[High], wj [Medium],

wj[Low], and wj[No], respectively. Kj is an

adjustment constant that ensures that Cjf is

preserved. Since wj[Qi(j)] is fixed for a given

factor], Kj will be different for each cost item.

The value of wj[No] is always zero. The value

of wj[Qi(j)] is higher when Qi(j) represents a higher level of influence. Consequently, a

larger portion of the variance is distributed to a

cost distribution that has a higher sensitivity.

2.4 Sensitivity of project cost to uncertainty

When several cost items for a project are

sensitive to particular factors, these factors are

likely to dominate the cost performance of the

project. Knowledge of factor-sensitivities gives

management a better idea of what factors to

control. For instance, management should

focus on carefully scheduling weather-sensitive

tasks and ensuring adequate equipment is available if weather and equipment

performance exert the biggest influence on

project cost. Controlling the factors that influence performance improves performance more than modifying or changing work

methods. This study measures the uncertainty

sensitivity of each cost item to a given factor

based on its standard deviation divided by its mean. A project in which a certain factor has a high standard deviation is considered highly

sensitive to that factor (since the mean of

project cost is equal for each factor), and

consequently project cost is more likely to be

affected by a change in that factor.

3. COMPUTER IMPLEMENTATION

In the model, when cost distributions are

sensitive to the same factor, a sample cost is independently drawn from a particular child

distribution (given a specified probability of

occurrence) for each cost distribution. For

example, if better than expected, normally

expected, and worse than expected weather are equally likely to occur, then one-third of a predefined number simulation iterations will

have cost samples that are simultaneously and

independently drawn from the better than

expected weather child distributions; one-third

will have normally expected weather child

distributions; and one-third will have worse

than expected weather child distributions. A

simulation language, STROBOSCOPE [8], is used to execute the simulation-relevant

procedure described in the model. This

procedure was implemented on a 586 PC with

64 MB under a 32-bit Windows environment

(namely, Windows 98). Making 1,000 analyses

of twenty-four cost categories of the example

project took approximately six minutes, which

is acceptable for research.

4. EXAPME DEMONSTRATION

An example for a building project is used to compare the results obtained using the model

with two analyses that do not consider

correlations, namely: a standard PERT analysis

(PERT) and a Monte-Carlo simulation, carried out using normally distributed costs with the same mean and standard deviation as the

model's total cost distribution (W/O

Correlation Normal). Meanwhile, three

100
different scale systems (Scales 1, 2, and 3) are applied to investigate the effect of the scale

system. This project comprises 20 direct-cost

division items and 4 indirect-cost division items

(that is, insurance, tax, profit, and contingency).

The model requires two types of inputs, the three-point cost estimates for each division item

and the qualitative estimates of the sensitivity

of each division item to various factors. The

analyses considered here involve 1,000

simulation iterations. The scales of Scale 1 are

listed in Table 1

Table 1 . Scales of Scale 1 Scales Fl Wpi[H] =16 Wpj[A]=12 Wp,[L] =8 Wp,[No]=0

F2 Wp2[Yes]

=12 Wp2[No]=0

F3 Wp3[H]=7 Wp3[A]=5 Wp3[L]=3 Wp3[No] =0 F4 Wp4[H]=4 Wp4[A]=3 Wp4[L] =2 Wp4[No]=0

F5 Wp5[H]=3 Wp5[A]=2 Wp5[L]=l Wp5[No]=0

where "H", "A", "L", and "No" represent high,

average, low, and no sensitivity, respectively.

"Yes" or "No" are used to describe the

sensitivity of cost items to F2. Fl - F5 represent owner approval, weather, material delivery,

labor, and equipment, respectively.

Meanwhile, the scales for Scales 2 and 3

(which exaggerate the differences between

high, medium, and low sensitivities) are displayed in Table 2 and Table 3, respectively.

Table 2. Scales of Scale 2

Scales Fl Wp][H]=8 WpJA] =5 Wpi[L]=l Wp,[No]=0

F2 WF2[Yes]=8 Wp2[No]=0

F3 Wp3[H] =8 Wp3[A]=5 Wp3[L] = l Wp3[No] =0 F4 Wp4[H]=8 Wp4[A]=5 Wp4[L]=l Wf4[No]=0

F5 Wp5[H]=8 Wp5[A]=5 Wp5[L]=l w p5 [No] =0

Table 3. Scales of Scale 3

Scales Fl Wp,[H] =

100

Wp|[A] =10 Wpj[L]=l Wp,[No] =0

F2 Wp2[Yes] =

100

Wp2[No]=0

F3 Wp3[H] =

100

Wp3[A]=10 Wp3[L]=l Wp3[No] =0

F4 Wp4[H]^

100

Wp4[A]=10 Wp4[L]=l Wp4[No]=0

F5 Wp5[H] =

100 Wp5[A]=10 Wp5[L]=l Wp5[No]=0

Results: project cost. The project costs obtained from various analyses (PERT, W/O

Correlation Normal, With Correlation Scale 1, Scale 2, and Scale 3) are compared using

several metrics, namely the mean, standard

deviation, minimum and maximum project

costs. Table 4 lists the analytical results, and

yields the following observations: • The mean and standard deviations for

PERT and W/O Correlation Normal are approximately the same because of the

effect of the Central Limit Theorem. • The analytical results with and without

correlation analyses reveal very little difference in mean project cost. Restated,

the correlation affects the variance rather

than the expected cost. • Correlation produces a project cost that may be significantly lower than

expectations (e.g., $117.96 K for Scale 1 versus $132K for W/O Correlation

Normal) or significantly higher than

expected (e.g., $184.25 K for Scale 1 versus $167.49K for W/O Correlation

Normal). The correlation effect thus has

the potential to create an unexpected cost overrun. • The project standard deviations of the

three With Correlation analyses are 153%,

137%, and 149% higher than for the W/O

Correlation Normal analysis for Scales 1, 2, and 3, respectively. For this example

project, the choice of scale systems does

not markedly affect the analytical results,

which fact applies even in the case of

Scale 3 (highlighting the differences

between sensitivities), because the

correlation effect determined by Scale 3 is enhanced only when most activities have

high sensitivities to the same factor or

factors. It was found out that the

correlation effect tends to be dominated

by the lower-sensitivity factor cost

distributions, rather than the highersensitivity ones.

Results: uncertainty sensitivity. Table 5

summarizes the results of uncertainty

sensitivity to Fl, F2, F3, F4, F5, and all factors

of project cost for different scale systems. For

Scales 1 and 2, the project cost is most sensitive

to F4 (labor), followed by Fl, F5, F3, and F2.

This information tells management that controlling the quality and availability of labor

deserves special attention Meanwhile, in Scale

101
3, which increases the difference between high,

medium, and low sensitivities, Fl becomes the

most sensitive factor rather than F4. Notably,

the PERT and W/O Correlation Normal models

are unable to provide this type of sensitivity

information.

Table 4. Comparisons of W/O correlation and

the mode analyses

Project

W/O

Corr.

Proposed

model

Cost ^ PERT Normal Scale 1 Scale 2 Scale 3 Mean 150 b 149.97 150.06 149.69 150.33

Standard

deviation

5.69 5.32 13.46 12.63 13.26

Min. cost N/A 132 117.96 118.65 117.05 Maxi. cost N/A 167.49 184.25 184.09 184.38 The results aie evaluated considering all factors. ^ All data are expressed in thousands (K).

Table 5. Effect of scale systems

Standard deviation Factors Scale 1 Scale 2 Scale 3

1. Owner approval 7.9857''[2]^ 6.8174 [2] 10.8664 [1]

2. Weather 1.5813[5] 1.9488 [5] 1.7313 [5]

3. Material 2.7240[4] 1.9603 [4] 3.8811 [4] delivery

4. Labor skills 8.3092[1] 8.9019 [1] 5.7696 [2]

5. Equipment 6.7841[3] 5.5836 [3] 4.0056 [3] breakdown

All factors 13.46 12.63 13.26

^

[ ] indicates the rank of the sensitivity with respect

to a given factor. ^ All data are expressed in thousands (K).

5. CONCLUSIONS

This work has developed a simulationfacilitated factor-based model that allows

correlation between cost items to be considered

in cost analysis. The model is based upon the two-step breakdown of uncertainty. The

correlation between cost distributions is caused

by their sharing the same factor(s). Correlation

is introduced by sampling from the child

distribution representing a given factor

condition. The use of qualitative estimates to describe the effect of factor-based uncertainty

should make the user more comfortable in providing inputs than other approaches. Future

research directions could include exploring

ways to capture non-Normal cost distributions

and total cost distributions; implementing timedependent and non-time-correlated cost

variables; and applying the proposed model to other practical projects.

6. ACKNOWLEDGEMENTS

The author thanks Professor Laura Demsetz

from the College of San Mateo and Professor

Hojjat Adeli from the Ohio State University for

their valuable assistance. Dr. Julio Martinez is also commended for making STROBOSCOPE

available.

7. REFERRENCES

[1] Adeli, H. and Wu, M., "Regularization

Neural Network For Construction Cost

Estimation", Journal of Construction

Engineering and Management, ASCE, Vol.

124, No. l,pp. 18-24, 1998.

[2] Touran, A. and Wiser, E.D., "Monte Carlo

Technique With Correlated Random

Variables", Journal of Construction

Engineering and Management, ASCE, Vol.

118, No. 2, pp. 258-272, 1992.

[3] Chau, K.W., "Monte Carlo Simulation Of

Construction Costs Using Subjective Data",

Construction Management and Economics,

Vol. 13, pp. 369-383, 1995.

[4] Ranasinghe, M., "Impact Of Correlation

And Induced Correlation On The Estimation Of

Project Cost Of Buildings", Construction

Management and Economics, 18, pp. 395-406,

2000.

[5] Wang, W-C, "Simulation-Facilitated

Model For Assessing Cost Correlations",

Journal of Computer-Aided Civil and

Infrastructure Engineering, Vol. 17:5, pp. 368-

380, 2002.

[6] Levin, R.I. and Rubin, D.S., Statistics for

Management, 5th Edition, Prentice Hall,

Englewood Cliffs, New Jersey, 1991.

[7] Wang, W-C. and Demsetz L. A., "Model

For Evaluating Networks Under Correlated

Uncertainty - NETCOR", Journal of

Construction Engineering and Management,

ASCE, 126(6), pp. 458-466, 2000.

[8] Martinez, J. C, STROBOSCOPE: State and

Resource Based Simulation of Construction

Processes, Ph.D. Dissertation, University of

Michigan, Ann Arbor, Michigan, 1996.

102
CRITERIA OF TAKING DECISIONS AT TECHNICAL OPERATION OF

BUILDINGMACHINERY IN CONDITIONS OF THE CONSTRUCTION PLANT

Alexej Bulgakow*, Alexander Drownikow**, Viktor Perschin**

'^'Technical University Munich, a.bulgakow@gnix.de ** South Russia State Technical University, drovnik@sssu.ru

Abstract: In the article on the basis of similarity functioning the technique of getting and using

the criteria of taking decisions at technical operation control, modernization and replacement

of the elements of building machinery in conditions of the construction plant is considered.

Keywords: similarity, functioning, criteria, technical operation, and modernization.

INTRODUCTION

The issue of quality management of technical operation (at maintenance service, repair, and also modernization, technical state control, solving

problems of refused elements, units replacement,

etc.) of building machinery in conditions of the construction plant remains quite acute, inspite of

positive experience of its solving in stationary conditions. Methods and means of solving the problems

mentioned above available and used in the world

practice are only suitable for conditions of

stationary speciaUzed repair - diagnostic firms and

building industry enterprises. Therefore at practical

solving of the specified problems in conditions of

the construction plant they are guided by the available operational experience and the employees' opportunities. Such kind of methods

(tests and mistakes) at the building machinery

diagnostics, analogues selection instead of the replaced or refused original elements and systems at modernization obviously results in reduction of

operational and technological opportunities of the machinery as a whole. It basically happens because

of the discrepancy of constructive and functional parameters of the compared analogues. Therefore a machine or a unit will be represented as though

another technical system that should be adjusted in accordance with the original one some additional

technical or technological measures (adjustment, a mode change, etc.) are needed.

Engineering methods of taking decisions in the

specified conditions should be based on the system

and, if possible, include typical techniques of

calculations, procedures of taking decisions. As a

result of engineering calculations criteria of the discrepancy allowable, criteria of similarity

compared (initial and received) systems and a way

of preset values achievement of the discrepancy

should be received.

For solving of the specified problems it is possible

to use principles of similarity of system's

functioning representing one of new kinds and

methods of research in the classical theory of

similarity. This theory states that any functional dependence between physical parameters of the researched phenomenon and an object can be also expressed as dependences among the criteria of

similarity made of these parameters. The features of

criteria are the following: informatively, models of

refusals development in the criteria form typical for similar processes of various technological systems;

complex criteria of similarity - independent

parameters. All these features allow to simpUfy

models of development of machinery refusals and

also to use algorithms of evaluation of its reUability, conformity which allow recalculation with their help of the initial or operational

machinery parameters from one conditions to the

others. The procedure of estimation of the elements of the machine, the degree of the adequacy of functional

characteristics and the physical processes carried out at various stages of the physical and moral

obsolescence, and also the order of eUmination of

their possible mismatch runs as following:

• To reveal in and out parameters of the technological process carried out by a system

or a machine;

• To reveal determining parameters of the carried out physical process and the parameters

describing the work capacity and design for the analyzed element;

• To form criteria of similarity of functioning

describing the constructional features and the physical processes carried out for the research element, a subsystem; containing it and a machine as a whole;

• To establish the dependence of criteria of the machine on the dependence of the elements,

subsystems;

• To define the numerical values of similarity

criteria at the initial and the researched

moments of operation (for example, before and

after the replacement of an element with the analogue), and also the accuracy of

103
reproduction of the given technological

process;

• To take decisions according to the specific purpose at the insufficient accuracy of the reproduction of the preset values of the parameters of the technological process by an element on the similarity criteria of

functioning.

dirnensions, the number of criteria of similarity will be equal 3 (the general number of parameters minus

the number of the independent dimensions). These

criteria will be defined by the method of zero dimensions. Let us conventionally take X3, X4, x^, X7 as the key parameters. The determinant made for these parameters from parameters of degrees of

their dimensions, should be different from zero, i.e.:

Let us admit that the "out" physical parameters of

the technological process carried out by the machine, are yi, yi, ... , yn and the "in" specifying

and revolting influences, the physical process and

the constructional features of the element are determined by parameters Xi, X2, ... ,Xn„ and at least one of yj parameters is connected with Xi, i.e.

A =

>"3 ^3 ^3 ^3

K

K

^1 ^7

yiG {y} =f(Xi, X2, ... ,Xn,). (1)

The choice of those or other parameters Xj is defined by a specific task of research of the technical system and by the following taking of

decisions. Let us accidentally admit that the quantity of

parameters Xj is equal to 7 and they are characterized by four units of measurements: time

T, weight M, length L and temperature 0.

According to the theory of similarity and

This term means, that taking parameters are really

independent. Symbols Z^-, A;,T-,77, in the determinant (2) correspond to the exponents at dimensions of weight M, lengths L, time T and

temperatures for the taken parameters X . As the criteria of similarity represent sizes of zero dimension the expression (1) should by written down in the dimensionless way:

\^ X 2 ^

A' 6-^7

X2 ,1,1,

A-j Az- A-7 ,1,1 (3)

where dimensions of the denominators and

numerators should be equal.

Substituting the complexes of expression (3) with

the dimensions of the appropriate parameters x , by known firom the theory of similarity methods

which numerical values are designate accordingly

The criteria of similarity will finally become:

X\

X3

c, X4 Xe Xi

X2

Til a

X3

2 bi Ci di

X4 Xe Xi

X5 a s bi Cs di

X4 Xe Xi

y, fly by Cy

Xt, X4 X6 Xi

Depending on the physical meaning of the received

criteria of parameters included the separate criteria will characterize geometrical similarity of the elements - analogues, others - similarity of physical processes occurring in them. Accordingly the first ones should be used for selection of elements - analogues at their constructive replacement of the refused elements, and others - for correcting of the technological parameters carried out by the machine. Thus it means, that the received criteria of

similarity can be accidentally divided or multipUed

thus forming new criteria of similarity suitable for solving of specific tasks. In particular, it is possible

to form the special criteria for out parameters of

systems' functioning. These criteria include "in" influences and internal parameters of the systems,

the so-called criteria of similarity of elements

functioning, the systems of building machinery.

Generally criteria may have an area of the admitted

values as constructional or the technological

parameters of the element of the machine are given

with the accuracy in certain Umits. Therefore values of criteria i of the element - analogue 7t-^ and

element - original K-q should follow the term:

104
71 :„ -n., (5)

where the set of values K is restricted by bottom

K^Q and upper TT^-q limits.

According to the given technique the concrete examples of taking decisions at technical operation

of the technical systems should be considered.

Thus if the analysis of interchangeability at a choice

of analogue the term is broken, recalculation and

the change of the rating values of the parameters

carried out by the element of the technological process with the purpose of saving the value of the main, determining quaUty criterion of system

functioning or the machine as a whole made or

calculated from the condition of the given

productivity, effort or other parameters is necessary. If quality of functioning is not saved

after that it means that another element of the replaced element is needed. The order of taking

decisions about the interchangeabiUty of the

technical objects was considered by the replacement of the refused pump adjustable on the pressure such as PVE 35 QR-1-21-CVP-JT6 by the domestic analogue.

The pump serves for maintenance of supply of the working element, carrying out of the working

operation in time to = 2^2,5 sec. that corresponds to the oil submission into the cylindrical cavity Qc =

70-80 l/min, and also for the shneck rotation with

frequency n^ = 120 min~' that corresponds to the oil expenditure through hydro motor Qgn, = 55 l/min at pressure P = 12 MPa. The import pump is characterized by the following rating values of

parameters: submission Qn = 106 l/min; working

volume qn = 70 sm^/vol; pressure Pn = 25 MPa;

rotation frequency of the shaft nn = 1450 min '; the maximal pressure of forcing Pnmax = 35 MPa. As a working Uquid oil viscosity Vn = 46 mm'/s.

The criteria of similarity made in accordance with

the offered technique for the given conditions look

like:

= 193,4

Qn = 0,024

TT. = 2_=o,75;

^4 = VJ =39,7

(6)

Apparently from the first and the second criteria dependences, saving of preset values of

technological parameters and at replacement of the pump by its domestic analogue

is possible if at TT- = const the condition is satisfied:

Q Q = const. (7)

with F as the area of the piston.

However, taking into account, that the submission

of oil in the hydro system of the machine to the hydro motor and the cylinder is adjusted and

stabilized by the stream regulators, this condition

basically may not be followed and the estimation of

the interchangeabiUty of the pumps should only be

carried out on conformity of rating values Q and P. At the same time at an estimation of the interchangeabihty of the pumps adjustable by the pressure of the pumps the third criteria is of great

importance as it means, finally, steepness of the

static characteristic of the adjustable pumps, the time and accuracy of regulation.

The carried out analysis on the criteria of the interchangeabiUty of the import pump by the domestic it is allowed to choose this analogue. In

this case as an analogue the domestic adjustable

pump RNA ID 63/320 UHL4 with the following

parameters was taken: Qn.a = 87 l/min; qn.a = 63

smVvol; P„.a = 32 MPa; P^aniax = 40 MPa; n„.a =

1500 min"'. The oil viscosity recommended by the factory manufacturer is = 12 075 mmVs.

According to this recommendation and including

the fourth criterial dependences (6) oil Tp-46 GOST

R 9972-74 was agreed. The value of the criterion 713 = 0,8, is better for the given pump than at the replaced one.

Similarly an example of taking decisions at the analysis of the technical condition of building

machinery should be considered. The choice and

the use of these or those techniques and means of

the technical condition of machinery in terms of the concrete building enterprises depends on the following factors: constructive and repair

complexity of building machinery, their quantity at the construction plant, economic feasibiUty of

appUcation of the techniques and means of

diagnostics, their complexity and availabiUty. Thus

the engineering preparation of the testing process of

the technical state is of great importance including

the determining of "in", internal and tested parameters and also their boundary condition at an

estimation of the work capacity of the machinery;

the grounded choice of kinds and evaluative criteria of the technical conditions and the appropriate to the evaluations recommendations on the regulations

of the further operation the technical service and

repair of the concrete machines.

105
Criteria of similarity of functioning having

informatively according to the processes carried out by the machine or the mechanism obviously may be

the source of information concerning the way how

far the concrete technical condition corresponds

with the efficient or another given condition. And if the number of the discrepancy of the initial and

valid values of the criteria exceeds the preset

limiting value it is possible to conclude about the

disability of the machine.

The advantage of the criteria of similarity is also in the fact that they can be made of any process

parameters, the phenomena connected by the functional dependence. At the control of the technical condition the criteria dependences made

of the structural and diagnostic parameters are also of interest. In this case it is possible to determine

the value of the structural and diagnostic parameter

(which registration is complicated) using accessible techniques and means of registration of the diagnostic parameters be the criteria dependence

without operations of dismantlement and without

breaking the manufacturing process in which the machine is involved.

The control technique of the technical condition of

the element, subsystem of the building machine

consists of the following.

Accepting values of the parameters included into the expression (4) and equal to the values

appropriate to the given condition of the element

the initial values of the criteria of similarity are determined.

In the process the control of technical conditions

having defined (by calculating) the vaUd values of

diagnostic parameters y- and having accepted

constant value criterion i ( TT- = const), according to

the expressions (4) it is possible to find the vaUd

value of structural parameter On comparison

of the parameter value with its boundary (the

greatest X^^ and the least X,^ ) values appropriate

to the given condition of the element it is possible

to judge about the vahd technical condition of the element and the machine as a whole, i.e., if

element j on parameter X,^ is in the efficient condition or on the contrary if

the valid condition does not correspond to the

preset value, i.e. the element is disable.

The presented technique was tested at the evaluation of the technical condition of the hydro

drive. Thus the following parameters of working

capacity were considered: S - a backlash in the

interface of the pair "the piston and the cylinder";

JU - the oil viscosity; Qq - submission of the pump of the constant productivity.

Let us admit that the functional dependence

determining the work of the hydro drive establishes

the connection of time t of the turn of the working

element with pressure difference on the cylinder of

turn AP^ , viscosity JU and the module of oil

elasticity E, the size of the outflow in cylinder

through the backlash S in condensation, diameter

d, length of course H and area F of the piston.

The criteria of similarity of the preset process of

functioning were received, the main of them are:

71, =tQ,S-';

(8)

As measured parameters it is convenient to accept

t and AP^ , and as seeked parameters - S,JU,Qq.

According to the first and third criteria of similarity

of functioning the increase of the turn time can be

generally connected with the appropriate decrease

of the pump submission, decrease the viscosity and

the increase of the backlash of the pressure

difference on the cyUnder.

According to the second criterion the change of the pressure difference on the cylinder (at constant

loading) may appear at the changing of the backlash, the oil viscosity and the submission of the pump.

The strategy of the control of the technical condition on the criteria of similarity can be

different according to the concrete conditions of

operation and construction of the hydro drive but

the essence of the technique remains constant. The

following strategy can be used in this case:

1 . The initial values of the parameters included into the criteria dependences and appropriate to the

preset condition were considered:

t = (5-6), s; Qo = (5,0 -5,0)10-^, mV^

6 = (1,5 -2,0)1 0 \ m;

APe = (4,0-2,5)10^^N•m"^

106
^ = (182- 160), N s m"-,

where the first ones are optimum, and the second

ones - the limiting values of the parameters

satisfying the preset, available and efficient condition of the hydro drive.

2. Values of criteria of similarity paid off:

711 = 86-10'°; 712= 12,75- 10"^ 713=10,95-10"*.

3. The valid values of the time of the turn and the pressure difference were measured:

r, = 8s; APcn = 3•10^N•m~-.

Taking into account the real conditions an

possibility of calculation of these or those parameters in case of their preserving at the level of

initial values of the other parameters was

researched. The calculation of the parameters was

carried out.

Using the third criteria dependence and having

assumed that the value of the backlash in the condensation and the quantity of the pump

submission corresponds with the preset the value of

the oil viscosity change was determined as:

AjU=!jlI£1L-ju , (9)

and its calculating value accepted for the valid one.

The calculating value of the oil viscosity

{jUp = 146, N s m~') is significantly less of

the required one that allows to make a conclusion

about the necessity of its analysis and replacement.

Thus the real submission value is determined at the

real viscosity value, the measured pressure

difference value and the initial value of the backlash. Similarly, the correctness of the assumption of the backlash conformity is checked.

In this case the values are within the limits and

make: the pump submission = 5,4 - 10"*, m\ s"'; the backlash in condensation 5r = 1,7 - 10'"\ m. It accounts for the working condition of the pump and

the cylinder, and the condition of the hydro drive is disable according to "the oil viscosity" parameter.

The presence of the functional dependences in the form of the criteria of similarity of conditions after measuring of the true values of the diagnostic

parameters of the elements allows to calculate the

real values of their structural or some other

diagnostic parameters and as a result to determine

the technical condition of the tested element, the system or the machine, the unit as a whole. And this in its turn helps to form the strategy of their further operation (adjustment, repair; replacement of

defective elements) without equipment downtimes

necessary for these purposes earlier and without any

dismantlement works.

Nowadays the caring out of the offered technique of

testing of the technical conditions is quite feasible by the experts - mechanics of the building

organizations.

The similar procedures of taking decisions can also be carried out at modernization of the building

machinery.

It is necessary to note, that there are some ways of

getting of the criteria of similarity on the basis of

the preset nomenclature of the parameters

characterizing the physical essence of the researched process. However the most effective is the way allowing to use the computer facilities. For

this purpose some simple computer programmers

are developed by the authors. The received criteria of taking of the decisions at the technical operation

are typical and universal for use at the various

stages of the "Ufe cycle" of the certain class of the building machinery.

CONCLUSION

Criteria of similarity of functioning having

informatively according to the processes carried out by the machine or the mechanism obviously may be

the source of information concerning the way how

far the concrete technical condition corresponds

with the efficient or another given condition. If the number of the discrepancy of the initial and valid values of the criteria exceeds the preset Hmiting

value it is possible to conclude about the disability

of the machine.

The advantage of the criteria of similarity is also in the fact that they can be made of any process

parameters, the phenomena connected by the functional dependence. At the control of the technical condition the criteria dependences made

of the structural and diagnostic parameters are also of interest. In this case it is possible to determine

the value of the structural and diagnostic parameter

(which registration is complicated) using accessible techniques and means of registration of the diagnostic parameters be the criteria dependence

without operations of dismantlement and without

breaking the manufacturing process in which the machine is involved.

107
J
DATABASE SYNCHRONIZATION TECHNOLOGY FOR

MULTI-PROJECT SCHEDULE COORDINATION

by

Hyun Jeong Choo' and Iris D. Tommelein^

ABSTRACT

This paper describes a computing environment, called WorkMovePlan, that supports the exchange of data pertaining to resources shared between multiple

production units and between multiple projects. It presents issues related to the

generation and management of this data exchange and the development of a

distributed, multi-project scheduling system that is deployed in industry practice.

KEYWORDS: Planning; Scheduling; Distributed Scheduling; Multi-project

Scheduling; Database; Synchronization; WorkMovePlan.

1. INTRODUCTION

In a complex and dynamic construction

project, no single participant can work in isolation for long. In addition, many participate

in several projects at the same time. Work of

every participant is interwoven with work of

others. This is especially true for those

responsible for production—designers,

construction personnel, and other specialists

who as individuals or as a team make up a production unit (PU)—as their deliverables are prerequisites to the work of others.

Production activities of PUs are interlinked

because of physical dependencies and resource dependencies (here, resources are information,

material, personnel, equipment, and space).

Whereas physical dependencies clearly

determine activity sequencing (e.g., in-wall

electrical and plumbing systems have to be

placed before wall panels are installed), resource dependencies do not: multiple

activity-sequencing alternatives might exist.

From the perspective of the PU performing

these activities, one alternative might not have

a clear advantage over another, but from the

perspective of others, or from the perspective

of the project as a whole, it may be superior,

for instance, if it "releases" more work or more

resources. Conversely, what one PU identifies as a superior alternative may be inferior on a broader systems basis.

The WorkMovePlan system described in this paper provides database and graphical support

for PUs to explore and rank alternatives, but it keeps people in the loop; WorkMovePlan does

not automate this process. Job-shop

scheduling, multi-objective decision-making,

and heuristic optimization are needed to gauge

and trade off what is best for individual PUs

vs. the system, but discussing these is beyond

the scope of this paper.

2. RESOURCE- vs. PROJECT-CENTRIC

DATA

Planners can assess the value of and compare

alternatives only if and when activity

descriptions are detailed enough and especially

when shared resource assignments are made

sufficiently explicit (exactly how detailed and

specific they have to be depends on the

simation). However, a single planner probably

does not have the knowledge to provide all that

is needed. PUs have to develop their own

PhD Candidate, Construction Engineering and Management Program, University of California, Berkeley,

215 McLaughlin Hall. Berkeley, CA 94720-1712, choohj@ce.Berkeley.edu

Professor, Construction Engineering and Management Program, University of California, Berkeley, 2 15-

A

McLaughlin Hall, Berkeley, CA 94720-1712, tomnielein@ce.Berkeley.edu, TEL 510/643-8678, FAX

510/643-8919

109
resource-loaded schedules based on each

member's skill level and productivity and then

share them with others to allow for comparison

and the selection of alternatives that best suit multiple interests.

^ To make effective trade-offs and generate

realistic schedules, planners need to adopt a more resource-centric view than they

traditionally have. Resource-centric means that the schedule for each resource is the building

block for the project and resources may be

engaged on multiple projects. This view is contrary to the view adopted by many webbased project management systems on the

market today, which are project-centric. Other

researchers also adopt a multi-project view, as

is presented here. For instance, Scherer et al. (2002) propose that each project participant

plan their workflow within the framework of

all projects s/he is involved in. A PU's resource-loaded schedule may contain

information about two types of resources: (1)

dedicated resources and (2) shared resources. Dedicated resources are committed solely to a

single PU on a single project. Shared resources

are committed to more than one PU or to more

than one project. Some shared resources may

serve multiple PUs on multiple projects, which

complicates the coordination problem even

more. Shared resources may be project shared

or company shared.

Project-shared-resources are resources used by

several PUs, but not necessarily 'owned' by

any. Examples are material hoists used by any

or all on site, but also personnel such as project

management staff (project engineers and

superintendents), and space such as material

storage areas, pre-installation and installation

working areas, and access paths. Companyshared-resources belong to a specific owner who is engaged in several projects. Examples

are equipment such as expensive hoisting

equipment, large plotters, and personnel such

as project managers and safety inspectors. This

distinction affects who has a say and what

objectives must be met in selecting from

alternative resource assignments.

Information regarding which projects share a resource is tracked by the resource's owner or whomever obtained (e.g., rented) the resource, whereas information regarding which PUs

share a resource resides in a production

schedule of each PU. In order to ensure that assignments do not result in conflict, resource

allocation needs to be checked across multiple

projects and PUs.

Several difficulties exist in achieving this goal

using current project (and production)

management tools: (1) each PU must develop

an appropriately-detailed resource-loaded

schedule and make a significant amount of

tacit planning knowledge explicit, (2) these

schedules must be described in a common

language so that they can be understood by

others, (3) data for these schedules must be

maintained in each company's database, while

schedules are being coordinated, alternatives

negotiated, and conflicts resolved, (4) data

must be reliable and disseminated in a timely

fashion.

3. WORKMOVEPLAN

3.1 Design Objectives

WorkMovePlan (Choo and Tommelein 2000a,

2000b), a computing environment designed to support distributed planning, allows each PU's

planner to create their own schedule.

WorkMovePlan' s aim is to help project

participants create more reliable schedules, in an effort to make the project delivery process more lean (also see www.Ieanconstruction.org).

The WorkMovePlan environment builds on

Microsoft Access (Microsoft 2000a) and

Microsoft Visio (Microsoft 2000d). Various

forms in Access allow the user to input and

manage a detailed activity list and resource assignments based on the Last Planner

methodology (Ballard and Howell 1994, Choo

et al. 1999). These activities can be directly

imported from Microsoft Project (Microsoft

2000c) or they can be developed from scratch. The hierarchical structure of the activities allows the user to break them down to any

level of detail. Since WorkMovePlan does not

rely on a single person but instead relies on

any or all production managers

(superintendents and foremen) to enter information, the description of activities and

resource assignments can get very specific.

The link to Visio allows planners to

110
geometrically detail space use based on space

layout stencils.

WorkMovePlan captures data pertaining to multiple projects. A project-specific detailed

schedule is automatically shared with other

project participants using database

synchronization technology. The PUs can then

check for shared resource conflicts within each

project and across projects.

WorkMovePlan maintains an offline copy of

other PUs' schedules as well as its own. It automatically updates changes only upon

synchronization. WorkMovePlan is portable

and does not require a fast consistent Internet connection. It can thus be used by

practitioners, including even those who do not have consistent Internet access to interact in

real time with an online database.

Each planner can look at the detailed

production schedule including space use on

site (described later) for all project participants

and determine whether they result in conflict. The planners then need to collaborate off-line

with others to develop alternatives for specific

conflicts and determine which alternative best

meets the needs of those in conflict, of the

projects they are involved in, and of their

companies.

3.2 'Near real time' Data Sharing based on

Synchronization

WorkMovePlan' s distributed planning and

coordination feature relies on 'near real time'

data sharing, which is based on the technology

called synchronization. Synchronization is defined as "the process of updating two

replicas in which all updated records and

objects are exchanged. The exchange of data

between two replicas can be one-way or twoway" (Microsoft 1999).

Each WorkMovePlan is a replica that is twoway synchronized. Each replica's database

contains two parts: one that contains private

information and another that contains public

information. Private information concerns the owner of the database. It contains information

regarding its resources, associate costs, and the

detailed schedule of each PU. This information

is not exclusive to a single project since resources may be shared across multiple

projects. The WorkMovePlan user can thus

schedule multiple projects at the same time.

WorkMovePlan automatically generates public

information by filtering out what is unnecessary to share, based on pre-set

conditions. For example. Figure 1 shows the

screenshots from WorkMovePlan for roof

drain installation. The bottom portion shows

the detailed weekly work plan for contractor

'Atlantic Roofs' as seen by its employees. The

top portion shows the weekly work plan for Atlantic Roofs as seen by all other project

participants. Accordingly, the private

information names Gilbert Atlas as the PU and

the exact hours (4.5, 8, and 5.5) he is scheduled to work. In contrast, the

automatically-generated public information

shows the name of the company the PU

belongs to (Atlantic Roofs) and only the days

(Wednesday, Thursday, and Friday) when

work will be done. By making a commitment

at a less detailed level to other project

participants, the PU creates flexibility to carry out work within any part of the revealed

duration. This is satisfactory as long as the

output thus delivered does not to prevent

others from performing their work.

Public informadon is the replicated part of

WorkMovePlan (Figure 2). By replicating

public information between all replicas of

WorkMovePlan, schedule information

regarding all PUs can be automatically

updated. A similar data categorization is used

in Microsoft Exchange Server (Microsoft

2000b), which can be configured to contain

private- as well as shared information. The

shared information can be created and viewed

by any one who has been granted permission to do so. However, private information is accessible only by each so-designated

individual and not by anyone else.

WorkMovePlan automatically synchronizes

only information that is relevant to each

project (Figure 3). The main reason for

designing the database in such a way, rather

than using a centralized on-line database, was

that not all PUs have a consistent Internet connection. Despite recent advancements in information technology, project site offices

rarely have high-speed Internet access, especially at the start of a project. Project

managers have pointed out that their planning

111
system has to be in place from day one (at the

latest!) because once the project starts, it is very hard for them to learn and/or change

procedures and support tools. Another reason

is that many PUs are protected by companyand project-specific firewalls. These firewalls,

in many cases, prevent users from taking

advantage of the available full speed of their Internet connection. Should online planning

tools be used during meetings, progress of the

meeting would slow down to match the

Internet connection speed.

A disadvantage of using synchronization

technology is that data is not available to all project participants in real time. Project

participants might not synchronize

WorkMovePlan for some time, but still create

their own plans based on obsolete data from

others. This may result in conflict between

project participants' schedules and create rework when synchronization takes place.

By keeping a copy of the 'near real time'

information, i.e., the information that was

available the last time the database was

synchronized, the owner of each

WorkMovePlan replica can still view the

schedule information of others off-line.

4. EXTENDED RESOURCE PLANNING

WorkMovePlan extends planning to include

space scheduling (Tommelein and Zouein

1993). A planner can specify site space needs on a day-to-day basis for labor, equipment, and

materials in terms of work-, laydown-, staging

area, or access path as needed throughout the

execution of a work package, which is the unit

of work assigned to a PU. WorkMovePlan

requires the user to explicitly input information on resources that need to be considered during

space scheduling (Figure 4). This space

scheduling information is automatically

synchronized in the same way as is done for

other resources.

Default categories for space scheduling refer to material, equipment, and labor but others can

be included as needed. Shape refers to the

physical shape of the space required. X, Y, and

Z refer to the dimensions of the needed space. Although three dimensions are specified,

WorkMovePlan' s space scheduling takes place

in a 2-D environment.

2-D drawings (such as blueprints showing a

site arrangement or a building floor) are widely

available and space can be assigned easily in 2- D. 2-D layouts convey space scheduling

information in a straightforward fashion. They

are crude but adequate for this application.

Nevertheless, the height dimension entered by

the user can later be combined by

WorkMovePlan with the layout schematic to generate a 3-D virtual reality mock-up using

the Virtual Reality Modeling Language

(VRML 1995). Figure 6 shows a sample

VRML model that is automatically generated

from WorkMovePlan.

The default schedule for space use is from the

start- to the end date of the work package, but

it can be adjusted to represent other realities,

such as the delivery of materials a day prior to the start of the work package. Once all resources to be assigned are specified, their

positions can be selected using a graphical user

interface (GUI). WorkMovePlan builds on

Microsoft Visio as the GUI for space

scheduling. All information generated within

Visio is captured by WorkMovePlan and

shared across all project participants. Planners can view other participants* space use when

scheduling their own space use. Choo and

Tommelein (1999) describe an example

application of WorkMovePlan.

5. CONCLUSIONS

The ability to build realistic schedules for

projects as well as for individual PUs depends

heavily on being able to collect and distribute

reliable information. The most reliable

information regarding resource characteristics

(e.g., productivity and availability) resides with

each PU. However, having information from

each PU does not necessarily guarantee a

realistic schedule unless the planning process

itself promotes realistic planning. The realism

of schedules also depends heavily on

timeliness of the data being used. Each

participant has to create and provide data to other participants with sufficient lead time to allow for conflict detection and resolution.

WorkMovePlan is a tool that helps to collect and capture such data, and it makes selected

data available for sharing with other project

participants. WorkMovePlan' s ability to make

detailed assignments in terms of labor.

112
equipment, and space will allow project

participants to generate more realistic schedules than they currently do.

WorkMovePlan suggests a very different way

of coordinating project participants as compared to what is done in current practice,

which includes numerous 'throw-away

schedules' that so many PUs generate today

(Russell and Froese 1997). Resistance is expected when a new planning paradigm is presented. Choo and Tommelein (2001)

discuss several barriers to adoption in industry

practice of the Last Planner methodology and

the WorkMovePlan environment. It remains to be seen whether the industry will widely

embrace either one or both. In the mean time,

additional research is to result in better tools for job-shop scheduling, multi-objective

decision-making, and heuristic optimization,

which can then be integrated with

WorkMovePlan.

6. REFERENCES

Ballard, G. and Howell, G. (1994).

"Implementing lean construction: stabilizing

work flow." Proc. 2"'^ Ann. Conf. on Lean

Constr., Santiago, Chili, Sept. Reprinted in Alarcon, L. (1997)(ed). Lean Construction.

A.A. Balkema, Rotterdam, The Netherlands,

497 p.

Choo, H.J. and Tommelein, I.D. (1999).

"Space Scheduling using Flow Analysis" in Tommelein, I.D. (ed.). Proc. 7^ Annual Conf.

International Group for Lean Construction,

26-28 July, Berkeley, CA, 299-31 1.

Choo, H.J. and Tommelein, I.D. (2000a).

"WorkMovePlan: Database for Distributed

Planning and Coordination." Proc. 8''' Ann.

Conf. Intl. Group for Lean Construction

(IGLC-8), 17-19 July, held in Brighton, UK.

Choo, H.J. and Tommelein, I.D. (2000b).

"Interactive Coordination of Distributed Work

Plans." Proc. Construction Congress VI, ASCE, 20-22 Feb., Orlando, Florida, 11-20.

Choo, H.J. and Tommelein, I.D. (2001).

"Requirements and Barriers to Adoption of

Last Planner Computer Tools." Ninth Annual

Conference of the International Group for Lean

Construction (IGLC-9), 6-8 August,

Singapore.

Choo, H.J., Tommelein, I.D., Ballard, G., and

Zabelle, T.R. (1999). "WorkPlan: Constraintbased Database for Work Package

Scheduling." ASCE, J. of Constr. Engrg. and

Mgmt., 125 (3) 151-160.

Microsoft (1999). Synchronization. Microsoft

Corp., Redmond, WA, http://msdn.microsoft.

com/library/default. asp?url=/library/

en-us/dao360/html/ rpldefsynchronization.asp.

Microsoft (2000a). Microsoft Access,

Microsoft Corporation, Redmond, WA,

http://www.microsoft.com/office/access/.

Microsoft (2000b). Microsoft Exchange

Server, Microsoft Corporation, Redmond, WA,

http://www.microsoft.com/exchange/.

Microsoft (2000c). Microsoft Project,

Microsoft Corporation, Redmond, WA,

http://www.microsoft.com/office/project/

Microsoft (2000d). Microsoft Visio, Microsoft

Corporation, Redmond, WA,

http://www.microsoft.com/office/visio/.

Russell, A. and Froese, T. (1997). "Challenges

and a Vision for Computer-integrated

Management Systems for Medium-sized

Contractors." Can. J. Civ. Engrg., 24 (2) 180-

190.

Scherer, R., Keller, M., and Menzel, K. (2002).

"Personalized Cross-Project Workflow

Approach For Multi-Project Participants." 3rd

Intl. Conf. on Concurrent Engrg. in Construction (CEC02), 1-3 July, Univ. of

California, Berkeley, CA, pp. 41-50,

http://www.ce.berkeley.edu/~tommelein/concu

r02/SchererEtAl.pdf

Tommelein, I.D. and Zouein, P.P. (1993).

"Interactive Dynamic Layout Planning." J. Constr. Engrg. and Mgmt., ASCE, 119 (2)

266-287.

VRML (1995). The Virtual Reality Modeling

Language, Version 1.0 Specification, 26'MAY95, available at http://www.virtpark.com/

theme/vrml/, visited 7/16/99.

113
Public

Information

Private

Information

Pny'ectNo Project. Name Name (Jiin) Tiiis Week

Cost Code Assignment Desc 2S 29 30 1 3 4

97-309-C /ttREAA

1 000 P H R oof-Area B;Roucti-lnRcofD rains Atlantic Roofs

Sheet Metal - -

Project No Project Nams! A'ome (Jun) Tfiis Week

Cost Code Asdgmnent Desc 2S 29 30 1 3 4

97-309-C 1000ARE A A

PH Rcot-AreaB: Rouch-lnRcof Drains

GilliertAtlAS 4 5 8 5.5 Sheet Metal

Figure 1. Relationship between Private Information vs. Public Information

SC-1

WMP

Private Public

Info. Info.

WMP

Private Info.

Public Info.

Internet n

WMP

Public Info.

Private Info.

SC-n

WMP

Public Private

Info. Info.

SC-2

Figure 2. WorkMovePlan (WMP) Synchronization Scheme

114
Figure 3. WorkMovePlan's Multi-project Scheduling Scheme

Space Scheduling

Please specify all resources that require space on site

Work Package No |97-309-c-iooo ^ j Categories |Equipment v|

Description [Loader

I

jShapej

^

\ <^ Rectangle <^ Circle C Triangle

X I 45| Y I 3o| Height I io| Color |Biack ^|

Name 1 28 1 | 2 | 3 | H | 5 | G 7 1 8 1 9 10 11 12 13 Gray Andre 8 8

Patterson Andy 8 8 8

Air Compressor 8 8 AM g| 51 gi PM gi

Aid

Resources to be on site

'Work Package No Categories Description Shape

97-309-C-1000 Equipment Generator Rectangle 97-309-C-1000 Labor <Nork\r\g Area Triangle 97-309-C-1000 Material Staging Area Triangle 97-309-C-1 1

Labor I'^orking Area Rectangle 97-309-C-400 Material Diti Pile Circle 97-309-C-400 Material Pallets Rectangle 97-309-C-500 Material Pallets of Cement Circle

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Figure 4. Space Scheduling Screen 1

115
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Figure 5. Space Scheduling Screen 2

Figure 6. Sample Site Layout using VRML

116
Project Performance vs. Use of Technologies

at the Work Function Level

by

James T. O'Connor' and Li-Ren Yang"

ABSTRACT: An industry-wide survey was used to collect project data from more than 200 capital facility projects on the issue of technology usage at the work function (WF)

level and overall project success. Findings pertaining to associations between project success and technology usage at the work function level are discussed. The project success

variables analyzed include project schedule success and project cost success. Research hypotheses analyzed in this study are presented as follows: 1 ) High-Tech WFs vs. Project Schedule Success, 2) Low-Tech WFs vs. Project Schedule Failure, 3) High-Tech

WFs vs. Project Cost Success, and 4) Low-Tech WFs vs. Project Cost Failure. Project

schedule success or failure is particularly leveraged with technology usage or lack thereof

for developing scope of work, acquiring & responding to shop drawings, communicating

Requests for Information & response, providing feedback about cost & schedule impacts

from changes, using as-built information in operator training, and updating as-built drawings. Project cost success or failure is particularly leveraged with technology usage or

lack thereof for monitoring faciUty energy consumption.

KEYWORDS: cost success, schedule success; technology usage; work function; work

function characteristics

1. INTRODUCTION

1.1 Study Background, Study Objectives,

and Scope Limitations

This paper presents findings pertaining to associations between project success and

technology usage at the work function level. The data upon which these statistics are based were collected from more than 200 capital

facility projects in the lower 48 states of the

U.S. between October 1998 and August 1999.

Technology usage metrics analyzed include

those for High- and Low-Tech WFs. HighTech and Low-Tech WFs are associated with

the highest levels of technology utilization

(Level 3) and the lowest levels of technology

utilization (Level 1) in executing work

functions for the subject project, respectively.

The project success variables analyzed

include final performance of the projects in terms of schedule and cost success. With

respect to the schedule success variable,

schedule success is defined to have occurred

when the actual project completion date was

significantly earlier than planned. Schedule

failure occurs when the actual project

completion date was significantly later than

planned. For the cost success variable, cost success is defined to have occurred when the

total installed cost was significantly under

authorized budget. Cost failure occurs when

the total installed cost was significantly over

authorized budget.

1.2 Research Hypotheses

Research hypotheses analyzed in this study

are detailed as follows: 1) Higher levels of

project schedule success are associated with

certain WFs when High-Tech approaches are applied to those WFs, 2) Lower levels of

project schedule success are associated with

certain WFs when Low-Tech approaches are applied to those WFs, 3) Higher levels of

' Professor, Department of Civil Engineering, ECJ

5.2, The University of Texas, Austin, TX 78712; PH

5 1 2-47 1 -4645 ; jtoconnor@mail.utexas.edu

^ Graduate Research Assistant, Department of Civil Engineering, ECJ 5.2, The University of Texas,

Austin, TX 78712; lrv@mail.utexas.edu

117
project cost success are associated with certain

WFs when High-Tech approaches are applied

to those WFs, and 4) Lower levels of project

cost success are associated with certain WFs

when Low-Tech approaches are applied to those WFs.

1.3 Methodology

Salient aspects of the research methodology

are presented as follows:

Small projects (<$5mil.) were excluded

from the analysis.

High-Tech/High Schedule Success WFs

involve significantly more technology

usage and are associated with a higher

rate of schedule success. Low-Tech/Low Schedule Success WFs

involve significantly less technology

usage and are associated with a lower rate of schedule success. High-Tech/High Cost Success WFs

involve significantly more technology

usage and are associated with a higher

rate of cost success. Low-Tech/Low Cost Success WFs

involve significantly less technology

usage and are associated with a lower rate of cost success. Project schedule success or failure is particularly leveraged with technology

usage or lack thereof for the work

functions pertaining to both HighTech/High Schedule Success WFs and

Low-Tech/Low Schedule Success WFs.

Project cost success or failure is particularly leveraged with technology

usage or lack thereof for the work

functions pertaining to both HighTech/High Cost Success WFs and LowTech/Low Cost Success WFs.

2. SCHEDULE SUCCESS FINDINGS

2.1 High-Tech/High Schedule Success WFs

Table 1 presents High-Tech WF descriptive

statistics according to project schedule

performance. High-Tech/High Schedule

Success WFs involve significantly more

technology usage and are associated with a

higher rate of schedule success, so HighTech/High Schedule Success WFs include the

following work functions (presented in order of

significance):

Develop scope of work

Model user's process

Conduct needs analysis

Prepare milestone schedule

Train facility operators

Use as-built information in operator

training

Provide feedback about cost and schedule

impacts from changes

Earthwork & grading

Acquire and respond to shop drawings

Develop detailed construction schedule

Communicate Requests for Information

& response

2.2 Low-Tech/Low Schedule Success WFs

Table 2 presents Low-Tech WF descriptive

statistics according to project schedule

performance. Low-Tech/Low Schedule

Success WFs involve significantly less technology usage and are associated with a lower rate of schedule success, so LowTech/Low Schedule Success WFs include the

following work functions (presented in order of

significance):

Provide feedback about cost and schedule

impacts from changes

Link between supplier cost quotes and

cost estimate

Request facility maintenance or modifications

Update as-built drawings

Use as-built information in operator

training

Develop scope of work

Submit contractor's request for payment

Provide elevated work platform

Acquire and respond to shop drawings

Detect physical interferences

Acquire and record material lab test results

118
3. COST SUCCESS FINDINGS

3.1 High-Tech/High Cost Success WFs

Table 3 presents High-Tech WF descriptive

statistics according to project cost performance.

High-Tech/High Cost Success WFs involve

significantly more technology usage and are associated with a higher rate of cost success, so High-Tech/High Cost Success WFs include the

following work functions (presented in order of

significance):

Monitor facility energy consumption

Monitor environment impact from

operations

Fabricate roof trusses Design HVAC systems

Design electrical systems

Monitor equipment operations

• Conduct needs analysis

Track the inventory of materials on site Prepare floor plans

Link between quantity survey and cost estimate

Model user's process

3.2 Low-Tech/Low Cost Success WFs

Table 4 presents Low-Tech WF descriptive

statistics according to project cost performance.

Low-Tech/Low Cost Success WFs involve

significantly less technology usage and are associated with a lower rate of cost success, so Low-Tech/Low Cost Success WFs include the following work functions (presented in order of

significance):

Use as-built information in operator

training

Update as-built drawings

Track design progress

Document budget assumptions

Train facility operators

Providing feedback about cost and

schedule impacts from changes

Update as-built drawings

Owner payment to contractor Monitor facility energy consumption

4. WORK FUNCTION

CHARACTERISTICS

Additional analyses of the data are on going

and pertain to Work Function Characteristics

(WFCs). WFCs are differentiae that characterize the 68 work functions. A total of

31 WFCs based on 6 categories (i.e., WF

procedures, Time/Space/Cost, Information &

data. Management, WF product, and Human

resource) were developed by O'Connor and

Won to classify work functions by their

attributes. WFC analysis reveals characteristics

common to a specific work function group.

This approach helps explain why different levels of technology usage exist and why

specific technologies and tools are in more

demand. Details associated with WFCs and

discussion regarding these analyses are included in Won's dissertation.

5. CONCLUSIONS

5.1 Analysis Results for Schedule Success

Presented in order of significance, HighTech/High Schedule Success WFs include the

following work functions:

Develop scope of work

Model user's process

Conduct needs analysis

Prepare milestone schedule

Train facility operators

Use as-built information in operator

training

Presented in order of significance, LowTech/Low Schedule Success WFs include the

following work functions:

Provide feedback about cost and schedule

impacts from changes

Link between supplier cost quotes and

cost estimate

Request facility maintenance or modifications

Update as-built drawings

Use as-built information in operator

training

Develop scope of work

119
Attention should be paid to the work

functions pertaining to both High-Tech/High

Schedule Success WFs and Low-Tech/Low

Schedule Success WFs. Project schedule

success or failure is particularly leveraged with

technology usage or lack thereof for these work

functions:

Develop scope of work

Acquire and respond to shop drawings

Provide feedback about cost & schedule

impacts from changes

Use as-built information in operator

training

5.2 Analysis Results for Cost Success

Presented in order of significance, HighTech/High Cost Success WFs include the

following work functions:

" Monitor facility energy consumption

Monitor environment impact from

operations

Fabricate roof trusses Design HVAC systems

Design electrical systems

Monitor equipment operations

Conduct needs analysis

Track the inventory of materials on site

Presented in order of significance, LowTech/Low Cost Success WFs include the

following work functions:

Use as-built information in operator

training

Update as-built drawings

Track design progress

Document budget assumptions

Project cost success or failure is particularly

leveraged with technology usage or lack thereof

for the work function "Monitor facility energy

consumption."

6. RECOMMENDATIONS FOR FUTURE

RESEARCH

Recommendations for future study are

offered:

Work function characteristics associated

with High-Tech/High Schedule Success

WFs, Low-Tech/Low Schedule Success

WFs, High-Tech/High Cost Success

WFs, and Low-Tech/Low Cost Success

WFs may help further explain project success. Any future similar survey should involve

expansion of assessment levels from 3 to 4 in order to improve resolution of

estimates of technology usage.

7. REFERENCES

[1] O'Connor, J. T., Kumashiro, M. E., Welch,

K. A., Hadeed, S. P., Braden, K. E., and

Deogaonkar, M. J. (2000). "Project- and phaselevel technology use metrics for capital facility

projects." Report No. 16, Center for

Construction Industry Studies, University of

Texas, Austin, Texas.

[2] O'Connor, J. T., and Won, S. (2001). "Work

function-level technology use metrics for

capital facility projects." Report No. 18, Center

for Construction Industry Studies, University of

Texas, Austin, Texas.

[3] O'Connor, J. T., and Won, S. (2001).

"Understanding Demand for Technology via

Work Function Characteristics", Proc, Special

Conference on Fully Integrated and Automated

Project Processes, Virginia Polytechnic and

State University, Blacksburg, Virginia, 13-24.

[4] O'Connor, J. T., and Yang, L. (2002).

"Capital facility project success and technology

usage." Report No. 22, Center for Construction

Industry Studies, University of Texas, Austin,

Texas.

[5] Won, S. (2002). "A model for work

function-based prioritization of technologies for

capital projects." PhD thesis, University of

Texas, Austin, Texas.

120
Table 1. High-Tech WF Descriptive Statistics by Project Schedule Performance

% of Responses at Level 3

ID WF

% of Projects

with

Schedule Success

% of Projects

with

Schedule Failure

A % Rank

1.01 Conduct needs analysis 33 0 33 3

l.Oi Develop scope of work 36 0 36 1 1.03 Model user's process 42 8 34 2

1.05 Prepare milestone schedule 40 10 30 4

3.09

Acquire & respond to shop

-J ^ drawmgs

22 0 22 9

4.01

Develop detailed construction

schedule

33 11 22 9

4.09

Communicate Requests for

Information & response

25 5 20 11

4.10

Cost & schedule impacts from

changes

24 0 24 7

5.02 Earthwork & grading 24 0 24 7

6.02 Train facility operators 33 8 25 5

6.03

Use as-built information in operator

training

33 8 25 5

Table 2. Low-Tech WF Descriptive Statistics by Project Schedule Performance

% of Responses at Level 1

ID WF

% of Projects

with

Schedule Failure

% of Projects

with

Schedule Success

A % Rank

1.02 Develop scope of work 26 0 26 6

2.11 Detect physical interferences 41 20 21 10

3.04

Link between supplier cost quotes

and cost estimate

50 19 31 2

3.09

Acquire & respond to shop

drawings

56 33 23 8

4.10

Cost & schedule impacts from

changes

78 29 49 1

4.14

Submit contractor's request for

payment

53 29 24 7

5.06 Provide elevated work platform 69 46 23 8

5.09

Acquire & record material lab test results 50 29 21 10

6.03

Use as-built information in operator

training

62 33 29 5

6.07

Request facility maintenance or modifications

50 20 30 3

6.08 Update as-built drawings 43 13 30 3

121
Table 3. High-Tech WF Descriptive Statistics by Project Cost Peri'ormance

II) WF

% of Responses at Level 3

A % Rank % of Projects

with

Cost Success

% of Projects

with

Cost Failure

1.01 Conduct needs analysis 25 0 25 6

1.03 Model user's process 21 0 21 11 2.05 Prepare floor plans 44 20 24 9

2.08 Design electrical systems 47 18 29 5 2.09 Design HVAC systems 47 14 33 3

3.03

Link between quantity survey and

cost estimate

31 8 23 10

4.06

Track the inventory of materials on

site 25 0 25 6

5.07 Fabricate roof trusses 33 0 33 3 6.06 Monitor equipment operations 38 13 25 6

6.09

Monitor facility energy

consumption

70 14 56 1

6.10

Monitor environment impact from

operations

43 0 43 2

Table 4. Low-Tech WF Descriptive Statistics by Project Cost Performance

ID WF

% of Responses at Level 1 A % Rank % of Projects

with

Cost Failure

% of Projects

with

Cost Success 2.10 Document budget assumptions 36 12 24 4

2.14 Track design progress 42 17 25 3

4.10

Cost & schedule impacts from

changes

75 55 20 6

4.13 Update as-built drawings 50 30 20 6

4.15 Owner payment to contractor 63 43 20 6

6.02 Train facility operators 63 40 23 5

6.03

Use as-built information in operator

training

67 40 27 1

6.08 Update as-built drawings 40 14 26 2

6.09

Monitor facility energy

consumption

29 10 19 9

122
DEVELOPMENT OF AN INFORMATION MODEL TO ENHANCE

INTEGRATION AND COORDINATION IN THE CONSTRUCTION PROJECTS

Amaury A. Caballero Ph.D., PE.; Syed M. Ahmed Ph.D.; Salman Azhar;

and Maribel Barcala

Florida International University

10555 W. Flagler Street, Miami, Florida 33174, USA

ABSTRACT: Construction is generally believed to be a fragmented industry and increased

integration and coordination among different processes and parties is considered by many

experts as one of the ways that can resolve most of the problems created by fragmentation. Process inefficiency and a lack of effective quaUty control in the products of construction are often attributed to fragmentation. The recent developments in information and communication

technology (ICT) have provided an opportunity to increase the level of integration among

different construction processes by improving the flow of information. This paper examines

the possibilities of increasing integration in the construction industry by integrating the planning, design, and construction processes. In addition, an information model is proposed

to integrate the different phases in the construction operations and to increase interaction among the stakeholders. KEY WORDS: Construction, Information Technology, Coordination, Integration, Modeling

1. INTRODUCTION

The construction industry is highly fragmented

as compared to other industries. This may have

caused significant low productivity, cost and

time overruns, conflicts and disputes, resulting

in claims and time consuming litigation.

(Latham 1994).

The fragmentation problem is further

compounded by the fact that the construction

process typically involves several disciplines,

e.g. architects, structural engineers, building

services fHVAC) engineers, quantity surveyors,

contractors, sub-contractors, material suppliers

etc., collaborating for relatively short periods in the design and construction of a facility. Until

fairly recently, these disciplines tended to work

independently, while making decisions that affect the others (Anumba, 2000).

Another facet of the fragmentation problem

is the fact that the construction projects

whether they be buildings, bridges, dams, or offshore structures usually involve many

stages, starting from the establishment of the

client's requirements through to design,

construction, utilization and eventual disposal of

the facihty. These stages of the project's life cycle and the associated activities and tasks are often undertaken as discrete processes, with only

limited integration of data/information,

participants, tools and procedures etc (Anumba,

2000).

Some of the consequences of the fragmentation

problem include (Amor and Anumba, 1999):

• Inadequate capture, structuring,

prioritization and implementation of

client needs.

• The fragmentation of design, fabrication

and construction data, with data

generated at one project not being

readily re-used downstream.

• Lack of integration, coordination and

collaboration between the various

functional disciplines involved in the

life-cycle aspects of the project. • Lack of true life cycle analysis of

projects (including costing, maintenance

etc.). • Poor communication and design intent

and rationale, which leads to

123
unwarranted design changes,

unnecessary liability claims,

increase in design time and cost, and

inadequate pre- and post-design

specifications.

To achieve the benefits obtained from a good

information system, it will be necessary to

clarify:

• What information is needed, in which

form and during which project stage?

• What decisions will be made and when?

• Who should contribute to these

decisions?

• Who should communicate to whom?

The purpose of this research was to fmd the answers to these questions and present them in the form of a graphical model, which could

integrate the different construction stages. A

number of research projects have addressed

aspects of integration among two or more stages

in the building project life cycle. However, there

are presently no integration models available

that are applicable to the whole project life cycle

from conception to demolition. Nevertheless the

feasibility and desirability of fully integrated

lifecycle models has been restricted to small

models. There is a gap in research particularly

into the development of appropriate integrated

models for the planning, conceptual design, and

demolition stages of the project lifecycle. An

important challenge in lifecycle integration is ensuring that the models are consistent,

persistent, and able to convey data as well as the

underlying design intent and rationale. (Amor,

1999; Anumba, 2000).

Important opportunities for improving

performance of engineering and construction

projects may be obtained through the integration

of planning, design, and construction phases.

With the construction integration process,

suppliers have a growing influence on the

design, which results in designs that better fit the

construction needs. This process has been

defined as the continuous and interdisciplinary

sharing of goals, knowledge, and information

among all project participants (Gilbertus, 1997).

The recent efforts of rationalizing the industry

reached the point to integrate planning, design.

fabricating, and assembly process like manufacturing industry. The previously separated

design information and construction process

planning are combined and integrated as a big

construction system. That conceptual progress is considered (Hasegawa, 2000) as the trigger of

construction automation.

2. OBJECTIVES

The main objective of this paper is to present a model that integrates the project

through the construction stages in a building.

This is not a feasibility study nor is it a software

architecture. The authors propose a framework

for the flow of information between the different

construction process participants. It is basically a logic diagram (Figures 1 and 2) that can be

used to develop an architecture. These stages are clearly defined in previous works. For any

building it is possible to identify four

construction stages and one operation stage. The

construction stages are defined as: (Eastman,

1993):

1. Feasibility study

2. Design

3. Construction planning

4. Construction

3. METHODOLOGY

The model has been improved during two years

with the help of the Construction Management

Program graduate students working in the

construction industry. All of our graduate

students are working full-time in the local construction industry in responsible managerial

positions and have an average of over 10 years

of experience in the construction industry. The

authors believe their input is therefore, very

relevant to real construction projects. The goal was to receive feedback from them that could

help us to refine it. The following guidelines were included to help in the graduate students

work.

1. All the parties will work on the product

from the early stages up to the

production stage like a team. The

previously separated design information

and construction process planning stages

124
have to be combined and integrated

as a fully integrated construction

system.

2. The process will be changed

interactively and according to the

needs.

3. All the information should be in a standard format recognized by all the professionals.

The data flow diagram for each stage in a

construction project is shown in Figure 1, and the interaction between the different

parties is shown in figure 2. The data model

exhaustively defines the construction project

through its entire construction cycle. The

data includes graphic representation in four

dimensions, technical and cost calculations,

scheduling, etc. The ultimate goal of this model is to form a software bridge between

mathematical coding - the language that computers read - and the characters and

pictures that human can see and understand.

4. MODEL DISCUSSION

The first stage in any construction project is the

feasibility study. The feasibility study is the

generator of the building model and thus

influences the design and later stages. This

stage also plans and sets goals at a general level for all the other stages. It defines the purposes

of the building project and assesses if the resources are appropriately matched with the

project scope. At this stage, the costs are balanced with the function of the building. The

planning at this level of the building model often

involves developing many different feasibility

models and comparing them in different

dimensions.

The design stage involves the translation of

functional criteria developed in the feasibility

stage into detailed descriptions of the building

project, including the preparation of detailed

drawings and specifications. The advantage of

this model is that since all the parties are involved in this process, different design

alternatives could be easily evaluated and the

bets and optimized design can be selected.

In the construction planning stage the bidding, the

impact on cost/schedule, and the construction plan

are completed. The construction stage executes the

construction plan. During this stage, if there is any

change in the design or specifications, it could be

easily incorporated by the consultation of the owner

and the designer.

Due to the cheap availability of the information

technology, this model could be easily converted

into a software system, which can store and manage

all the information. Such software could be coupled

with the state-of-the-art web-based technologies. In

this way, all the information will be available on-line

and accessible to all the project parties regardless of

time and space limitations.

5. CONCLUSIONS

A model to increase interaction among

stakeholders in the construction process has

been presented. The proposed model attempts to deal with all the involved parties from the onset of the project in a manner similar to a construction team. This is a great advantage for the project itself because all changes can be

discussed among the different parts of the team

before these have to be implemented. This is also very helpful to the management in making

better decisions about any upgrade of the

project. The model may also contribute to reducing the level of risks during the

construction stage.

One effect of the construction integration

process is that the suppliers will have more

influence on the design process, which results in designs that better fit the construction needs.

The recent efforts of rationalizing the industry

has reached the stage where it is necessary to integrate planning, design, fabricating, and

assembly process like the manufacturing

industry. Managerial functions like engineering,

management control, contract administration,

and others, move towards the integration.

One limitation of this study could be that the

feedback was generated only from graduate

students. It is recommended that future studies

could be expanded to include more diverse

participants from the construction industry.

125
6. REFERENCES

Amor R. & C. J. Anumba (1999, August). A

Survey and Analysis of Integrated Project

Databases. Concurrent Engineering

Construction: Challenges for the New

Millennium, CIB Publication 236, Espoo,

Finland. 217-227.

Anumba C. J. (2000). Integrated Systems for

Construction: Challenges for the Millennium.

Proceedings of the International Conference on

Construction Information Technology (INCITE)

2000, Hong Kong, 78-92.

Eastman, C. M. (1993, August). Life Cycle

Requirements for building product models.

Proceedings of the T' International Conference

on Management of Information Technology for

Construction. Singapore.

Gilbertus T. (1997, June). Automating

Communication in Civil Engineering. Journal of

Construction Engineering and Management. V123,No. 2. 113-120.

Hasegawa Y. A. (2000). New Wave of

Construction Automation and Robotics in Japan.

Proceedings of the 17'*' International

Symposium on Automation and Robotics in Construction ISARC 2000. Taipei, Taiwan, kl5

-k20.

Latham, M. (1994) Constructing the Team.

London: Her Majesty Stationary Office

(HMSO).

126
Feasibility Stai

< ^1 Ovmer'i Project Manag«tn«nt ^

. staff^

:

7

Project Concept

Conceptual Design

Documentation

Usable Space & Total Units Market Absorption Model

Project Cost & Cash Flow

Project Schedules

Matenal & labor quantty availability

D«tlgn Team ^ Archlted and Engfnten

Definition ol the Project &

Prehminafv Design

Design Stage {

Approved Definition of the Project & Preliminary Design

Detail Design include Gral & Detail Drawings & Specifications

Approved Final Owner's Estimation Storage of Database

through

Internet and / or

Intranel:

Construction J

Planning Stag^

V

r ->

Construction Management

Contractor

Construction-^

Stage \

Design Documents

Project Costs, Cash Flow

Schedule f-letworK Design & Site Changes

Generate Change Orders

Matenal & Labor Availability Constnjction Strategies V

NOTES: — .^-The dashed line represents the interaction between the parties. ^ The continuous line shows how the data is sent to or received from the database storage. However, the interconnection between the processes take place in the database.

Evaluation of Preliminary Design of the Project

Project Management Team

Bid Package &

Notice to Bidders

Selection of the Contractor

CAD System Descnplion

Construction Task Planning

Site Investigation Regional Resource Planning DeatI Product Identification

Design Documents

Terms of Functional Service

Project Cost & Cash Flow

Schedule Network

Coordinate Team's work

Construction Strategies Evaluation of Change Orders

Figure 1 . Data Flow Diagram for each Stage in a Construction Project

127
'"''<5wi»ef "

The Project Concept &

Conceptual Design Documentation IDesfgii Team''

Architect and Engineers < >

Definition of the Project &

Preiinninary Design

Approved Definition of the Project & Preiinninary Design

Detail Design include: Gral & Detail Drawings & Specifications

Approved Final Owner's Estimate

/

Project Management Team

Bid Package L

Notice to Bidders

Bidders get info by invitationBidders get ingo

tlirougi) Internet

Selection of the Contractor

Construction M^hagemetit

Contractor

Project Cost 8. Schedule Network

NOTE:

The direction of the arrows indicate how the information is flowing through the system. ^ The doted line represents the owner's actions through the server. ! The dashed line indicates the interactions of the parties through the database. • The continuous line shows how the data is sent to or recerved from the database storage. We can visualize the proposed management process by using a database storage on Internet and / or Intranet. The information is available to any party at anytime. Therefore, it would benefit communication between the parties during the bid process.

Bidders can get information easily reglardless of where they are located.

In case of design changes, the Project Management Team can access information instanstaneously. Because all parties involved have access to the same database, they have the same information source.

Figure 2. Interaction Between Parties

128
Development of an Integrated Cost Estimation and Cost Control System

for Construction Projects

Salman Azhar, Syed M. Ahmed and Amaury A. Caballero

Florida International University

10555 W. Ragler Street, Miami, Florida 33174, USA

ABSTRACT

Today, most of the construction companies are using computer-aided softwares for cost estimation and

cost control. The cost estimation is done before the construction begins while the cost control is performed during the construction period. The organization which controls the cost could be different

from the organization which prepares the cost estimate. Moreover, different softwares are available for cost estimation and cost control. This may complicate the cost control process due to inconsistencies

between the cost estimation and cost control data. The purpose of this study is to develop a system which

could integrate the cost estimation and cost control processes. Such integration enables the transfer of cost estimation data automatically to the cost control process. Therefore, complete information regarding the cost status of the project can be accessed at any time. Systems Analysis and Design (SAD) approach

using relational database management system is used to develop the integration model. MS Access''"'*^ is used as a physical tool to implement and test the system. This paper provides a glimpse of the

requirements analysis, system development and implementation stages.

KEYWORDS

Cost Estimation; Cost Control; Cost Integration; Cost Engineering; Construction Softwares, Data

Modeling

1. INTRODUCTION

Cost engineering consists of cost estimation and

cost control. Estimation is a methodology for

forecasting and predicting cost and expenditures

of a future project and to produce a budget. Cost

control is a process to hold expenditures within

the budget by monitoring and appraisal of the

cost performance (Clark and Lorenzoni, 1997).

In most construction projects, cost estimation

and cost control are performed by different

people (e.g. estimation is done by quantity

surveyors or estimators while cost control is the

responsibility of the owner or contractor's cost engineers) and sometimes by different

organizations using different techniques and/or

softwares (Kibler, 1992). Due to these reasons,

the cost estimation and cost control data are usually available in different forms and at

different levels of detail. This inconsistency of

data results in lack of accuracy and untimely

generation of cost control reports for any

corrective decision making (Cagle, 1991).

However, if the estimation and control processes

are integrated, there will be a communication of

information between the two processes. The

results of the cost control process can be used as a feedback to the estimation process for future

projects, while a good estimate may make the

control process more effective.

Therefore, this study is conducted with the

objective of developing an integrated cost estimation and control system which could

facilitate the transfer of information between the

two processes for current and future projects.

The system identifies the linkages (common

attributes) between the two processes and

by

129
presents a data flow schema to implement it in the real life using any database management

software such as MS Access^'*^ or OracleTM.

2. METHODOLOGY

Due to its inherent simplicity, systems analysis

and design (SAD) approach is selected to develop the integration model and the prototype

software (Whitten et aL, 2001). The framework

selected for this research is outlined in Figure 1, which consists of three steps with interlinked

inputs and outputs.

2. 1 Requirements Analysis

There are three types of requirements which

were identified for developing the cost

integration model. These are cost estimation

software requirements, cost control software

requirements and the requirements for their integration. For this purpose, the existing cost estimation and control softwares were explored

to identify their vital attributes which could be

used for integration. Such attributes included the

cost and work activities coding system,

techniques to measure different processes, and

input and output formats.

2.2 Integrated Model Development

The integrated model development begins by

developing the individual data schemas for cost estimation and cost control parts. This is done by

plotting the logical dataflow diagrams (DFD) for each part, which provided a key to integrate both

parts. This process is briefly illustrated in Figure 2.

In the next step, the data requirements of the

integrated cost estimation and control processes

are identified. These data requirements are then

combined to prepare an integrated data model

(i.e. an Entity-Relation (E-R) diagram) which

serves as a basis to construct prototype software.

2.3 System Development and Testing

MS Access''"'*^ is used as commercial-of-the-shelf

tool to develop prototype software using the

integrated model developed in the second step.

After the prototype is created, its testing is conducted to determine any errors, problems and

feedback for improvement.

3. REQUIREMENTS ANALYSIS

3.1 Coding System

CSI MASTERFORMAT is used for cost estimation and control coding which assigns a

specific activity id to each individual activity

(O'Connor, and Caraway, 1993). The activity id

is divided into 4 parts: l_id, 2_id, 3_id, and

item_id representing major item, minor item,

type of construction and the location. For

example, activity id 03 010 020 001 shows

formwork and support for concrete columns in the first floor of the building.

3.2 Cost Estimation and Control Processes

Cost estimation includes estimates for materials,

labor, equipment and subcontracts. For the sake

of simplicity, lump sum contract is used in this study. Therefore, the format of estimating model

consists of work package cost plus markup and

overhead as a percentage of total work packages

cost for overall project.

The cost control model is based on the earned

value concept, consisting of three elements:

actual cost of work performed (ACWP),

budgeted cost of work performed (BCWP) and

budgeted cost of work scheduled (BCWS).

ACWP for material = total amount paid for

materials in a work package

ACWP for labor = total amount paid to labor for a work package

ACWP for equipment = total amount paid for

equipment assigned to a work package

BCWP for material, labor or equipment =

percent work progress multiplied by total cost of

labor or equipment or material in a work

package

BCWS for material, labor or equipment = total estimated cost for labor, equipment, or material

at the control time.

On the basis of these parameters, cost variances

and schedule variances are calculated to

130
determine work productivity which is used to measure the rate of work progress.

3.3 Input and Output Formats

The inputs for the system are the quantities of

work packages, unit prices, work schedule and

the daily progress data. The output will be cost estimates and cost control reports for overall or any specific part of the project.

4. MODEL DEVLOPMENT

4. 1 Dataflow Diagrams

One basic requirement in the integrated cost estimation and cost control model is that the

estimation data should be automatically

transferred to the control part. Keeping this condition in mind, the logical data flow

diagrams for both parts are designed. The logical

dataflow diagram depicts how the system

behaves without any physical implementation

and provides a great tool in developing an

information system.

Figure 3 illustrates the dataflow diagram (DFD)

for estimation part. The 3-D rectangular boxes

show the external agents which interacts with

the system and provide necessary inputs. These

inputs are then passed to different processes

labeled in the logical order. Each process is linked with a certain database to store and/or

retrieve the information. The most important

process in the estimation DFD is process no. 3 which prepares the cost estimation sheet for

material, labor, equipment and subcontracts.

This estimation sheet which is developed

before the construction stage of the project life cycle is used during the construction stage as a

reference of cost. Therefore, the estimation sheet

is combined with the project scheduling in order

to track down the costs on daily basis.

Similarly, figure 4 shows the DFD for the cost

control part. The major input is coming from the

process no. 3 (i.e. estimation sheet) which is linked to the process no. 7 to map estimation

part with the project schedule. The labor time

card is used to assess the actual work of an employee for a work package. The labor time

card combined with the labor unit price from the

estimate storage (storage no. 8.0) will produce

actual labor cost of work performed

(ALCWP), i.e. storage no.9.0.

The material card is used to assess the amount of

material used for each work package on site. The

material card combined with the material unit

price from the estimate storage (storage no. 8.0)

will produce an actual material cost of work

performed (AMCWP), storage no. 10.0.

Actual equipment cost is similarly calculated

from the equipment time card data which is collected from the site combined with the

equipment unit price from the estimate storage

(storage no. 8.0). However, the equipment idle cost should also be considered by calculating the

type of equipment which is not used on that day

(storage no.23). The cost of idle equipment will not be used directly in the work package, but it will be added in the calculations of cost variance

for total project cost.

The ACWP of material, labor, and equipment

will be used to find respective cost variances for

each work package performed. This task can be

achieved by combining the ACWP for material,

labor, and equipment with the budgeted cost of

work performed (storage no. 12, 13, and 14).

The budgeted cost of work performed can be

calculated by combining the quantity of work

done and the unit price of material, labor and

equipment from the estimate storage (process

no. 11).

Finally, the cost variance for complete project can be found by combining the equipment idle cost (storage no.23) with the cumulative of cost variance for material, labor and equipment for the total work package done (storage no. 15, 16,

and 17). The cost variance for total project is represented as process no. 18 in Figure 4.

For the purpose of using the cost control data for

future projects, a database of labor and

equipment productivity is developed. The labor

productivity (process no.20) can be assessed

from the actual labor cost of work performed

storage (storage no. 9) multiplied with the

131
quantity done, and labor unit price from the

estimate storage (storage no. 8.0). The

productivity of equipment (process no. 21) can be assessed in the same way as labor.

The material waste is also considered for the

future project estimation. The material waste

could help the future estimator to estimate the

waste of materials for a certain work package more accurately. The material waste (process no. 22) can be assessed from the actual material cost of work performed (storage no. 10) combined

with quantity take off, material unit price, and

conversion of material unit from the estimate

data stored in estimate storage (storage no. 8.0)

4.2 Data Model

Based on the data needs as ascertained in the

DFD's, a data model is prepared using the

relation database concept as shown in Figure 5. The data model is normalized to the 3'^'* degree to increase the processing speed of the prototype

software.

5. SYSTEM DEVELOPMENT AND TESTING

Among the different commercial off-the-shelf

softwares, MS AccessTM is selected due to its user friendliness, cheap cost and easy

availability. As a first step in prototype software

development, data Tables are designed for

material, labor, equipment, subcontracts and

work progress. This was followed by Query

design to establish the relations between

different entities. Each process (as shown in Figures 3-4) is interpreted in the form of Macros

and finally Forms are designed to get input and

generate reports.

After development, the prototype software is tested on a number of projects to identify any

errors and deficiencies (the software results are compared with the manual calculations). This

process is repeated until no significant problems

are found.

6. CONCLUSIONS

The purpose of integrating the cost estimation

and cost control is achieved by using the

relational database management system in Microsoft Access. Such integration enables the

transfer of cost estimation data automatically to the cost control process. Therefore, complete

information regarding the cost status of the project can be accessed at any time. The system

provides different tools for controlling the

project cost such as productivity data of

equipment & labor, and materials waste data. Such information can enable the management to take preventive actions to control the total project costs. The productivity and materials

waste data can also be used to prepare estimates

for future projects.

7. RECOMMENDATIONS

The integrated cost estimation and control

system in this study is designed for lump sum

contract projects. There is a need to extend it for

different contract types and enhance its usability

for multitasks environment.

8. ACKNOWLEDGEMENT

The fundamental concept of this study is taken

from the class lecture notes (Information

Technology in Construction) of Dr. Chotchai

Charoenngam, Associate Professor, Asian

Institute of Technology, Bangkok, Thailand.

9. REFERENCES

Cagle, R. F., 1991. Implementing an Owner's

Cost Control System, AACE Transactions, O.7.

Kibler, B. E., 1992. Integrated Cost and

Schedule Control: a piece of cake. Cost

Engineering, Vol. 34, No. 7

Lorenzoni, D.C., and Clark, F.D., 1997. Applied

Cost Engineering, ^'^ edition. Marcel Dekker,

Inc., USA.

O'Connor, J.T., Caraway, P.H., 1993. Need for

Specification Format That Accommodated

Engineered Projects, Journal of Construction

Engineering and Management, Vol.1 19, No.4

Whitten, L.J.; Bentley, L.D.; and Dittman, K.C.,

2001. Systems Analysis and Design Methods,

McGraw-Hill Higher Education, USA.

132
PROCESS ^

OUTPUTjii

I. CuiTcni Practices of . aod

f cost estimation K

Dd cost control \ Requirements analy;

2- Cost esiimatton

tables

3 Costconot)! tables

OUTPUT 1

Important attributes of integration

Model Development ^ \^

1 . Design of database :

2. Construction of prototype | y

OUTPUT 2

Integration of Cost

Estimation and Cost

Control Tables

Output 2 System Development and

Testing ^

^^

Revl5lon and Enhancement

Feedback for Improvement

Cost

Softwve

CcMt

Figure 2. Integrated cost estimation and cost control model development concept

Figure 1 . Basic framework to develop an integrated cost estimation and control system

Project _

Docu men ts

-standard Foiii at

1.0

Generate Work Item

List

1.0 Standard Fomna

Project

Information 2.0

Project Information

-Project DocumentsProject

Client

2.0

Quantity Takeoff

Run

Extension

Quantified

Worit Items

Work Item List

1 Formula

4.0 Formula

Subcontractors

5.0 Price List Price Data Document

4.0

Add

enei Overhead

5.0

Add

Markups

6.0 General Overheads

Suppliers

Genera] Overheads Estimate Management

Marlojps 1

7.0 Markups

Total -Projed—

Costs

6.0

Prepare

Reports

Figure 3. Data flow diagram for cost estimation

133
134
Automated DSS for Lighting Design of Nighttime Operations in Highway Construction

Projects

by

Khaled El-Rayes^ and KhaHed Hyari^

' Assistant Professor, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana,

IL 61801 Telephone: (217) 265 0557, Email; elrayes@uiuc.edu, http://cee.ce.uiuc.edu/elrayes

' Graduate Research Assistant, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign,

Urbana, IL 61801 Telephone: (217) 265 5215, Email: hyari@.uiuc.edu

ABSTRACT: Nighttime construction lighting is reported to be a crucial factor affecting quality, safety, cost and

productivity of nighttiine construction projects. This paper presents an automated decision support system (DSS) for

lighting design in highway nighttime construction projects. The DSS is designed to optimize four major objectives:

(1) maximizing average illuminance; (2) maximizing lighting uniformity in the work zone; (3) minimizing glare

produced by the lighting system; and (4) minimizing cost of the Ughting system. Seven decision variables are optimized in this Ughting design problem namely: (1) lighting equipment selection; (2) type of lamps; (3) lamp

lumen output; (4) mounting height; (5) lighting towers positioning; (6) luminaires aiming angle; and (7) lighting towers rotation. A multi objective evolutionary algorithm (NSGA-II) is used to optimize this lighting design

problem. The proposed DSS provides a practical tool for the design and optimization of lighting arrangements in nighttime construction operations.

KEYWORDS: highway construction; lighting; nighttime construction; optimization.

1. INTRODUCTION

An increasing number of highway construction

and repair projects throughout the United States are being performed during the off-peak

nighttime hours to alleviate construction-related

traffic congestions. The use of nighttime

operations in highways construction and repair

projects is reported to provide many advantages

including: ( 1

) reduced impact on the traveling

public through reducing congestions and

motorist delay; (2) decreased project duration

(Hancher and Taylor, 2001); (3) minimized

adverse economic impacts of traffic congestion on local commerce particularly for shipping and

delivery services; (4) decreased pollution from

idling vehicles stopped at construction sites (McCall, 1999); (5) improved work-zone

conditions as the smaller amount of traffic at night creates an opportunity to enlarge work

zones allowing the concurrent performance of

multiple functions; (6) longer working hours at night; (7) enhanced work conditions due to

lower temperatures (Shepard and Cottrell,

1985); (8) faster delivery of material to and from

the work zone since traffic conditions are better

at night, leading to less idle time for both labor

and equipment (Price, 1986); and (9) reduced

equipment costs (Hancher and Taylor, 2001).

Despite the above advantages, nighttime

construction suffers from a number of

disadvantages including: (1) decreased visibility

for both workers and motorist, causing

decreased levels of safety and quality (Shepard

and Cottrell, 1985; Hancher and Taylor, 2001);

(2) problems in implementing quality control

procedures, and decreased quality of

workmanship; (3) increased number of drivers

with insufficient sleep, vision problems and

intoxication during nighttime leading to higher

numbers of accidents at work zones; (4) adverse

public reactions due to construction noise during

nighttime; (5) difficulty in recruiting personnel

in spite of the wage premiums that compensate

for nighttime work; (6) difficulties in material

delivery, utility services and urgent equipment

repairs during nighttime hours (Shepard and

135
Cottrell, 1985); and (7) increase in cost for nighttime operations due to labor premiums and

overtime, additional traffic control devices,

additional artificial lighting arrangements, and

higher engineering inspection costs (Hinze and

Carlisle, 1990)

To overcome many of the above disadvantages,

proper and adequate lighting arrangements need

to be provided on nighttime construction sites. Lighting was reported to be one of the most

important factors affecting quality, safety, cost and productivity of nighttime construction

projects (Kumar, 1994). The design of lighting

arrangements needs to be performed in a systematic and optimal way to achieve the best use of available lighting equipment. The

dynamic nature of nighttime highway

construction and maintenance projects in terms

of variability of work zone locations and layouts

within the same project requires an automated

decision support system (DSS) that copes with

these dynamic design aspects.

This paper presents an automated decision

support system for the design of temporary

lighting arrangements in nighttime highway

construction operations. The system provides

support for highway contractors and resident

engineers in optimizing lighting design for

nighttime construction. It is designed and

developed to be (1) effective in providing near optimal solutions to the lighting arrangements;

and (2) efficient in generating the required

design in a reasonable time and effort due to the

temporary nature of such lighting arrangements.

2. PROPOSED DECISION SUPPORT

SYSTEM

The development of the system is attained

through three main stages: 1) determining the

design variables and constraints pertinent to the

nighttime construction lighting arrangements; 2)

identifying the objectives of the lighting design

in highway nighttime construction and

formulating them in a robust optimization

model; and 3) implementing the optimization

model using a multiobjective evolutionary

algorithm.

2. 1 Decision Variables

The following decision variables were identified

for the lighting design in nighttime construction:

• Lighting equipment selection : The designer

needs to choose from available alternatives

of (a) ground mounted towers, (b) trailer mounted towers, and/or (c) equipment

mounted luminaires.

• Types of luminaires : The type of lamp needs

to be selected from available alternatives of: (a) metal halide lamps; (b) high pressure

sodium vapor lamps; (c) halogen lamps and

(d) low pressure sodium vapor lamps.

• Lamp lumen output : It represents the energy

emitted from the lamp and influence visual

comfort and illuminance (lESNA, 1998).

• Mounting height: It represents the vertical distance between the center of the

luminaires and the pavement surface. Portable lighting towers are typically

manufactured with adjustable mounting

heights that can reach up to 25m.

• Lighting towers positioning: This variable

represents the location of the lighting towers

in the work zone. Lighting positioning

affects the average illuminance and the

uniformity of lighting in the work zone.

• Aiming angle of luminaires : It is the angle

between the center of the luminaires beam

spread and the nadir. This variable

determines the directional distribution of

lighting and affects the coverage area as well as the glare produced by the luminaires.

• Lighting tower rotations : This variable

represents the rotation of the lighting tower

luminaires around a vertical axis, which is needed, as a decision variable when the

luminaires light distribution is not symmetrical. A proper rotation angle

enables the designer to direct the lighting

intensity towards the intended area and to minimize the lighting spillage to unnecessary directions, reducing light

trespass that is a common source of

complaints in nighttime construction in urban areas.

136
2.2 Lighting Design Objectives 2.3 System Implementation

The design of lighting arrangement in nighttime

construction operations should satisfy the

following objectives:

• Illuminance: The lighting system needs to maximize the average illuminance level in the construction work zone. An objective

function was formulated using the point-bypoint method to calculate the average

horizontal illuminance in a grid of uniformly

distributed points covering the work zone

area. The horizontal illuminance at each

point of the grid is calculated using the

inverse square law (Pritchard, 1995)

considering all light sources in the work

zone.

• Uniformity ratio: The uniformity ratio needs

to be minimized in order to ensure that light

evenly reaches all areas in the work zone. This value is computed by dividing the

average horizontal illuminance value over

the minimum illuminance computed at any

grid point in the work zone.

• Glare: Glare needs to be minimized in order

to limit the visual impairments and/or

discomfort experienced by the traveling

public and workers. The veiling luminance

ratio is used in road lighting as a control measure of glare (lESNA, 2000). The

veiling luminance calculations in this model

are formulated by adopting the same

standard conditions for observer's sight

direction and angles that are used in roadway lighting design due to the similarity

of both cases. The observer's eye height is taken to be 1.45 m, and the observation

direction is the drivers' sight direction,

which is parallel to the centerline of the

roadway (lESNA, 2000).

• Lighting cost : The cost of a lighting system

can be reduced by minimizing two major

cost items: (a) ownership cost of the lighting

equipment, which is either the cost to buy,

rent, or lease the lighting equipment, and (b)

operational cost of the lighting equipment,

which is a function of the energy

consumption of the lighting equipment.

The proposed optimization model was

implemented using NSGA-II, which is an improved version of NSGA, referred to as the

fast elitist nondominated sorted genetic

algorithm (Deb et. al., 2000). NSGA-II is a pareto-based approach that handles

multiobjective optimization problems through

the nondomination concept.

Many engineering design problems involve

multiple objectives. Typically, engineering

design problems have at least two objectives: the

cost of the designed system that should be

minimized, and a certain quality characteristics or utility from the system which should be

maximized. While the single objective design

formulation finds the best possible design

solution that corresponds to the minimum or maximum value of the objective function, there

is no single best solution in the multiobjective

design. Rather we have a set of trade-off

solutions generally known as the pareto optimal

solutions or nondominated solutions (Deb et. al., 2000).

Genetic algorithms (GAs) are search and

optimization tool inspired by the mechanics of

natural selection and genetics. Those algorithms

adopt the survival of the fittest, and the

structured exchange of genetic materials among

population members over successive generations

as a basic mechanism for the search process

(Goldberg, 1989). Since its development, GAs

have been widely used in various disciplines

including engineering, science, business, and

medicine (Chambers, 2001). The success of GAs

in these fields can be attributed to their broad

applicability in terms of their ability to handle

various types of functions and to find global near optimal solutions in a multimodal search

space (Deb, 1999).

Several approaches can be used to handle

multiobjective optimization problems including:

(1) weighted sum method; (2) goal programming

approach; (3) constraint method; (4)

lexicographic ordering method; (5) game theory

approach; (6) gender-based GA; (7) multiple

objective GA; and (8) non-dominated sorted GA

137
(NSGA, NSGA-II) (Coello, 1999; Deb et al., 2000).

The proposed optimization model was

implemented using NSGA-II due to its superiority over other multiobjective

optimization tools in (1) providing the entire

pareto optimal front of nondominated solutions

in a single run; and (2) handling any number of

objectives (Deb et ai, 2000). NSGA-II works by

sorting the population members at each

generation into sets of nondominated pareto

optimal fronts. All points in each of the pareto

optimal fronts are given the same fitness value

according to their rank and solutions with higher

rank have higher probability of being selected

for reproduction (Deb et ai, 2000).

The optimization model was coded using C-1-+ language to enable the evaluation of the

formulated objective functions for a given set of

decision variables. As shown in Figure 1, four

functions were developed to calculate

illuminance, uniformity ratio, glare, and cost to enable their evaluation in the optimization

model. The photometric characteristics of the

lighting tower luminaires (light distribution and

lamp lumen output, and the reflectance

characteristics of the pavement surface are entered as data files that can be accessed by

these functions. Other decision variables such as number and position of lighting equipment,

luminaires aiming angle, rotation, and mounting

height are randomly generated for the initial population.

This initial population evolves over a number of

specified generations in order to obtain a number

of feasible solutions that are considered to be

nondominated. The decision maker can select one solution for implementation from these sets to satisfy the particular design problem at hand.

3. APPLICATION EXAMPLE

An application example of lighting design for a work zone with a length of 27 meters, and a width of 10 meters is analyzed to illustrate the use of the proposed system. The design criteria

in this example are specified to be: (1) a minimum average illuminance level of 100 lux

to provide acceptable visibility for the

construction activities in the work zone; (2) a maximum average illuminance of 200 lux to avoid light trespass to adjacent properties; (3) a maximum allowed uniformity ratio of 6; and (4) a maximum allowed glare (veiling luminance

ratio) of 0.4.

Several runs were performed with different

genetic algorithm parameters to study their effect on the convergence characteristics of the

model. The output of the model in each run was

a set of nondominated solutions that satisfy the

earlier described four design objectives. The

solution space is a four-dimensional one, which

makes the pareto optimal front for all functions

impossible to view simultaneously. Twodimensional slices from the pareto optimal front are therefore obtained to visualize the trade-offs

between the different objectives. These slices present subsets of the nondominated solutions

that represent the pareto optimal fronts

. considering two objective functions at a time.

Six fronts are obtained for each run. For

example. Figure 2 shows the trade-off between

illuminance and glare/veiling luminance ratio objectives.

It can be recognized from the nondominated

fronts that both objectives are conflicting, and an

increase in the fitness of one function will lead

to a reduction in the fitness values of the other. The shape of the nondominated fronts in terms of slopes provides insight on the nature of the trade-offs between different objectives. The

designer can select a solution that produces low

glare while making only a small compromise in illuminance.

Almost all fronts obtained from different runs have roughly the same shape, as shown in Figure

3. These fronts however have different

properties in terms of their spread, and the

values of the objective functions. It was also

observed that the population size has a more

important role in determining the quality of the

obtained front than the number of generations as shown in Figure 3. The results obtained from the run that has a population size of 250 and 50

generations are better than the results obtained

from the run that has a population size of 50 and

250 generations because the nondominated

138
fronts in the former case have a better spread over the entire front, and also have better fitness values.

From the above analysis, one can see that it is possible to reduce the computational

requirements of the lighting model, if the

accompanying reduction in the fitness values of

the objective functions is acceptable. It seems

that the run with population size of 250 and 50

generations gave acceptable results with respect

to the best run with a population size of 800 and

234 generations. The number of function

evaluations in the former case with a reduced

population size and reduced number of

generations is less than 7% of the number of

function evaluations in the run with a population

size of 800 and 234 generations.

4. CONCLUSIONS

The results presented in this paper illustrates the

capability of the proposed decision support

system in: ( 1 ) handling multiobjectives in lighting design process simultaneously; (2)

providing feasible solutions by satisfying the

design criteria; (3) achieving good quality in lighting design rather than accepting the

minimum requirements; (4) quantifying glare

which is a major source of complaints in highway nighttime construction; (5)

incorporating cost as an important objective in the optimization of the lighting design process;

and (6) providing an automated and practical

tool for the nighttime construction operations

personnel to deal with the dynamic lighting

design process.

5. REFERENCES

1 . Chambers, L. (Editor) (200 1 ) "The Practical

Handbook of Genetic Algorithms

Applications". 2001. Chapman and

Hall/CRD. Florida.

2. Coello, C. ( 1999) "A Comprehensive

Survey of Evolutionary-Based Multi

objective Optimization Techniques".

Laboratorio Nacional de Informatica

Avanzada. Veracruz, Mexico.

http://www.lania.mx/~ccoello

3. Deb, Kalyanmoy et. al. (2000) "A Fast

Elitist Non- dominated sorting genetic

algorithm for multi-objective optimization:

NSGA-H". Proceedings of the Parallel Problem Solving from Nature VI

Conference, 16-20 September, Paris.

4. Deb, Kalyanmoy. (1999) "Evolutionary

Algorithms for Multi-Criterion Optimization

in Engineering Design". Proceedings of

Evolutionary Algorithms in Engineering and

Computer Science (EUROGEN-99).

5. Goldberg, D. (1989) Genetic Algorithms in Search, Optimization, and Machine

Learning. Addison Wesley Longman, Inc.

6. Rancher, D. , and Taylor, T. ( 200 1 ) "NightTime Construction Issues" Paper presented

at the Transportation Research Board 80th

Annual Meeting, January 7-11.

7. Hinze, J., and Carlisle, D. ( 1990) "Variables

Impacted by Nighttime Construction

Projects", Final Report TNW 90-07,

Transportation Northwest, University of

Washington, Seattle.

8. lESNA (2000) "lESNA Practice for

Roadway Lighting". American National

Standard / Illuminating Engineering Society

of North America ANSI/IESNA RP-8-00.

2000 USA.

9. lESNA ( 1998)."IESNA Guide for Choosing

Light Sources for General Lighting". Report

DG- 10-98. Illumination Engineering Society

of North America 1998. New York.

10. Kumar, A. (1994) "Development of a Model

for Determining Work Zone Illumination

Requirements During Nighttime Highway

Construction " PH.D Dissertation University

of Florida.

11. McCall, H. C. (1999). "Report on the

Department of Transportation's

Administration of the Nighttime

Construction Program", Report 98-S-50,

State of New York Office of the State Comptroller.

12. Pritchard, D.C (1995) Lighting, 5th Ed.,

Longman Scientific and Technical, Burnt

Mill, Harlow, Essex.

139
13. Price, D. A. (1986) " Nighttime Paving",

Implementation Report CDOH/DTP/R-86/6,

Colorado Dept. of Highways, Denver,

Federal Highway Administration, April.

1986.

14. Shepard, F.D. and Cottrel, B (1985)

"Benefits And Safety Impact of Night

Work-Zone Activities", Report No.

FHWA/RD-85/067, U.S. Department of

Transportation, Federal Highway

Administration, June 1985.

Input No. of Generations (Ni. Population Size. Prob. Of

Crossover. Prob. Of Mutation

liiitiabze Population

First Generation n=l

Luminaries

Photometric / Chaiacterislics

\ Data

Evaluate Fitness

Function Evaluation Programs (Illuminance. Uniformity Ratio. Veiling Luminance, and Glare)

Sort Population

Calculate Crowdiiig

Calculate Constraints Violation

Pavement

Reflectance

| Characteristics

'

Data

Select Population

Perform Crossover and Mutation

Create Child Population

Evaluate Fitness of Child Population

Combine Child and Parents Population

Sort Combined Population

Select Parents Population for Next Generation

Next Generation

( End~)

Figure 1. Lighting Design and Optimization

Model

0.4

0.3

^ 0.2 O

0.1

1 N: Population size 9

1

1

1

1

1

1

1 ^ ^

100 150 200

Illuminance (lux) N = 100 -.•--N = 200 _^_N=400

...A-- - N = 800 -.0-. N = 50

Figure 2. Illuminance / glare trade-off

(0 CE

E)_o

'c

Z)

6

5

4

3

2

1

N: Population size

t: Number of generations

/

1 00 1 50 200

Illuminance (lux)

-o N= ICQ, t= 250

-A N = 250, t = 25

-o - -

. N = 250, t = 50

A N = 50, t = 250 -•— N = 800, t = 234

Figure 3. Illuminance / uniformity ratio trade-off

140
SESSION 3

DESIGN PRACTICES TO

FACILITATE CONSTRUCTION

AUTOMATION

141

De Bolder, an unusual example of off-site construction

by

Ger Maas, Bert van Eekelen

ABSTRACT:

De Bolder ('The Bollard") is a 42.5 metre-high building with a circular cross-section of 30 metres and

a weight of 25,000 KN. It was built in an industrial plant, transported a considerable distance across

water, subsequently put ashore and placed on a foundation.

This study focuses on the differences in construction methods and the consequences of these

differences.

Research aim: How can the De Bolder study results be used to improve traditional construction

techniques?

Research questions: What are the differences between construction of De Bolder and construction on a

traditional site? Where do these differences stem from? To what extent do these differences impact the

actual construction period?

Results: use of this method depends on the characteristics of the object (volume, design and weight)

and circumstantial attributes (transportability). The dynamics of transport determine the building's

design; planning of an off-site construction process entails other dependencies, such as blurring of the

distinction between structural works and finishing works.

KEY WORDS:

Building systems, industrialised construction, integrated product and process design, transport of

building.

1. INTRODUCTION: 1.2 The design

This is a project involving the construction of a new Headquarters for the Mammoet Van

Seumerengroep in Schiedam, the Netherlands, an organisation known throughout the world

for its unique achievements in the offshore

industry and the associated heavy transport

operations. In 2001, the company successfully

raised the Russian submarine Kursk, an

operation considered impossible by many.

1.1 The initiators The building was to be designed in the form of

a bollard. It was to be a compact, tenstorey

construction with a cylinder-shaped building

volume, which, by reason of its constricted

shape, resembled a bollard. The building is situated on the axis of the Benelux tunnel, the route of the A4 motorway under the river

Meuse (the Rotterdam harbour), which makes

it visible from a long way off by the 150,000

motorists who travel along this motorway each

day.

Eindhoven University of Technology. Faculty of Building,

Architecture and Planning, Postbus 513, NL 5600 MB Eindhoven, The Netherlands g.i.niaa5@bwk.tuc.nl

143
The building's compact bollard shape made it ideal for transporting. Because of the

production capacity at Grootint Zwijndrecht -

one of the subsidiaries of the Seumerengroep

where oil platforms are made - the idea was

conceived of constructing this building in the

industrial plant in Zwijndrecht and transporting

it by water to its ultimate location in Schiedam.

Figure 1 De Bolder under construction in the

industrial plant

The project has the following characteristics:

diameter: approx. 30 metres; height: 42.5

metres; mass: 25,000 KN; transport distance

by water: 25 km; over land: 300 metres; method of transport: self-driven platform

trailers and seagoing pontoons; largest

obstacle: the Botlekbrug bridge with a maximum headroom of 45.7 metres at lowest

possible water level; construction period

(superstructure): mid-July 2001 to 29 January

2002.

As there was no experience with the

prefabrication of this type of office building,

the decision was taken to develop this innovative industrialised construction method

parallel to a building to be constructed using

traditional techniques.

This meant that it had to be possible to build

the structure along traditional lines and also in such a way that it could be transported. This

applied to all aspects of the construction, i.e.

functional and spatial development, intended

constructional and installation technologies, as well as other specific structural details and

dimensioning.

As a result, the building differs only slightly

from traditional structures, with the exception

of a few components. It may be assumed that it

is possible to optimise the construction yet

further if the transportable variant is opted for

at an earlier stage. On the other hand, limiting

the project by allowing for both options did

result in an explicit focus on specific aspects

such as planning effects and specific

circumstances on the construction site, without

these aspects being related to a very different

building concept. To all intents and purposes,

De Bolder is a traditional structure, but one

built under industrialised circumstances in a factory setting, and one that could be

transported.

2. RESEARCH QUESTIONS

• What are the differences between

construction of De Bolder and

construction on a traditional site? • Where do these differences stem from?

• To what extent do these differences

impact construction time?

• How do the separate building activities relate to one another?

• How can the results of the research

into this type of conditioned

construction work be used to improve

current construction processes?

3. RESEARCH METHOD

3.1 Research limitations

Research work was carried out between

November 2001 and June 2002.

When the study started, the project was already

at its final completion stage. Apart from the

fact that the outside walls had not yet been

sealed off, it was not immediately possible to see that this building had been factory-built.

Nor was it possible during construction to identify and measure productivity or failure costs and to compare these with standard times

144
or costs of traditional structures cited in the

relevant literature.

3.2 Research approach

This study was conducted by reconstructing

the preparation and construction processes as

faithfully as possible. By collecting data and

conducting interviews with people directly

involved in the construction work, it was

possible to paint a picture of the way in which

preparations and actual construction work had

been carried out. Of particular interest were the

decisions taken and the criteria and

considerations leading up to them. This

reconstruction was compared to the common

Dutch construction methods. Traditionally

prefabrication is limited to certain sections of a

building.

4. THE RESULTS

4. 1 Planning

4.1.1 Introduction

An important difference between traditional

techniques and those used in the construction

of De Bolder is the drastic reduction in building time. Despite the time required for

transport, a net time gain of 22 weeks was

made. The difference in construction time is made up as follows:

1 . Work under industrial circumstances

(- 6 weeks)

2. Changes in planning (order and

sequence of building activities)

(-20 weeks)

3. Preparations for transport, transporting

and unloading (+ 4 weeks)

4. 1 .2 Work under industrial circumstances

The fact that works could continue irrespective

of the weather resulted in a direct time gain. A

standard of 29 days on which work is held up

on account of weather conditions applies to

this region of the Netherlands for the duration

of any construction work. This downtime

includes seven working days due to frost, nine

due to rain and eleven due to wind.

Although deviations will, in practice, occur as regards actual weather conditions and there

will be workable days on which weather does

hold up work but only to a certain extent, these

29 days are a generally observed rule. Eliminating downtime not only shortens the

construction period but also does away with

the unpredictability of work during the winter.

Work can be carried out under all circumstances, irrespective of the weather, so

that the work itself and the link between the

project as a whole and the various individual

activities involved (sequence and drying times,

for instance) can be far more strictly planned.

4. 1 .3 Changes in planning

If we compare the planning work of this construction project with those of traditional

projects of the same type and scope, three

aspects among the various activities stand out most.

Firstly, the erection of the supporting structure can start without prior work on the

foundations. The floors in industrial plants

where oil platforms and offshore installations are built have sufficient load-bearing capacity

to support a building of this size. The building

of the eventual foundation for the building can

run parallel to the construction of the upper

structure at the final location, generating a time

gain of eight weeks in this case. A second difference is the direct succession of

structural work and finishing work. At the

completion stage, materials are used that are susceptible to weathering. The building has to be fully glazed before most of the finishing

work can be started, which is why it is usually not worthwhile starting finishing work

immediately after the structural work. In the case of De Bolder, the entire project was both

water and wind 'resistant' from the onset and

conditioned construction was, therefore,

possible. This allows for a direct start of the

finishing work immediately following the

structural work, storey by storey (by tradition,

the building was built up from the bottom).

Although, as far as safety was concerned,

various incompatible activities were being

conducted at the same time, conditioned

circumstances on the construction site made it possible to keep this under control by working

145
with two separate construction teams

different shifts throughout the critical period.

m

The third difference hes in the timely

installation of costly equipment. As a rule, the

building should be appropriately sealed off

before costly equipment such as air conditioning and telecommunication systems

and ICT networks are installed. Especially

users equipment is often put off until after final acceptance. The result is that shafts and

ceilings have to be reopened. In the case of De

Bolder, facilities such as those mentioned

above were assembled and installed in good

time, seeing as the risk of theft or vandalism was virtually eliminated. The above two

differences resulted in a time gain of twelve

weeks; this does not include the time gained

after completion once the end users started moving in. The total time gain of the three

mentioned differences is 8 + 12 = 20 months.

4.1.4 Productivity

Finally, we must mention a further key factor,

which we have not been able to explore in greater detail: actual productivity during

construction work. Various factors play a part, for instance the extent to which activities can be planned, whether they can be physically

prepared, the logistic advantages of an

industrial setting (both material advantages and

advantages as regards the information flow),

and matters relating to motivation of the

employees on the job.

Previous analyses have shown that improvements to circumstances on the

construction site can lead to a dramatic

increase in the productivity of construction

workers, from 50% to 75% of the available

working hours. This may be even more in an

industrial production setting such as the one

used for De Bolder. On the other hand, the

consequence of adapting this kind of building

structure to an industrial setting in which high

safety requirements and stricter procedures

apply for working on offshore installations

may also have a decelerating effect. We recommend that further case studies

investigate productivity more thoroughly, as

this can lead to new findings of pracfical use to more tradifional building methods.

Figure 2 De Bolder on the transition structure

4.2 Design and choice of materials

Design requirements, weight and deformations

have to be taken into account to make the

fransport of a structure possible, in fact the

specific fransport modalifies have to be taken

into account as early as the initial design stage.

Vehicles bear the weight of the structure during fransport; in the case of De Bolder these were what are known as self-steering platform

frailers commonly used in the offshore

industry.

Complete oil platforms and complex

installations are built in factory sheds and

fransported to the wharf on such vehicles. This was also done with De Bolder. The number of

vehicles is, in theory, infinite - the weight to be carried is limited only by the axle loadbearing capacity.

UNLS KAWAG KAirCRM TRAILER VZ-fiH POWEPPACK

1 A /

Figure 3 The platform trailers

The ground plan of De Bolder specified a maximum weight of 2,5000 KN. This meant

that, compared to the usual construction

method, the weight of this building with its nine office levels had to be reduced.

Monolithic inner leaves and floors are

146
generally used in buildings such as these, the

decisive factors being ease of realisation as well as cost reduction. By opting for more

expensive composite floor slabs and inner

leaves with a wood frame construction, it was

possible to reduce the weight of the building

by 20%.

Design factors are likewise important, which is why the office-dividing partitions were not erected until after transport. Although weight can be distributed across several platform

trailers, the structure should be such that it is possible to transport it without running the risk of major deformations. For the offshore

industry this means that the load is always

grouped in such a way that three ultimate

bearings are created, so that deformations and

leaning during transport can be checked and

managed.

Traditional structures always transfer their own

weight and utilisation load to the foundation

construction, following a logical grid. In the case of a building that is to be transported, that load has fu-st to be redirected to three bearings

and then redistributed over the several axles.

In practice, therefore, this means that a

transition structure is required for the

substructure of the building, something not

usually found in traditional structures.The

transition construction can be part of the

building's own structural framework or made

as a temporary structure; the latter was opted

for in the case of De Bolder.

It is, in any case, evident that both the

transportable designs of the structure and the

structural features this requires have to be

taken into account as early as the initial design

stage.

4.3 Costs

De Bolder has been built at a cost akin to that of a traditional building. This does require some comment, however. There was access to an industrial plant of sufficient size and loadbearing capacity and with all the necessary

amenities. Transport facilities were also

available and hardly any equipment needed to be bought specially for this project.

Given the overall cost of the project, the

transport costs were by no means the heaviest.

These amounted to EUR 113,250 i.e. the sum

of the costs for the platform trailers plus the

seagoing pontoon.

The costs for the temporary load-bearing

construction, i.e. the transition construction

that made it possible to carry and transport the

building on the platform trailers, were

significantly higher, viz. EUR 1,250,000. In addition, the wharf at the building's final destination had to be reinforced to receive the

platform trailers, the costs for which came to EUR 50,700.

These excess costs were eventually

compensated by the savings made on

construction time, the reduced risk of theft and

wilful destruction, as well as other economies.

As both the industrial plant and the final location are by the waterside, making transport over land difficult, we investigated to what

extent circumstantial factors have an impact on

the transportability of such buildings. Using an

abridged sensitivity analysis, we found that transport distances, be they by water or over

land, had no profound effect, provided no cost- raising obstacles had to be overcome. Given

the flatness of the land and the abundance of

waterways in the Netherlands, this concept

opens up possibilities for future use.

4.4 Social effects

Cutting back construction times has been an

issue in the Netherlands for some time now.

This can be achieved in a number of ways.

Optimising conditions on construction sites is in itself one way of improving the

predictability and planability of construction

work, thus also avoiding interruptions, loss and

downtime. In that sense, much can learnt from

the factory-based approach used in the

construction of De Bolder. However, there is no need to opt for total prefabrication or

transport of an entire structure.

Yet it would seem that in the Netherlands there

is an increasing shift in the characteristics of

the surroundings in which construction work is carried out, from erecting new buildings in 'green field' sites, i.e. within perimeters, to embedding construction works in existing

147
urban settings, adapted to existing daily

operational activities. Such construction

projects are found in the ever more densely

built-up inner cities, near airports, railway

stations and large complexes such as exhibition sites, educational institutes and

health care institutes. Studies of the effect that the surroundings have on building work in

'revitalisation' areas have shown that disruptions should be kept to a minimum. Not

only that, the nature and duration of such

inconveniences, as well as their predictability are also crucial. The traditional construction

process 'within the perimeters' is not geared to that and numerous practices and sector-specific

improvements in traditional building projects

are inconsistent with environmental

requirements.

It is for that reason in particular that the De

Bolder project has attracted so much attention

from the construction industry as a whole.

5. CONCLUSIONS/LESSONS:

6. REFERENCES

L M.R.Tuinenburg (484176) TU

Eindhoven, Techniek en Maatschappij,

TIB AE, faculteit Technologic

Management: Transportsystemen voor

grote bouwwerken, een casestudy naar

alternatieve weg- en

watertransportsystemen voor "De Bolder"

juni 2002

2^ http://www.staalbouw.nl/invulpaginas/dns

t proi bolder.html

3^ http://www.mammoet.coin/projects/index.

htm

4. http://www.heerema.com/content/hfg/

yards/grootint/projects/bolder.htm

• If a design is suited for off-site production

and transport, there are many advantages

to be gained from alternative construction

process dependencies resulting in disruption-free building with shorter

interfaces and a blurring of the distinction

between structural work and finishing

work.

• The success of De Bolder has established

the efficacy of this technology; its application depends on the volume, design

and weight (object attributes) of the

structure and its transportation capacity

(circumstantial attributes). • The design of such structures depends

largely on dynamic aspects (unusual for buildings), which implies that there are other construction problems that need to be addressed at an earlier stage in the development process.

148
AUTOMATED DATA ACQUISITION AND PLANNING

OF HIGHWAY CONSTRUCTION

by

Ahmed Hassanein^ and Osama Moselhi^

' PhD Candidate, Dept. ofBuilding, Civil and Environmental Engineering

Concordia University, Montreal, Quebec

hass @alcor. Concordia, ca

" Prof, and Chair, Dept. of Building, Civil and Environmental Engineering

Concordia University, Montreal, Quebec

moselhi @cbs-engr.concordia.ca

ABSTRACT: This paper briefly describes a model, designed to automate data acquisition and

analysis for planning and scheduhng highway construction projects. The paper briefly describes

the proposed model, and focuses primarily on its automation aspects. Geographic information

systems is employed to analyze spatial data and estimate cut and fill quantities. The model also

stores activities typically involved in highway construction and automatically generates the precedence network respecting job logic. The model generates digital terrain models to represent the ground topography and underlying soil strata. Transition of soil strata between

borehole locations can either be: 1) automatically generated by the model; or 2) defined by the

user. The model employs the mass haul diagram to develop the optimum earthmoving plan. It accounts for the presence of transverse obstructions, such as rivers and existing highways, when

developing the earthmoving plan and defining project activities. The model is implemented in a prototype software that operates in Microsoft Windows environment. It provides a user-friendly

interface, including menus, dialog windows, and graphical capabilities to expedite data input

and retrieval. Several input and output formats are accepted to facilitate data sharing with

commercially-available software packages.

Keywords: automation; earthmoving; geographic information systems; highway planning

1. INTRODUCTION

Although highway construction projects are

typically large in terms of capital requirements

(Adeli and Karim 1997), little effort was made

to automate the planning stage of this class of

projects. The effort required to develop a competent plan is perceived as a major

obstacle to developing high quality schedules

(Chevallier and Russell 2001). Earlier smdies

(eg. Herbsman 1987; NCHRP 2000) revealed

the dissatisfaction of parties involved in planning and scheduling highway operations

with available planning and scheduling tools. Of these operations, earthmoving operations

generally represent a major bid item, making

their optimization of paramount importance to developing successful bids (Jayawardane and

Harris 1990). Acquiring and analysing spatial

data has been perceived as a time-consuming

process, which is susceptible to certain biases

(Fan et al 2001). Several methods have been

proposed for accurate estimation of cut

quantities (e.g. Siyam 1987; Epps and Corey

1990; Easa 1992). On the other hand,

considerable work has been done to optimize

earthmoving operations (e.g. Stark and Mayer

1983). However, none of these models: 1) provide for automated data entry; 2) account

for the impact of transverse natural and man149
made obstructions on the earthmoving plan; 3)

support three-dimensional visualisation; or 4)

provide scheduling capabilities.

2. PROPOSED MODEL

This paper briefly describes a model designed

to automate the above-mentioned functions,

and focuses primarily on the automation

aspects. Transverse obstructions, such as rivers are considered when developing the workbreakdown structure (WBS). The model stores a list of activities typically encountered in highway construction, and generates the

precedence network respecting the job logic.

Geographic information systems (GIS) is employed to acquire and analyze spatial data

and generate the optimum earthmoving plan

using the mass haul diagram. The model

automatically generates digital terrain models

(DTMs) to represent the original ground

topography and underlying soil strata. When

estimating quantities of cut and fill, the model

accounts for variations in swell and shrinkage

factors of soils of these strata. The model is implemented in a prototype software that operates in Microsoft Windows environment.

It accepts several input formats and provides

graphical and tabular reports.

The model is schematically illustrated in Figure 1. It utilises GIS to acquire and analyze

spatial data. A knowledge base is employed to define the WBS and generate the precedence

network respecting the job logic. Relational

database models store: 1) swell and shrinkage

factors of common soil types; and 2) available resources. Once the WBS and precedence

network have been defined and crews have

been assigned to their respective activities, the

project can be scheduled. In view of the highly

repetitive nature of highway construction, the

scheduling engine employs resource-driven

scheduling. As the figure shows, the model

generates tabular and graphical reports, and

generates the optimum earthmoving plan using

the mass haul diagram. The main functions of

the model are discussed below.

2.1. Data Acquisition and Analysis

Figure 2 illustrates the sequence of operations

to automate data acquisition and analysis. The

model extends the capabilities of the traditional mass haul diagram (Stark and Mayer 1983) to account for: 1) the presence of different soil strata in cut sections; 2) the presence of

transverse natural and/or man-made

obstructions; and 3) varying degrees of soil compaction. The model generates threedimensional DTMs to represent the original

ground topography and underlying soil strata. These DTMs are stored as triangulated

irregular networks (TINs) so as to reduce

demand on the system's memory without

sacrificing accuracy (Oloufa 1991). An

iterative procedure is proposed to generate TIN

nodes along contour Hnes (see Figure 3). Initially, the iteration number (R) and contour

line identifier (L) are initialized to unity. Next,

the node number (i) and distance from start of

contour line (dj) are initialised to unity and

zero, respectively. If (R=l), the distance along

the contour line to the next node, "Dirn", is set equal to the horizontal component of the

perpendicular distance to the nearest contour

line. Otherwise (i.e. R>1), Dirn is reduced to half its value in the previous iteration.

This process is repeated until nodes are generated along the entire length of the contour

line (nested loop 1). The same procedure is applied to generate TIN nodes along remaining

contour lines (nested loop 2) enabling the

generation of a DTM. Next, the volume of soil contained under that DTM, "VoIr", is computed. If (R=l) then "R" is incremented

and the whole process is repeated (loop 1). Otherwise, estimated volumes of soil from the

last two iterations are compared. If the change

in "VoIr" is less than the specified tolerance

(default=15%), then the process is complete.

Otherwise "R" is incremented and the process

is repeated until the required accuracy is attained.

Strata profiles can either be: 1 ) defined by the

user, by specifying the strata connectivity

between boreholes; or 2) automatically

generated by the model, and revised as needed

by the user. In the latter case, each soil layer

in a borehole is assigned a number, "i", that

150
accounts for its sequence from top to bottom,

starting with i=l at ground level. The model

assumes that the assigned number for each

layer can go up or down by one level between

two successive boreholes. If a stratum is not found in neighbouring borehole test results, it

is assumed that the stratum tapers linearly to reach a thickness of zero (0) at the location of

that borehole.

The volume of soil contained between two

successive sections in the highway

embankment is estimated knowing the end

areas and the distance between them. A

modification of the average-end-area method

proposed by Epps and Corey (1990) is employed. The methodology proposed by Easa

(1992) is employed to estimate the volume of

soil contained in curved portions of the

highway embankment. This methodology

requires that end section be simplified, and the

procedure proposed by Easa (1989) is employed for that purpose. The model

automatically determines which sets of

equations to employ when estimating cut and

fill volumes.

2.2. Work-Breakdown Structure

Transverse obstructions, such as rivers and

creeks, play a major role in performing the

WBS (Alkass and Harris 1991). There are two

types of obstructions: 1) surmountable, where

access is granted across the obstruction at an

overhead (time and cost); and 2)

insurmountable, where no access is granted.

Work zones are normally defined based on the

locations of insurmountable obstructions,

while segments are defined based on the

locations of surmountable ones. The model

stores a list of activities typically encountered

in highway construction and divides activities into work packages based on the locations of

transverse obstructions. The resulting WBS is shown in Figure 4.

2.3. Precedence Network

The model automatically generates precedence

networks defining the construction of new

highways, as well as the rehabilitation of

existing ones. Generated precedence networks

are generated detailing operations along the

main project route as well as the construction

of: 1) overpasses; 2) transverse overpasses; and

3) interchanges. The model enables the

selection of any or all of the stored activities,

and the precedence network is generated

accordingly. The model also enables the

definition of additional activities, along with

their precedence relations.

3. COMPUTER IMPLEMENTATION

The proposed model is implemented in a prototype software that operates in Microsoft

Windows. The software: 1) is user-friendly; 2)

generates graphical and tabular output; and 3)

enables data exchange with commercially

available software. It provides an interface

with dialog windows, menus, toolbars and a

status bar. In view of its widespread

acceptance, ArcView GIS (version 3.1) is employed as the GIS engine, while three- dimensional analysis is carried out using

ArcView 3D Analyzer. Microsoft Access is employed as the database management system

(DBMS). The software accepts a wide variety

of input formats, including AutoCAD files, digitized blue prints and GPS data points. It provides three-dimensional visualization of: 1) final highway embankment; 2) ground

topography; and 3) underlying soil strata.

4. SUMMARY AND CONCLUDING

REMARKS

This paper briefly describes a model, designed

to automate: 1) spatial data acquisition; 2) the

generation of the optimum earthmoving plan;

3) the development of the project's workbreakdown structure; and 4) the development

of precedence network respecting planned job

logic. The paper focuses primarily on the

automation aspects of the developed model,

which employs geographic information

systems to compute cut and fill quantities and

generate the optimum earthmoving plan. A

methodology is proposed to generate digital terrain models representing the original ground

terrain and estimate quantities of cut and fill. A

relational database stores swell and shrinkage

151
factors for common soil types, enabling

accurate estimation of soil quantities. The

model accounts for the presence of transverse

obstructions on the work breakdown structure and consequently the proposed earthmoving

plan.

The model is implemented in a prototype

software that operates in Microsoft Windows

environment. The model demonstrates the

potential of GIS as an emerging tool in acquiring and analyzing spatial data. Using the

proposed model can significantly reduce the

time and cost required to plan highway

construction, while enhancing the accuracy of

the developed estimates.

5. REFERENCES

Adeli, H. and Karim, A., 1997,

"Scheduling/Cost Optimization and Neural

Dynamics Model for Construction", Journal of

Construction Engineering and Management,

ASCE, Vol. 123, No. 4, pp. 450-458.

Alkass, S. and Harris, P., 1991, "Development

of an Integrated System for Planning

Earthwork Operations in Road Construction",

Construction Management and Economics, E

& FN Spon, Vol. 9, pp. 263-289.

Chevallier, N. and Russell, A.D., 2001,

"Developing a Draft Schedule Using

Templates and Rules", Journal of Construction

Engineering and Management, ASCE, Vol.

127, No. 5, pp. 391-398.

Easa, S.M., 1989, "Simplifying Roadway

Cross Sections Without Reducing Volume

Accuracy", Canadian Journal of Civil

Engineering, CSCE, Vol. 16, pp. 483-488.

Easa, S.M., 1992, "Estimating Earthwork

Volumes of Curved Roadways: Mathematical

Model", Journal of Transportation

Engineering, ASCE, Vol. 118, No. 6, pp. 834-

849.

Epps, J. and Corey, M., 1990, "Cut and Fill Calculations by Modified Average-End-Area

Method", Journal of Transportation

Engineering, ASCE, Vol. 116, No. 5, pp. 683-

689.

Fan, L., Ho., C. and NG, V., 2001, "A Study of

Quantity Surveyors' Ethical Behaviour",

Construction Management and Economics, E

& FN Spon, Vol. 19, pp. 19-36.

Herbsman, Z.J., 1987, "Evaluation of

Scheduling Techniques for Highway

Construction Projects", Transportation

Research Record 1126, National Research

Council, Washington, D.C., pp. 1 10-120.

Jayawardane, A. and Harris, F., 1990, "Further

Development of Integer Programming in Earthwork Optimization", Journal of

Construction Engineering and Management,

ASCE, Vol. 116, No. 1, pp. 18-34.

NCHRP (National Cooperative Highway

Research Program), 2000, Project

Management Information Systems, Synthesis

of Highway Practice #282, Transportation

Research Board, National Research Council,

National Academy Press, Washington, D.C.

Oloufa, A.A. 1991. "Triangulation

Applications in Volume Calculation", Journal

of Computing in Civil Engineering, ASCE,

Vol. 5, No. l,pp. 103-121.

Siyam, Y.M., 1987, "Precision in CrossSectional Area Calculations on Earthwork

Determination", Journal of Surveying

Engineering, ASCE, Vol. 113, No. 3, pp. 139-

151.

Stark, R.M. and Mayer, R.H., 1983,

Quantitative Construction Management: Uses

of Linear Optimization, John Wiley & Sons,

Inc, New York.

152

I
153
C Start )

Figure 3: Developed algorithm to generate TIN nodes

1 1

! H ! 1 -—r I—HI TT^""\ 1

Figure 4: Proposed WBS

154
ASPHALT QUALITY PARAMETERS TRACABILITY USING ELECTRONIC TAGS

AND GPS

Francois Peyret', Robert. Tasky^

ABSTRACT: This paper begins by

introducing the developmental work carried out within the scope of the OSYRIS project, in the aim of proposing a new IT infrastructure

for road-building sites and by drawing

attention to the need for an electronic

connection between paving operations and the

asphalt mixing plant. The set of system

specifications required to satisfy this connection is then given, along with a state-of- the-art survey. The central section of the paper

presents the proposed solution, which is based on both electronic tagging of the trucks

hauling asphalt and a GPS positioning of the

asphalt pavers. The first experiment conducted

in 2001 is also described and the paper closes

with concluding observations and an outlook.

KEYWORDS: information and

communication technologies, asphalt

fabrication and laying, tracability, electronic

tagging, GPS, quality control.

1 INTRODUCTION

Recent research initiatives, such as the

European project OSYRIS, have been

proposing new IT infrastructure in support of

asphalt laying and compacting operations.

OSYRIS focuses on the laying and compacting

tasks but does not directly address the asphalt

fabrication operation, which proves to be of

greatest importance since this operation serves

to set the quality of the asphalt material that

will constitute the pavement.

Some quality assurance procedures have

already been introduced to monitor and assess

material quality at the plant, yet no direct

connection between fabrication and paving

operations has been established, hence no

direct use can be made of quality assessment at the plant during paving and compaction

processes. The aim of the present research is to create an electronic link in order to fill a major

void in the sequence of electronic monitoring

procedures for road asphalt sites.

2 THE OSYRIS PROJECT

2.1 Key Issues And Philosophy

OSYRIS ("Open System for Road Information

Support") is a European Union-funded project

devoted to developing information

infrastructure for road construction and

maintenance processes [1].

It is intended to enable both contractors and

road owners to generate their own knowledge

bases and quality assurance systems, which are now expected of them given that access to

critical information in real time is one of the

key challenges facing the new century.

The OSYRIS philosophy lies in building

openness and modularity into a system through

use of compliant components. OSYRIS data

storage and management is based on a product

model of the road specially designed to be: compatible with the latest road management

databases, object-oriented, and located within

a 3D geographical reference.

^5//^ Robotics and Positioning Team, LCPC

(Laboratoire Central des Fonts et Chaussees),

Bouguenais, France, francois.peyret@lcpc.fr

^SEMR - CETE Normandie-Centre, Blois, France,

robert. tasky @equipement.gouv.fr

155
The OSYRIS project was launched in February 2000 and will last until the beginning

of 2003. The Consortium partners consist of: the University of Karlsruhe (1MB) - Germany;

LCPC - France; Moba - Germany; Tekla Corp.

- Finland; and Skanska - Sweden. The project

is funded under the European Union Program

"Growth" (Contract No.: GiRD-CT1999-

00080).

2.2 Expected outputs

Four following commercial OSYRIS products

have been foreseen:

OSYRIS Standards: a set of several pre- standards describing the format and

contents of information exchanges taking

place between OSYRIS components,

OSYRIS Machine: a set of on-machine

components developed to fulfil a

contractor's basic needs in supporting

paving and asphalt compaction work, for a

typical asphalt-laying set-up of 1 paver

and 2 rollers,

OSYRIS Machine Extensions: a set of

options to extend the basic OSYRIS

Machine configuration,

OSYRIS Design and Documentation:

consists of a line of software for the

planning, analysis, documentation and

long-term storage of roadwork parameters.

These products are intended primarily for

consultants and road owners.

3 SPECIFICATIONS OF THE MATERIAL

TRACABILITY SYSTEM

3. 1 The Quality Control Chain

Generally speaking, material tracability is to be performed through eight main phases, as follows:

1. Supply of components (aggregates,

binders, etc.) to the asphalt plant

2. Storage of components in piles or tanks

3. Transfer of components from storage

devices to the mixing equipment

4. Fabrication, consisting of component

grading and mixing, and constitution of

material batches

5. Output of material batches from the plant

6. Reception of batches at the asphalt-laying

site

7. Laying of the material

8. Compaction of the material.

This quality control chain contains a major

natural discontinuity: the transport and

delivery of materials from the plant to the

construction site, between phases 5 and 6. This

discontinuity often accounts for lost quantitative and qualitative information and, in some instances, delivery location errors occur. Consequently, it was decided that he system

should be capable of: automatically collecting the most relevant

fabrication-related information from the

plant's existing monitoring and quality

control systems for each batch of material;

automatically downloading this information into a tag mounted on the

truck headed for the paving site, along

with the batch of material;

automatically transferring this information once on site to the paver information

system for use with respect to execution

and documentation purposes;

automatically locating and dating the

information along the road at the particular

place where the corresponding material

has been laid.

4 DESCRIPTION OF THE PROTOTYPE

SOLUTION

4. 1 The Concept

The solution we have chosen is based on the

two following technologies:

"Radio Frequency Information Data"

(RFID), for storing the data into electronic

tags; and

- "Global Positioning System" (GPS), for

positioning the material parameters with

respect to the road-building project.

The data related to a batch of material are extracted and transferred to the tag from both

156
the quality-monitoring computer (responsible

for recording the quality parameters from the

plant's main control computer) and the

weighing table computer that measures the

load of each truck as it leaves the plant. The

transfer is performed through an interfacing

box (called "i-box") connected to an antenna. Data are conveyed to the site by the tag; while

the truck is loading asphalt into the paver

hopper, the data are downloaded into the

OSYRIS paver's computer by a similar

transmission chain working in the opposite

direction.

Figure 1 shows the physical structure and data

flow of the system.

Plant main

control

computer

Serial link,

standardized

format

Plant quality

monitoring

computer

Truck

weighing

system

TCP-IP

protocol

Plant tag i-box

JI

Plant antenna

868 MHz

Truck tag

868 MHz

Paver

antenna

IT

Paver tag i-box

TCP-IP

On-board paver

computer

GPS

sensor

Figure 1: General structure and data flows of the system

For purposes of the feasibility experiment and

due to the unavailability of the OSYRIS on- board computer and GPS receiver, SEMR and

LCPC used a dedicated computer along with a GPS specific sensor. A customized software

program has also been written for this demonstration.

4.2 Electronic Tagging System

The device chosen was "Flex ID", marketed by

the German company DEISTER [2]. The main

features of this system are as follows:

transmission frequency: 868 MHz,

tag dimensions: 15 cm x 3 cm x 2 cm,

maximum number of antennae per i-box:

4,

storage capacity of tags: 8 to 32 Kbytes,

maximum read/write distance: nominal: 30 m; effective: 15 m,

possible links between i-box and tag:

TCP/IP, RS232 or RS485.

Figure 2 shows the tags and the antenna.

157
Figure 2: The Flex ID antenna and two of the

tags

4.3 GPS Positioning

A stand-alone GPS is capable of providing 2D

accuracy of approximately 3 to 5 meters since

the Selective Availability (SA) feature was

switched off by the USA in May 2000. This

accuracy is not good enough for our needs, as we require being able to distinguish between

the various lanes of a road.

For this reason, the GPS sensor we selected is an integrated DGPS sensor manufactured by

the OMNISTAR Company; it is composed of an 8-channel Trimble receiver, a GPS antenna

and a communications satellite antenna, to receive the differential GPS corrections, all embedded into the same housing.

4.4 On-board computer and software

For the feasibility study, a software program was developed to manage and display data

collected from the paver's on-board tag as well

as to perform a number of intermediate

computations.

Although this software has been run during the

evaluation experiment described below, it is not yet refined to a point of being proposed as an industrial product. In the near future, the

functions proposed by this software will also

be partially provided by the OSYRIS on-board

computer. Nonetheless, a dedicated system

focusing on the tracability between plant and

paving site has also been foreseen as a separate

development.

5 INITIAL EXPERIMENT

5.1 Description

In November 2001, in cooperation with the

DDE 77' offices, an initial experimental site was set up in order to demonstrate and validate

this concept. For the experiment, we designed

and built a prototype system around two

distinct goals: quality documentation and

operator assistance. This paper will focus

primarily on operator assistance aspects, which

may prove more illustrative and offer the

advantage of introducing the system from a more attractive perspective for contractors. The site consisted of a thin asphalt wearing

course for a new road, located in the town of

Bray-sur-Seine some 60 km southeast of Paris. A two-lane course of approximately 600 m x

6.2 m was built during the first day, and a

traffic circle plus the adjoining access roads were built during the second day.

At the plant, due to the absence of a standard

plug for connecting a quality-monitoring

computer, we had to manually enter the data

read on the plant control dashboard into a laptop computer and then transfer them into

the electronic tag through the i-box.

All of the trucks involved in the experiment,

five the first day and five the second, were

equipped with an electronic tag screwed onto

the right side panel, as seen in Figure 3.

^ DDE 77 standsfor "Direction Departementale de

I'Equipement" (Regional Bureau of the Ministry of

Construction and Public Works) for French

Department No. 77 and is in charge ofbuilding and

maintaining the department's public roads.

158
Figure 3: The tag screwed onto the truck side

panel

Figure 4: The paver on-board computer and

GPS antenna

An i-box and antenna, placed in a suitable

location for reading tags while the truck was

downloading its material, were installed on the

paver, as shown in Figure 4. In addition, an

ultrasonic sensor was used both to detect the

amount of material in the paver hopper and to validate completion of the downloading step.

Figure 4 shows the on-board computer

mounted on the side of the paver along with

the OMNISTAR GPS receiver used.

5.2 Data recorded and displayed

The following data were selected to be

recorded.

Quality parameters, from the plant computers:

- theoretical proportion of each component (in

percent), - theoretical asphalt fabrication rate of the plant (in tons/hour), - bitumen

temperature, upon introduction into the mixing

tube (in °C), - asphalt temperature, when

loaded into the trucks (in °C) (1), - precise

bitumen weight for each batch (in kg).

Quantity parameters, from the weighing

station:

- weight of the material batch for each truck

(in tons) (2),(weight of the empty truck (in

tons).

Miscellaneous identification parameters:

- identification of the work site, - identification

of the type of mix design, - batch number, - identification number of the tag or truck (3), -

starting and ending times of batch fabrication,

- truck weighing time (4), - plane coordinates

(using the national "Lambert" reference

projection system) of the starting and ending

points of the surface area covered by the batch,

together with the application time, both

provided by the GPS receiver.

In addition to parameters quoted (1) to (4), were displayed the following parameters, after computation by the on-board software:

- actual mass production rate of asphalt, using

batch weight and fabrication time (5), - actual

bitumen mass proportion for the material

batch, using batch weight and bitumen weight

(6), - average mass paving rate of the asphalt,

computed from the batch weight and batch

downloading time provided by the GPS

receiver (7), - paving process output: ratio of

paving rate to production rate (8), - exact average speed of the paver, thanks to GPS

timing (9), - suggested correct speed of the paver, in order to increase output as much as possible (10), - average asphalt weight per unit

area, using (9) and ( 1 0) and a theoretical width

(11), - total cumulative asphalt weight (12), -

total cumulative corresponding paving length

(13), - esfimated post-compaction thickness

(14), using (13) and the theoretical specific mass of the compacted material (15).

Numbers 1-6 are related to fabrication, and 7- 15 to the asphalt-laying operation.

159
5.3 Sample system output for tracability

purposes

Figures 5 and 6 show examples of simple

graphical outputs that may be of direct interest

to the project manager or architect/engineer

for checking the quality of the work.

direction - of the

3oo| paver

n1 789C8X77-10h15/6

SS n2 877BYM77-10h26/6

n3 877BYM77-16h04'6

~; n4 789C8X77-16hl8/6

n5 91 ANG77-15h52/6

It n6 7310VJ77-9h4S/7 S n7 607BSP77-9hS4/7

Figure 5: Location of the various batches

along the road (straight line)

n1 7279YY77-10)l15/7 sn2 552ABW77-10h20/7

n3 7310VJ77-10h59/7

n4 607BSP77-11hia7

n5231BTA91-11h31/7

n6 7279YY77-13h29/7 Sn7 552ABW77-13h38/7

Figure 6: Location of the various batches

along the road ( roundabout)

Trucks are numbered in the chronological

order. The scales used for both the x- and y- axes are in meters. This graphical display

clearly provides valuable information on the

way in which the site has been executed. For

instance, it can be observed on Figure 5 that batch no. 5 was laid after batch no. 4, even

though it had been loaded first at the plant.

Given the availability of such output, we are convinced of site managers' and supervisors'

ability to check very rapidly that site operations are running smoothly since any

disturbance (e.g. abnormal delays between

batches) can be detected quite easily. Figure 6

clearly illustrates the positioning accuracy

obtained by GPS from traces recorded in the

traffic circle, whose radius was about 10 m.

6 CONCLUSION AND OUTLOOK

This first site validated the satisfactory

behavior of information transmission by means

of RFID tags, which represented a novel

technology for us, in contrast with the rather

well-known GPS technology.

Despite the quality of results, this experiment was carried out in a semi-automatic mode and

this created some problems at the site level by

virtue of interfering with the execution and

disturbing the process it is supposed to trace. It seems obvious that total process automation is necessary in order to attain the high level of

reliability expected of the system.

In 2002, prototype improvements are foreseen

to conduct further experimentation, in the aim

of introducing a completely automatic mode of

operations. These improvements will mainly

concern software aspects. The new

experimental site is scheduled to be

operational by the end of the year: it will be a highway site, where we intend to trace all of

the successive pavement layers.

7 REFERENCES

[1] Ligier, A. et al. (2001), Open System for

Road Information Support, Proc. Of

the 18^^ International Symposium on

Automation and Robotics for

Construction, Krakow, 205-210

[2] Finkenzeller, K. (1999), RFID Handbook - Radio-frequency identification

fundamentals and applications, John

Wiley & Sons, London.

160
Monitoring Construction Equipment for

Automated Project Performance Control

by

Rafael Sacks' ", Ronie Navon", Aviad Shapira^ and Irina Brodetsky^

ABSTRACT: The ability of company managers to respond to variations in performance in construction projects

is severely limited by the time delay common in existing information and control systems in reporting schedule,

budget and quahty deviations from plan. We propose a system for interpreting data acquired automatically by

monitoring the activity of major construction site equipment, such as tower cranes, concrete pumps, etc. The

primary objective is to provide a rehable, real-time, automatic source of project performance information for construction managers. This requires interpretation of the monitoring results using a knowledge-based rule processor, and reUes on the existence of a computerized Building Project Model.

KEYWORDS: Automation; Construction equipment; Information technology; Monitoring; Project performance

control.

1. INTRODUCTION

The impact of management decisions on the

work carried out on a construction site is severely limited by the time delay required in order to provide accurate reports of project

performance in terms of schedule, budget and

quality. In existing information and control

systems, status reports are commonly delivered

with very long time lags, resulting in undesirable trends being identified too late for

corrective measures to be taken. Consequently,

fully automatic monitoring of indirect

performance parameters, and processing of the

data to provide informative indicators of

project progress, have been proposed (Navon

and Goldschmidt 2001). Progress indicators can be compared to project control limits to deduce the project performance and identify

probleins. If the project information is directly

available in the form of a computerized

building project model, the interpretation can

be done using knowledge-based software.

A focused research effort is currently under

way at the Technion (Israel Institute of

Technology) to develop the principles for: • fully automated data collection on

construction sites (Navon and Goldschmidt

2002),

• knowledge-based interpretation of the data

in relation to a computerized Building

Project Model (BPM) (Sacks 1998).

• provision of useful information about the

schedule, cost and quality of the work being

performed.

The generic term for systems using this approach is "Automated Project Performance

Control" (APPC). The aim of such systems is to support the overall APPC goal of shortening

the reporting cycle to one day, while

eliminating the effort of reporting entirely. A

number of projects have been initiated as part

of this effort: a labor monitoring system using

Automated Data Collection technology (Navon

and Goldschmidt 2001, Navon and

Goldschmidt 2002, Sacks et al. 2002), a system

for monitoring and reporting work performed

by heavy earthwork equipment (Navon,

Goldschmidt and Shpatnitzky 2002), and a

material control system.

Nearly all of the materials and components for a building are lifted into place by construction

equipment, such as tower and mobile cranes, concrete pumps, hoists, etc. Tracking and

recording the activity of such equipment is technologically straightforward. For these

reasons, the authors propose that monitoring

construction equipment holds the potential to provide significant data for APPC.

The system solution is a typical monitor and

control loop (see Figure 1). The main part the

control system is a decision rules processor. The processor receives data daily from the

' College of Architecture, Georgia Institute of

Technology, Atlanta GA30332-0155 USA. Tel: 404-894-0437 rafael.sacks@arch.gatech.edu

' Construction Engineering and Management,

Faculty of Civil Eng., Technion - Israel Institute of

Technology, Haifa 32000 Israel Tel: 972-4-829-

2600 ronie@techunix.technion.ac.il

161
monitoring 'black box' installed on the

equipment. This input consists of load weights

and crane-hook location coordinates gathered

from the equipment through its working day.

The location measurements are translated into

the local site coordinate system so that they can be related to particular building elements

or activities. The rules processor draws on a knowledge base of typical historical data, such

as unloading durations or profiles for different

construction activities, typical weights and

heights of auxiliary equipment (between the

hook and the load), spatial volumes typical of

construction activities, etc. The data describing

the project itself are drawn from a Building

Project Model based interface, including

details of pending activities (start/finish dates,

duration, main material components and their

approximate weights), probable storage areas and material delivery zones, etc.

particular activity, and can provide additional

information for other existing control systems

(such as Materials and Labor Control

Systems). Finally, the information provided is made available to management, and is used to update the project database.

In the following sections, the technology for

monitoring equipment is presented for the

typical case of construction tower cranes. Next,

we detail the system information flow and the

logic required for interpreting the data

collected, and outline the implications for

detailing of the necessary Building Product

Model objects and relationships. Finally, we

discuss the potential modes of use and benefits

of equipment monitoring APPC systems.

2. AUTOMATED MONITORING OF

CONSTRUCTION EQUIPMENT

Building

Project Data Building Product

Data, Acti«ty Schedules, BOM,

Site and

Equipment Data

Typical ActiMty

Data, Standard Equipment Data, Decision Rules,

etc.

Knowledge ^ Base

Q Start ^

BPM

Interface

Labor

Monitoiing

System

Materials Monitoring

System

Con\«rsion and

sorting of monitored data

Decision Rule Processing

Corrective Action by

Management

Figure 1 . Construction Equipment Monitoring

System

Using these three sources, the system is required to correlate the equipment movements

with particular activities. It can then draw

conclusions, with some calculated level of

certainty, about the performance of any

The particular case of tower cranes is used here

as an example (the methodology and

technologies for other equipment types are

similar). Selection of the monitoring

equipment is dependent on the data required.

These are identified as:

Wg(t)- the gross weight of the load being

lifted measured continuously through

time.

Lh(t)- the location of the hook in local building coordinates measured

continuously over time.

Typical plots of Wg (t) and Zh (t) - the height

coordinate of Lh(t) - are shown in Figure 2. At

least two distinct technological possibilities

exist for measuring these:

a) Separate Load and Location Measurement.

A variety of tensile links, crane-scales, load

measuring pins, load cells and others are available for measuring the gross load weight

with maxima ranging from 500 kg to 100 tons (MSL 2002, Strainstall 2002). Most have cable

or telemetry connections to a central interface

block. Their accuracy is typically about ±1%

of actual readout. A data recorder must be

added. For location monitoring, a Global

Positioning System (GPS) receiver may be

used (Roberts et al. 1999). A pair of receivers

may be used and operate in differential mode

to avoid transmission interference, and to

162
achieve sub-metric accuracy (Peyret et al. 2000). GPS coordinates can be translated into

local coordinates (Navon and Goldschmidt,

2002).

Load (kg) — — Height (m)

Figure 2. Typical Concrete Bucket Loading

and Unloading Profile for Pouring a Slab.

b) Built-in monitors supplied by the equipment

manufacturer. Large construction plant

companies offer optional crane monitoring

systems that provide real time monitoring of

weight and location parameters. For example,

Potain's 'Dialog Visu' control system enables

real-time monitoring and recording of the 'on- hook weight', and of the hook position in

terms of boom rotation angle, radius of the

trolley from the tower, and height of the hook

from the ground (Potain 2002). (This definition

of location, about the tower axis, can be

considered a 'local crane polar coordinate

system'). It should be noted that these

advanced control systems are intended mainly

to enhance site-safety, for more accurate crane

operation in zones with reduced visibility, and

for operation with remote control. They can be

programmed to give warning against overload

or to prevent travel into dangerous zones. They

were not intended for project performance

control purposes.

3. INTERPRETING MONITORED

DATA

Comparing these data with calibrated typical

load data and with the project model

information should allow the system to draw

conclusions about the type and identity of the

building element being worked on the material

or equipment being lifted, to identify supply of

material to the site, and to identify the specific

construction activity being performed.

3.1 Knowledge Based Rules

The knowledge rules encompass all of the

processing as laid out in Figure 3. It is envisaged that most of these will use production rule format expressions of the

logic, although other techniques may be

employed as needed. For example, consider

derivation of the identity of the load, which is a

central piece of information. Not only can the

load itself be compared with known loads, but

the pattern of unloading over time may also be

matched with a library of typical patterns, such

as the pattern for unloading concrete from a bucket for pouring a slab, as shown in Figure

2. In the figure the multiple points of

unloading, and the residual load of the bucket

during descent, are typical of casting concrete using a bucket on a crane. Recording a library

of such patterns, and deriving pattern-matching

rules from them, is therefore one of the tasks

required for development of the knowledge

base.

3.2 Project Data Model Information

Requirements

Processing the knowledge-based rules outlined

above requires that up-to-date information

describing the construction project be available

in computerized form. Given the diversity of

sources of this information, we assume that it will be provided by means of a Building

Product Model (Eastman 1999). The

information must cover three main areas: • the building product: the physical parts of

the building. • the construction process: the activities through which the building is built. • the resources employed in construction

(materials, equipment and labor).

The details of these are illustrated in the

following discussion using the example of

construction of a simple reinforced concrete column.

First, the existence of the column, in a

particular geometric location in terms of the

building's local coordinate system, and having

a specific shape, must be known, so that the

location of delivery of equipment and materials

163
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Figure 3. Rule processing flow.

164
can be correlated with a specific building

element. The physical components of the

column - the reinforcing cage and the concrete - must also be identified and described in sufficient detail to allow calculation of their weight and location. The fact that the column

is part of an assembly consisting of the other

RC columns on the building's floor (and

possibly also the slab it supports) must also be

known. These basic aspects of building

product information - product identity,

location, geometric shape, material type and

assembly/component aggregation - are included in Building Product Models such as

the IFC 2.x schema (lAI 2001). They are communicated in the CIS/2 structural steel product model (CIS/2 2001).

Second, the nature of the construction

method and the planned schedule of

construction activities must be available. At

the simplest level, knowing whether the column is precast or cast-in-place is critical to interpreting the lifting data. Each construction

activity, such as 'build 4"' floor columns' must

be fully defined in terms of its scope (the

elements it includes - which columns are to be

built), its scheduled start time and duration,

the activities which precede or succeed it, and

the resources that will be used and/or

consumed in its execution (see next

paragraph). However, this level of detail is insufficient to allow conclusions to be drawn

using the rules outlined above. The basic

activities of each activity (as defined by its construction method - Sacks and Warszawski

1997), must also be detailed (Sacks et al. 2001). For an assembly of cast-in-place RC

columns, the activity 'Build Columns' would

include the following basic activities: prepare

column forms, fix rebar cages in place,

position and stabilize forms, pour concrete,

compact concrete and strip the forms. It is at this level that the APPC system contemplated

here can identify execution of an activity - by

associating the specific loads and unloading

patterns of equipment and materials with

specific sequences of basic activities. Some of

these aspects of the construction process are provided in computerized construction

schedules (note that the problem of updating

schedules is specifically addressed by APPC.

Nevertheless, while construction managers will be relieved of the need to input historic data.

they will still be required to update their future

intent).

Third, the resources of interest are those lifted by the crane - equipment (such as steel forms

for RC columns) and materials (rebar cages

and buckets of concrete). Their identity,

function (i.e. association with a basic activity

type), and weight must be detailed. In all cases except for bulk materials, their shape and

center of gravity are required. Some

resources, such as precast concrete pieces

(elements), rebar cages, etc are project

specific, while others, such as steel shutters, concrete buckets, etc. and all bulk materials, are generic across many projects.

Note that certain prefabricated parts of a building are defined as 'products'. For the

proposed system to function, the fact that they

also exist as material 'resources' (prior to their erection in the building) must be stored

explicitly.

4. POTENTIAL BENEFITS

The processed information will be used for progress monitoring to produce 'as-made'

information for updating project schedules.

Additionally, it will be used as input to existing models - e.g. labor inputs control

(Navon and Goldschmidt 2002) - for cross- reference purposes, thus improving their

decision-making algorithms. Additionally, the

research is expected to explore the potential for

generating significant additional information

from monitoring lifting equipment, such as: • Accurate quantities (weights) of materials

supplied (e.g. precise quantity of concrete

poured), steel installed, etc. « Patterns of building structure weights and

their distributions (for long term validation

of structural design codes).

• Potentially life-saving real-time

information of crane hook location vis-avis worker locations (monitored with hardhat GPS - Navon and Goldschmidt 2001).

• The identity and quantity of materials

delivered to the site and the movement of

materials within the site, for materials

control purposes.

• Data regarding the availability of

equipment and materials necessary for

scheduled activities prior to their

165
commencement, to avoid delays and

reduce downtime for crews. • Data that can be used for improving the

efficiency of equipment operating

procedures, and/or of other aspects of the

production process (e.g. work study data).

5. CONCLUSIONS

The concept of automated monitoring of

construction equipment, within the framework

of an Automated Project Performance Control

system, holds the potential to greatly enhance

the ability of construction managers to respond

quickly to project performance problems. A

road map for both the measurement and

information technologies that are required has

been set out. Ongoing research will focus

principally on developing and testing the

knowledge-base that must interpret raw

monitoring data and produce reliable

performance information.

6. REFERENCES

Ciesielski, C. A., (2000). "ADCIC - Automatic

Data Collection in Construction." A.I.M.'S

Global Academic & Scientific Conference.

Cairo (Egypt).

CIS/2 - CIMsteel Integration Standards 2, (2001). http://www.cis2.org

Eastman, CM., (1999). "Building product

models: computer environments supporting

design and construction," CRC Press, Boca

Raton, Florida.

lAI (2001). International AUiance for

Interoperability (http://www.iai.org). Industry

Foundation Classes IFC Release 2.0.

Monitoring Services (UK) Ltd. (2002). "Load

Transducers & Telemetry Monitoring

Systems", www.msl.ision.co.uk

Navon, R., and Goldschmidt, E., (2002).

"Automated Data Collection for Labor Inputs

Control," Automation in Construction

(accepted).

Navon, R., and Goldschmidt, E., (2002). "Can

Labor Inputs be Measured and Controlled

Automatically?" ASCE Journal of

Construction Engineering and Management

(accepted).

Navon, R., Goldschmidt, E., and Shpatnitzky,

Y., (2002). "Field Test of an Automated

Location Measurement for Project

Performance Control," Special issue on Automated Data Capture Technologies of the

Journal of Computer-Aided Civil and

Infrastructure Engineering (accepted).

Peyret, F., Betaille, D., and Hintzy, G., (2000).

"High-Precision Application of GPS in the

Field of Real-Time Equipment Positioning.

Automation in Construction, 9: 299-314.

Potain S.A. Ltd. (2002). "Lifting Equipment

Products", www.potain.com

Roberts, G. W., Dodson, A. H., and Ashkenazi,

v., (1999). "Global Positioning System Aided

Autonomous Construction Plant Control and

Guidance". Automation in Construction, 8: 589-595.

Sacks, R., (1998). "Issues in the Development

and Implementation of a Project Model for an Automated Building System," International

Journal of Construction Information

Technology, Salford University, Salford UK

Vol. 5 No 2 pp. 75-101.

Sacks R., Navon, R., and Goldschmidt, E., (2001). 'Building Project Model Support for

Generating Automated Project Performance

Control Information', submitted to the ASCE

Journal of Computing in Civil Engineering,

December 2001.

Sacks, R., and Warszawski, A., (1997). "A

Project Model for an Automated Building

System: Design and Planning Phases,"

Automation in Construction, Elsevier Science

Publishers B.V., Vol. 7 December 1997 pp. 21-

34.

Strainstall (UK) Ltd. (2002). "Industrial Load

Measurement", www.strainstall.com

166
Experiences with the Design and Production

of an Industrial, Flexible and Demountable (IFD) Building System

Frans van Gassel

*

Eindhoven University of Technology, Department ofArchitecture, Building and Planning,

P.O. Box 513, 5600 MB Eindhoven, The Netherlands.

ABSTRACT: The Dutch government encourages innovative construction by subsidizing cohesive industrial, flexible and demountable building (IFD) pilot projects. Industrial building concerns the process-related aspects

of production, robotization. mechanization, automation, prefabrication, communication, etc. Flexible building

involves products that are made in accordance with customer's wishes and the possibiUty to make adjustments

when the building is in use. Finally, demountable refers to the sustainability of the building.

This paper describes the experiences relating to the design and production of a demonstration project (IFD

Today) for an apartment building system on the Eindhoven University of Technology campus. A housing

corporation had commissioned the design of an industrial, flexible and demountable building system for flats, on

an existing foundation, the surface area and floor plan of which had to be adaptable during use. The current flats do not meet present requirements as set by the government and the occupants, and renovation is too expensive.

The data was obtained through participation in the design team and close production monitoring. The paper

focuses on industrial building. After monitoring the design and production process, the following conclusions can be drawn:

• IFD building requires co-operation and a multidiscipUnary approach during the design process. Essential

issues to be considered during the design process are the tasks, choice of designer, design tools and the expected result. Design meetings must also be organized.

• Due to the lack of a suitable model to calculate the production, operating, renovation and demounting costs and the absence of a marketing plan, conventional designing solutions were frequently applied. • The steel structure and floor panels were mounted very quickly. This was in contrast to the outer walls, roof,

fittings and finishing elements.

• It is advisable to entrust one specific company with the responsibility for a number of production tasks, such

as planning, making and checking the drawings, and allocating labor resources with regard to transport and

safety.

KEYWORDS: Building Site, Building System, Industrial Construction , MultidiscipUnary Design.

1. INTRODUCTION 2. IFD BUILDING

A trial module was built on the Eindhoven

University of Technology campus to gain

experience with the design and production of an IFD building system. This paper presents the

findings. The first paragraphs explain the concept

of IFD building, the IFD Today project and how

the study was set up. Finally, conclusions and

recommendations are made with regard to the

marketing of the IFD building system, based on

the results of the study.

In the Netherlands, a program entitled 'Industrial,

Flexible and Demountable Construction

Demonstration Projects' has been developed by

the Ministry of Economic Affairs and the Ministry

of Housing, Spatial Planning and the

Environment. This program was developed to promote the innovative application of industrially

developed and manufactured construction

components in the construction and renovation of

homes and public utility buildings.

E-mail: f.j.m.v.gassel@bwk.tue.nl

167
IFD building provides an integrated approach to the initiation phase, the design, production and use

of buildings, and is characterized by early co- operation between the parties, enabling alignment

of the concept, design and execution. The

industrial production of components offers increasing opportunities for flexible use. Demountable building enables a separate

replacement of components with various lifespans,

thereby extending the life of the building as a whole. As such, IFD building is a form of

sustainable building. [SEV]

Van den Brand describes IFD building as a threepronged strategy to innovate the building process:

the client (flexible), the manufacturer (industrial)

and society (demountable). This is characterized

by the following principles: 'level-thinking'

[building - floor - room - work station], a fixed

form and space combined with variable options

for the interior, a multidisciplinary design,

separate technical systems; dimensioning and

nodes; modularity and demountability. [Van den

Brand]

3. IFD Today

Between 1945 and 1963, about 400,000 apartment

buildings were constructed in the Netherlands

with the following characteristics: traditional

design, the use of clay, no insulation, poor sound

insulation. They were, almost without exception,

four-storied staircase-access flats. Between 1964

and 1975, another 475,000 medium-rise apartment

buildings and 300,000 high-rise apartment

buildings were constructed. Today, these

apartments still have poor (sound) insulation (see

figure 1).

Figure 1. Apartment blocks.

The improvement of post-war houses as from

1974 mainly involved the application of

insulation. Although heat insulation was

improved, the number of problems associated with

building physics increased. In spite of substantial

investments, very little could be done to improve

the living quality. Houses were cramped and

inadequately equipped, they had poor sound

insulation, and were only accessible by a narrow

staircase. A more drastic approach proved technically

impossible or would have required substantial and

unprofitable investments. The current demand for

houses is very diverse in terms of surface, layout

and fittings. Even in cases where a drastic

approach was adopted, the required level of

housing differentiation could not be achieved

within the existing shells. For this reason, more

and more post-war houses will be demolished.

[IFD Today]

A partnership (IFD Today) between the Amnis

housing corporation, contractor Heijmans IBC,

installer Stork and the Eindhoven University of

Technology has chosen to solve the above

problem with IFD building. A design team

comprising staff employed by the partners was

instructed to develop an IFD building system

using existing technology.

4. IFD BUILDING SYSTEM

According to Eekhout, a building system is an

orderly collection of construction elements and

construction components with connecting

facilities, which can be combined or applied in various ways, in accordance with regulations or agreements and depending on the environment.

[Eekhout]

The building system process is characterized by

the following aspects: technology, the human

factor, information and organization. The building

system product is characterized by the aspects of

function, flexibility, geometry, materials,

structural and technical capacity, complexity and

cost. The dominance of the aspects depends on the

market in question. The production of frequently

used construction elements has now largely been

mechanized or is carried out by robots, for example. Specific construction elements requested

by the client are manufactured in the traditional

way.

The conceptual design in IFD building is based on

six specific values of a building:

• Basic value: achieving a building physics

level that is higher than current standards.

• Use value: aiming for as much layout freedom

as possible at building, story and apartment

168
level and with regard to individually

adjustable and quantifiable installations.

• Local value: achieving a building system that allows differentiation possibilities according

to type, surface, layout, fittings and

architecture.

• Ecological value: reusing foundations and the

necessity of applying light structures. • Economic value: developing a product in line with marketing conditions.

• Strategic values: constructing a building that can be adjusted in the course of time.

These values can be considered on four different

levels: the built environment, building, house and

living quarters level. The conceptual design

addresses the design aspects, viz. the

requirements, design, quantification and design

strategy.

[Rutten] [Systeemcatalogus IFD Today]

Hendriks has developed a number of design

criteria for IFD building: • Integration and independence of disciplines:

installation, bearing structure, outer shell and

interior finishing.

• A completely dry building method: no pouring

of concrete, mortar joints, screeds,

stuccowork, sealant or PUR spray.

• Perfect modular dimensioning: a great deal of

attention to drawings, prototype testing,

quality system for drawings, and assembly

instructions. • Adjustability of all parts: bearing structure

(limited), installation (practically unlimited), outer shell (limited and modular), interior finishing (practically unlimited and modular).

[Hendriks 1999]

The IFD building system has the following

characteristics: • A steel support construction of hot-rolled

standard profiles, L-supports at the comers,

and I-supports and joists on the grid line. • The supports provide stability and the joists

have been fixed to the bearers in such a way

that vibration is kept to a minimum. The floor

panels are placed on the joists. • The floor panels are hollow to enable the

inclusion of technical installations. See figure

2. • Piping can be placed in the supports and the

floor panels at the plant or the building site. • Non-bearing walls dividing houses and rooms

can be placed anywhere.

• Free choice of outer wall. • There is no specific roof design. The

traditional solution is adopted, i.e. warm roof.

Figure 2. Assembling the floor panels.

Characteristic elements of IFD building are: • An 1 1 -meter span and a 7.2-meter grid. • Optimal free space providing various layout

possibilities.

• Maximum flexibility with respect to vertical

and horizontal piping, providing various

possible locations for toilets, kitchens and

bathrooms.

[Systeemcatalogus IFD Today]

5. STUDY

To gain experience with the IFD building system,

a trial module was built on the DUBO

(Sustainable Building) park on the Eindhoven

University of Technology campus. The trial module is fourteen meters wide and eleven meters

deep, and has two stories. See figure 3.

Figure 3. IFD building system trial module on the

Eindhoven University of Technology campus.

Not only the trial module's design process but also

its production process was assessed for its IFD

characteristics.

169
This report only describes one aspect of IFD

building, viz. industrial building.

According to its conceivers, the IFD technology

makes use of the following traditional elements of

industrial building:

• Production at the plant. • Mechanized production.

• Mass production.

• Co-operation is independent of projects.

• Deployment of information technology.

Today, the emphasis in industrial building is on:

• Customer-oriented production and marketing.

• Flexible production systems.

• Subsystems are independent but can be

combined.

[Hermans]

The transfer of production from the building site to the plant has resulted in an integration of

functions and sometimes materials of a component

or a system of components. This requires a high

level of component alignment (specifications,

dimensioning, finishing) [Bouwen op kennis]

For the purposes of this study, the following

description of industrial building is used: the

transfer of physical tasks from the building site to the plant and from people to machines and

computers. These tasks do not involve building

alone but include the collection and processing of

data, consultations and alignment, optimization

and planning.

It is apparent from this description of industrial

building that designers from various disciplines -

architectural designers, building physics

designers, electrical and mechanical designers,

construction designers and implementation

designers - are involved in joint designing from

an early stage.

• The fitter discusses solutions a great deal. • Little use was made of sketches in the concept

design phase.

• Design problems were passed on to the

subcontractors, who then solved them

independently.

• Production costs were calculated in the

traditional manner.

• Design problems were still being solved in the

execution phase, usually at the building site.

During the building phase of the trial module, the

meetings between the designers and the parties

executing the work were sometimes reminiscent

of a site meeting.

During the design and production process, a list of

points for improvement was made, which could be

used during a subsequent design process.

5.2 Production process study

The production process is considered a transformation of materials into a building, with

waste as a by-product. The transformation is carried out by people and tools and managed using

plans, drawings and instructions (monitoring). See

figure 4.

Materials

Management

Production

Process

Labour

Building

Waste

People

5.1 Design process study

The trial module was designed in close co- operation by a team consisting of an employer,

architect, structural engineer, fitter, contractor and

representatives of the supply industry. An attempt

has been made to describe the experiences gained

through intensive participation in design meetings:

• The preparation for the meetings was limited

to an agenda.

• Other subjects, such as planning, subsidy

applications, composition of the design team, were also discussed.

• The fitter, in the capacity of installation

consultant, aims to find quick solutions.

Figure 4. Model of the production process ofa

building.

The following aspects of the production process can be observed:

• The production process: preparation,

transport, storage, treatment, processing,

conditioning.

• Materials, construction elements, construction

components.

• The building and (separate) waste flows.

• The people: planners, project manager,

supervisors, construction workers, mechanics.

170
• Labor resources: tools, scaffolding and

accessibility structures, transport equipment.

• Management: planning, schedules,

instructions, drawings.

The findings obtained during close monitoring of

the production process at the plant and at the

building site were recorded in a log, filmed or photographed. Explanations, comments and points

for improvement are provided for photographs

depicting extraordinary situations. Table 1 gives a concise overviev,' of the findings and points for

improvement for each aspect. [Van Gassel]

6. CONCLUSIONS

The following conclusions can be drawn after monitoring the design process and production

process:

• In IFD building, the design process requires

co-operation and a multidisciplinary approach.

Matters such as design tasks, choice of

designers, design tools and expected results must be considered during the course of the

design process, and design meetings must be

organized.

• Due to the lack of a suitable model to calculate the production, operating, renovation

and demounting costs and the absence of a marketing plan, conventional design solutions

are frequently chosen.

• The steel structure and floor panels are demounted very quickly. This is in contrast to the outer walls, roof, fittings and finishing

elements.

• It is advisable to entrust one specific company

with the responsibility for a number of

production tasks, such as planning, making

and checking the drawings, and allocating

labor resources for transport and safety.

7. RECOMMANDATIONS

The IFD building system should be treated as a comprehensive product and be marketed by one company or a cluster of companies. The company

or cluster of companies should develop an IFD

cost model and marketing plan for this purpose.

The marketing plan should address at least the

following elements: living concepts, mass

customization, adaptability at all phases of the

building's economic life, period of use versus economic life, customer order release point, longrange production planning etc. Specific skills required for the organization and facilitation of

and participation in design meetings could be

obtained by a mutual exchange of knowledge.

8. REFERENCES

[Van den Brand] Van den Brand, G., Rutten, P., Dekker, K. 1999, IFD Bouwen, Principes en

Uitwerkingen. TNG (Netherlands Organization for Applied Scientific Research) report 1999-BKRR021, TNO Bouw (Building and Construction

Research) Delft.

[Bouwen op kennis] Bouwen op kennis,

Rapportage verkenningscommissie Bouw, 2000,

Adviesraad voor het Wetenschaps- en

Technologiebeleid.

[Eekhout] Eekhout, Mick, 1997, POPO of

ontwerpmethoden voor bouwproducten en bouwcomponenten. Delft University Press.

[Van Gassel] Van Gassel, Frans, 2001, Bijdragen aan de IFD Today systeemcatalogus. Report of

the Eindhoven University of Technology.

[Hermans] Hermans, M, 1997, De marktpositie van IFD-bouwen voor de Nederlandse

Bouwindustrie, Damen, Rotterdam.

[Hendriks 2001] Hendriks, Nico, Frans van

Gassel, 2001, Construction of a prototype ofan

industrial, flexible and demountable (IDF)

apartment building system. International Status Report on Aspects of FutureSite. CIB Publication

265, Wellington NZ.

[Hendriks 1999] Hendriks, Nico, 1999,

Industrieel, Flexibel en Demontabel Bouwen

(IFD): Ontwerpen op veranderbaarheid,

Eindhoven University of Technology.

[IFD] IFD Today, 2000, Leaflet.

[Rutten] Rutten, P., Trum, H., 1998,

Prestatiegericht ontwerpen en evalueren.

'Geintegreerd ontwerp van gebouw en

installaties', reader of the Eindhoven University of

Technology.

[SEV] SEV, Leaflet IFD and www.sev.nl

[Systeemcatalogus IFD Today] Internal IFD

Today publication.

171
Table 1. Findings and points for improvement with regard to the production process

Aspects Findings Points for improvement

Materials Additional production space was needed

at the plant to mount technical

installations into the steel construction.

Mechanics had to determine reference

points and dimensions themselves as these were not indicated on the drawings

submitted.

The production of large elements was

treated as a project instead of serial production.

Mechanics frequently tried to mount

installations at the building site instead of

at the plant. Parts were selected and the assembly

order was determined at the building site. Small materials were delivered unsorted

and in bulk. As a result, much sorting was

needed and materials got damaged.

Special assembly drawings should

be made.

Investments should be made in

mechanization and robotization.

Construction components should

be coded.

Materials should be supplied in crates and using additional means

of transport.

Management Each supplier submits its own drawings.

Connections between construction

components of the various suppliers were

not provided and a solution had to be

found on site. Many telephone calls were

needed to obtain the required assembly

information.

Drawings should be made of the

connections between the

construction components.

Specifications should be of a

quality that the need for drawings

and instructions is eliminated.

A project database and project extranet should be used.

People • Different types of scaffolding were

erected for different parts of the work.

• Traditional safety provisions such as edge

protection were used.

• One type of scaffolding should be

used.

• Safety provisions should be

integrated in the building system.

Labor

resources

Various types of cranes were used,

sometimes as many as four at the same

time.

Special labor resources were made and

deployed at the building site for the

purpose of the project.

• One type of crane should be used

during the execution process.

• Specific labor resources should be

designed.

Waste • Much waste was produced during the

fitting-out process.

• Waste was not collected separately.

Returnable packaging should be

used.

Work on material carried out at the building site should be kept to a minimum. This should be

confined to the plant as much as

possible.

Waste should be separated in accordance with government

regulations.

Building Building physics measurements showed

that a number of details had not been

finished properly: noise leaks, air leaks,

etc.

• Details should be finished

properly.

172
FutureHome - A PROTOTYPE FOR FACTORY HOUSING

by

Robert Wing' and Brian Atkin^

ABSTRACT: The manufactured housing project FutureHome, which received major funding from the European Commission, has developed the engineering know-how to create affordable, high quality, cost

effective manufactured housing, with a customer focus that takes account of diversity of styles, designs,

materials and locations. The provision of housing to an acceptable standard is becoming an increasingly

serious problem worldwide, and the widening gap between supply and demand points to manufactured

solutions as the most viable way forward.

FutureHome has developed systems for product and process analysis suited to manufactured and

prefabricated construction solutions, and these have led to design prototypes. To mark the end of the research phase of the project, one design has been built to full scale as a demonstrator. The research has

led to leaner design and construction processes that focus on value for money, improved productivity,

maintainability and sustainabihty. It has also focused on basic engineering requirements such as fast connectors, and automation solutions for materials handUng and assembly. Further aspects of the research programme have considered how the product can be adapted to areas of high seismic risk, and

has developed software solutions for design and management from a virtual-reality customer interface to cyber-agents for logistics.

FutureHome is expected to have benefits through savings in construction costs and time, significant

reductions in defects on completion, and will enable industry to be more competitive overall. Other

benefits include improving the quality of life, social fabric and health of the European economy through a more efficient and effective construction process.

Keywords: housing; manufacture; construction; automation; process

1. INTRODUCTION

FutureHome is a European R&D project

bringing together fifteen partners from six

European countries, and forms part of a global

project under the Intelligent Manufacturing

Systems (IMS) programme. This project has

explored the potential to apply advanced

manufacturing technology to housing design

and production, aiming for significant

construction cost and time savings, and major

reductions in defects on completion. The

studies have shown that high quality can be

delivered at a fraction of the cost of the

traditional construction methods that currently

dominate the market. A strongly IT oriented

approach is seen to be fundamental, with state of the art simulation tools for support of the

design and construction processes and

effective involvement of the customer.

The project is industry-driven and draws on the

substantial expertise and resources of some of

Europe's major manufacturers and niche

contractors - all with a reputation for developing and applying innovative solutions.

The European Commission supports the

project under its 5nYe-Euram programme,

enabling leading European research institutes and universities in this field to work alongside

the industrial partners; the European

consortium has a formal collaboration

agreement with IMS project IF7, "The

Intelligent Field Factory", involving a large

Japanese research consortium. The Japanese

project is primarily concerned with larger,

' Department of Civil and Environmental Engineering, Imperial College of Science, Technology & Medicine,

London SW7 2BU, United Kingdom. Tel: +44 20 7594 5997 Email: r.wing@ic.ac.uk

^ Atkin Research & Development Ltd., Woodcote, Reading RG8 OQX, United Kingdom

Tel: +44 1491 681818 Email: brian@atkin.co.uk

173
particularly taller, structures, but in other

respects its objectives parallel those of

FutureHome. That consortium includes three

major construction companies in alliance with

universities and research institutes [Ref. 1].

2. HOUSEBUILDING AND EUROPE'S

ECONOMY

At the start of the 21^^' Century, much of

manufacturing industry is exploiting the

efficiencies of mass-customisation, with design

integrated to computer-controlled production.

Customers enjoy affordable high-tech goods

and, particularly in the fields of

communications and entertainment, see improvements to their quality of life and work.

The housebuilding industry, however, is slow

to adopt the benefits of our post-industrial

digital age, opting for the traditional craft approach with its rather variable output

quality.

Attempts during the 20"^ Century have failed to provide a factory approach to housing

construction, and today's most advanced

offerings, represented by pre-fabricated

modular systems are struggling to gain their

market. Factory-produced panel constructed

housing is gaining popularity in the

Netherlands and Germany (Fertighaus), where

this approach has become a substantial

industry sector [Ref. 2]. The main advantage

is that many of the construction processes are brought indoors, and benefits then arise from

reduced weather impact on scheduling, and the

relatively easy availability of machines and

services in a well-structured factory

environment.

Extension of this principle into 3 dimensions is seen in modular prefabricated housing. Here

entire room sized units can be completely

fitted out within the factory and delivered to

site for assembly. A demonstration project of

this type has been recently completed in London (Murray Grove), where it was the

client, Peabody, the UK's largest housing trust, that drove the initiative to use modular

methods; the general success convinces it to use the same concept on further projects.

Such projects, however, represent only a minute proportion of the construction industry,

the largest industrial sector in Europe's

economy; with an output of 780 million Euro

it exceeds Japan's construction industry by

10%, and that of the US by 30%. It is also

Europe's largest employer, providing jobs for

1 1 million workers, and with each construction

job generating another two in related sectors some 21% of Europe's workforce therefore

depends directly or indirectly on construction.

In this time of sociological, demographic, and

rapid technical change, the industry is adapting

to many new challenges, including;

• Creation of multi-functional buildings

capable of adapting to the changing nature

of work and leisure. • Provision of housing for Europe 's ageing

population, offering comfortable and

autonomous lifestyles. • Provision ofquality urban environments.

• Reduction of energy usage, buildings

currently being responsible for more than

40% of total consumption.

• Reduction of waste; future building

products need to be re-usable and

recyclable.

The above factors, together with client demands for both quality and quantity in the

housing sector indicate that factory methods

will be essential in the future if the industry is to handle future demand and avoid loss of this market to foreign competition. The greatest

challenge for the industry is to leave traditional

methods behind, and evolve solutions based on

a fully manufactured house rather than simply

introduce factory-prefabricated parts into current processes. The perceived solution is mass-customisation rather than custom-build,

together with an IT-based approach to design

and construction.

3. THE FutureHome CONCEPT

FutureHome's priority has been to evolve a design system that takes account of the

diversity of styles, designs and material

composition, and especially the preferences of owners and occupiers, that is, customers who

are as diverse as Europe itself. All share the same basic requirement of a home that is affordable, decent, modem in its facilities and

capable of adapting to changing needs. The

general maintainability of the products of

174
FutureHome, employing materials and

components that can be reused, is a key

objective.

New approaches to design and production are needed, for assembly in a controlled, factory

environment by a higher skilled labour force,

using materials more efficiently, and involving

low energy use in operation. These, in any

case, are essential elements in Europe's path

towards sustainable development.

Production has to be divided between fixed

plants for component manufacture, and field factories for assembly of larger units local to the construction sites. The field factories

reduce the overall transportation resources

required, and importantly will bring

employment to the area undergoing

regeneration. It is not, however, an easy

change for the traditional housebuilding

industry, and it is possible that the initiative for

setting up the manufacturing facilities will come from another industry sector, as has

happened in Japan.

The current panel-based pre-fabricated housing

systems use production processes based on

labour rather than machines. They address

part of the problem, as site-based employment

becomes less attractive to prospective

construction workers and consumers demand

more consistent quality. Systems based on

steel, timber and concrete structural components have been developed, but only

steel and concrete would be suitable for the

full range of apartment types and heights

required, and the economical transport radius

for concrete systems is limited. Thus the core components in a new European housing

industry would need to be fabricated from steel [Ref. 3].

Small-scale suppliers of pre-fabricated

buildings based on light steel frames exist in most European countries. The challenge is to create a more efficient integrated production

system, taking advantage of these firms'

knowledge of local requirements as well as drawing on the expertise in other industrial sectors with long experience in combining

customisation with mass manufacturing

technique. Customisation is the key to the success of this approach; current housebuilding

supply chains are not robust enough to tolerate

the variabilities in customer demands because

capacity is not engineered into the system.

The IMS link with Japan has been valuable in understanding the market requirements, as in that country mass-produced, customised homes

have secured 7% of the new housing market,

and with excellent customer response

Development of the new housing systems and

associated manufacturing plant proposed in FutureHome's outputs will contribute to the

regeneration of urban areas, create new skills,

and establish integration of the technological,

social, economic and business aspects to support the future provision of housing in Europe.

4. FutureHome's ACHEIVEMENTS

The engineering R&D within the project

covered three linked areas:

• Building System studies. • Automation studies

• IT studies

Examples of FutureHome innovations and

developments from each area are given below;

it is hardly necessary to state, however, that even this large project barely scratches the

surface of the major gains obtainable from a

full factory-based solution.

4.1 The FutureHome building system

The FutureHome building system derives

from a Kit-of-Parts approach, wherein

standardisation plays a significant role in achieving economies from the many variations

allowed in the parts set. The choice of light

steel framing for the pre-fabrication base comes from transport logistics and the

requirement to use automation tools both in the

factory and on site. This demands assured

dimensional precision and avoidance of

problems such as warpage and shrinking.

Kit-of-Parts is a specific implementation of

prefabrication; the distinction being that such

structures follow an assembly, disassembly,

parts replacement, re-assembly sequence as required during their life-cycle. Normal

prefabricated structures, however, can only be

taken apart with loss of functionality, either

175
due to unavoidable damage or irreversible

jointing.

The general modular concept, I-KOP, or

Integrated Kit of Parts, centralises the

provision of services in standardised core modules, leaving considerable design freedom

for the outer (less serviced) modules and

panels (Figure 1).

4.2 Production optimisation for

prefabricated buildings

The balance between site and factory processes, and the optimum level of

prefabrication for housing designs are analysed

using software tools such as DSM

(Dependency Structure Analysis), a systems

analysis tool for the investigation of

interactions and interdependencies between

elements in a complex system - modules and

sub-systems in this case. Used on the

architecture of the product, DSM determines

possible integrative components, in other

words, it seeks potential for employing larger

factory pre-fabricated modules. Used on the

assembly process DSM creates optimised task

sequences that can be fed into planning tools

to determine the critical path for the assembly

process.

Additionally, IDEFO process analysis methods

have been used to produce optimised workflow

procedures for the purpose of providing a model of the total process for design and

manufacture of FutureHome products. The

aim has been to create a single, integrated

model of the process from which views of the

various phases can be mapped in detail. Information has been sought from the project

partners and from outside the project to develop this blueprint for total process control.

The use of the international standard, IDEFO,

to portray the logic of the process, its activities, information flows, controls (i.e. constraints) and mechanisms (i.e. personnel

and tools) within the model brings together in one place the core information needed to organise and manage the design and

manufacture process. Figure 2 illustrates the

top-level view of the process, which is decomposed into lower levels of detail that equate to specific work flows.

Using BPWin software, a detailed model has

been created, with activity, cost and time data

incorporated. The model has been used to export these data to an ODBC-compliant

database (Microsoft Access), located on a password protected web site: the term Process

Control Interchange has been given to this development. Authorised users can interact

with the model's database to import data for cost estimating and time scheduling. Other

data can be exported to assist in defining work

flow and decision control procedures.

One of the benefits of this modelling approach

is that a change in any one element is reflected

automatically in the rest of the model, thus

preserving data integrity. Different

arrangements within the process can be tested and optimised.

The model combines an earlier model for the

design of a structure at full size, with those for

off-site manufacture and on-site production of

the components and assemblies. This holistic view of the process provides the basis for the

development of ICT tools for automating work

flow. Output from the model can be

interchanged with many applications, allowing

value to be added to the basic process model.

4.3 Connectors for automated assembly

Complementing the Kit-of-Parts, connectors

have been developed for FutureHome

modules, covering structural, assembly, and

services requirements. These are seen as the

essential means of enabling the use of

intelligent machines for assembly processes, and they make use of Design for Assembly and

Smart concepts [Ref. 4].

For site assembly of prefabricated modules

using conventional construction site plant

equipment, conical paired assembly connectors

allow auto-centering of modules. A computercontrolled 1/5 scale crane was built for

evaluation of this approach to site assembly of

large modules [Ref. 5]. Snap-fit structural connectors for modules and panels have also

been developed, using plastic compression

spring fastenings.

A universal services connector provides a

highly standardised factory fitted system,

where traditionally a variety of tradesmen are

176
involved on site. The object here was to develop a connection system that not only

reduces pure on-site assembly time by use of a

fast mechanical connection, but also brings a

substantial reduction of the total assembly time

by off-site integration of trades (Figure 3). It will thus be possible to increase added value in the factory and deliver components of large

manufacturing depth and a high degree of

prefabrication to the construction site. In addition to the cost advantages, quality

improvement is assured.

4.4 Cyber-agent technologies

Cyber-agents as decision-making aids have

many potential applications in both on and offsite construction processes. The project has

investigated some specific examples,

addressing agent communications issues

extensively, covering agent-agent as well as agent-human operator interactions. The lack

of international standards, security, and

network bandwidth are seen as the main

problem areas in their implementation.

A materials delivery agent was developed as a demonstration of this technology. Using

electronic tagging devices attached to individual components, the delivery cyberagent tracks parts, reconciles items with

orders, and interfaces with the construction

database. Information is stored in attached 'e- tags', which for the type selected have up to 64Kb memory.

4.5 Visualisation developments

Visualisation methods provide support on

several levels in this project. VR is employed

to complement the Kit-of-Parts, providing a common virtual environment to be shared by

clients, architects, engineers, constructors,

maintenance providers, etc. Thus clients can

be led through the virtual design of their house,

which is created on-line using prefabricated

components from the Kit-of-Parts.

In addition to the house model, a simulation of

the construction process of the house is provided, allowing examination of cost, quality

and time parameters [Ref. 6].

The design environment within which the user can create a design from its constituent

prefabricated components (Figure 4). A 3D

window (top left) lists the components

available from the current library. The user can

select a component and view it in 3D; they can

then choose to add the component to the

design, using collision detection and constraint

based modelling techniques to ease the

interaction process. As the design process

proceeds, a window within the environment

keeps the user updated with the total component cost of the design.

The user then moves to the construction

environment for an animated simulation of the

construction process (Figure 5); this includes a tower crane and other virtual site equipment.

4.6 Performance and economics

Space limitations preclude adequate

presentation of many of the innovative

contributions from this large partnership,

especially those relating to the use of IT. The

research has included developments required

to ensure a satisfactory whole-life performance

for the products, and to deliver good value for

money. Building physics issues have included

structural analysis, thermal characteristics and

ventilation issues, acoustics, seismic

performance, regulatory, sustainability and

ecological requirements - especially those

regarding material choice and reuse. These,

together with architectural, aesthetic, and

environmental considerations are clearly

essential to any design for future housing.

As the main phase of this project ends, the

partnership believes that the FutureHome

project has significantly progressed the arrival in Europe of a fully factory-based approach to housing that exploits the benefits of today's

digital technologies. The use of visualisation

and mass-customisation concepts will, we

trust, avoid the greatest perceived danger, that of factory housing being associated with styles

that are bland and incapable of expressing

custom or culture. REFERENCES

[1] Yagi J., Automation & Robotics in construction

in Japan, Proc. 16* IS ARC, Madrid, Sep 1999, p.III [2} http://www.europahaus.de

[3] Davies J.M., Steel framed house construction. The Structural Engineer, Vol 78 No. 6, Mar 2000.

177
[4] Wing R.D., Factory Housing - Making the Connections. Proc. 17* ISARCJaiwan, Sep 2000,

Keynote, p. 33.

[5] Balaguer C. et al, FutureHome: An Integrated

Construction Automation Approach, IEEE Robotics

& Automation, Vol.9, No.l, Mar 2002, p. 55.

[6] Murray N. et al, A Virtual Environment for Building Construction, 17th ISARC, Taiwan, Sep

2000, p. 1137.

FIGURES

Figure 1 . I-KOP Building system Figure 3 . Services connector prototype

Figure 2. Top level IDEFO

process diagram

USED AT: AUTHOR: llBlA>:ll DATE: rafflom MORKWG READER DATE CONTECT: trmfcr. FniRHoa<D«igi*Haiia«N OISAPT

MQTes; 12946677910 PUILCATOK »-0

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Design and manufacture FH products

Figure 4. Virtual design environment Figure 5. Virtual construction site

178
AUTOMATION IN BUILDING DESIGN WITH SPATIAL

INFORMATION

Tang-Hung Nguyen

Assistant Professor, Department of Civil Engineering, Nortli Dakota State University,

120D CME Building, Fargo, ND 58105 - Tel.: (701) 231-8646 - Email address:

hung, nguyen ©ndsu.nodak. edu.

Amr A. Oloufa

Associate Professor and Director of Construction Engineering Program, Department of

Civil and Environmental Engineering, University of Central Florida, P.O. Box 16245,

Orlando, FL 32816 - Tel.: (407) 823-3592 - Email address: aoloufa@mail.ucf.edu

Abstract: While current CAD (Computer-Aided Design) systems provide a variety of data

representation schemes (e.g. wire-frames, surface, and solid modeling) and data exchange

protocols, they fail to address automation issues in retrieval of building information to be used

in different AEC (Architecture, Engineering, and Construction) applications. In these CAD

systems, topological information (also known as spatial relations) describing the three- dimensional spatial relationships between building components is conventionally represented in a manual fashion into data models. The manual data representation, however, inherently is a complex and challenging task due to the wide variety of spatial relationships. This paper outUnes a computer-based building design framework with emphasis on the engine capable of

automatically deducing topological information of building components, which support various

aspects in building design such as constructabiUty analysis, construction planning, and building

code compliance checking.

Keywords: Computer-Aided Design, Topological Information, Automated Building Design

Systems, Sohd ModeUng.

Introduction

Presently, most CAD systems provide

two major tools for representing data of

building components: the geometric modeling

system dealing with spatial abstractions and

the database management system dealing with

functional information. The spatial information

describes the building components' geometry

((i.e. dimensions and locations) and topology

(i.e. spatial relations among the components),

while the functional data represents all the

other discipline-specific properties of the

components (e.g. structural, thermal properties,

design constraints, and building regulations).

Formal representation of spatial data in general

and topological data in particular of building

components is a complex and challenging task

in developing building design systems. The

complexity is in part due to the fact that each

professional usually utilizes his/her own

representation of topologies and

dimensionalities to express spatial information of

building components. Furthermore, different

design tasks require different types of topological

information. For example, information about the

walls surrounding a particular space (e.g. fire zone) is needed for code compliance checking of

that space, details of connections between

individual structural members of a reinforced concrete frame should be provided for reasoning

about constructabiUty, and information about the

adjacency among floors of a high-rise building is required for planning the sequence of construction

activities. The variety of topological information to be used throughout the design and construction

process may contribute to complexity in data

definition, representation and retrieval. Moreover,

the topological information of building/product

elements is conventionally structured directly in product data models, in which designers are prompted to manually specify spatial information

of interest to different disciplines. Such a manual

representation is usually subject to data

inconsistency, incompleteness, and prone to error.

179
which may result in a misinterpretation of

information. Thus, the topological information

should be classified and modeled in such a way that the required spatial data for a

particular design task (e.g. energy analysis,

building code compliance checking,

constructability reasoning, and construction

planning) can be automatically retrieved. This

paper attempts to identify and classifies various topological information commonly

used in AEC disciplines into more specific

categories such as adjacency, connection,

containment, separation, and intersection.

These topological relations are then

incorporated into a CAD system so that the

required spatial relationships between building

components can be automatically deduced to support different design tasks.

Classification of Topological Information

The first step taken in the development

of the proposed building design system is to identify various topological information (i.e. spatial relations between building components)

commonly used in the AEC domain. The

spatial relations are then classified into several

main categories to support automatic deduction

of building information required by different

project participants. Five main categories of

the topological information have been

identified and named separation, adjacency,

connectivity, intersection, and containment.

• Separation: refers to the relation where

two building components are physically separate from each other. Information about the separation

relation of a building component with

others can be used to check for its code compliance. For example,

"Individual roof panels shall be

separated from each other by a

distance of not less than 4 feet measured in a horizontal plane"

[BOCA Subsection 2607.2, 1993],

implies the requirement of a separation between two roof panels.

• Adjacency: is introduced to express the

type of vicinity that may exist between

building components. Depending on the

location of one component relative to another one adjacent-to it, the vicinity

relations may be represented by different

terms, such as next-to (e.g. mechanical room is next-to electrical room), above,

below (e.g. parking space is below lobby

area), right-hand-side, and left-hand-side.

• Connectivity: relates to modeling

connected-to, attached-to or supported-by

relations between building components.

For examples, a suspended acoustical tile ceiling is connected-to a concrete frame, a

rigid insulation is attached-to a protected

roof membrane, and a beam is supportedby a column.

• Containment: corresponds to contained-in

or included-in relations. This type of

topological information can describe the

spatial relationships between two spaces

(e.g. an incinerator is contained-in a room

space), two building components (e.g. a window is contained-in a wall), or between a building component and a space

(e.g. an air duct is contained-in a ceiling

space or plenum).

• Intersection: represents shared-by

relations. A typical application of this type

of topological information is that the

intersection between a tower crane's boom

and an existing building helps verify for

constructability of a new building where

the available tower crane is selected for

material delivery.

The classification of topological relations provides

a basis for establishing a building data structure

facilitating the organization and management of

various topological relations in a building data

model. Such a data structure is helpful in making it easy to develop algorithms responsible for the

automated deduction of spatial information in the

proposed computer-based building design system.

The Automated Building Design System

Basically, the proposed computerbased building design system is built on top of

180
a 3D (three-dimensional) solid modeling

system and is capable of automatically

deducing various topological relationships

between building design objects (e.g.

beams, columns, windows, walls, etc.). To

achieve such an automated design system,

the algorithms for deduction of the five

main categories of topological relations

described above must be developed

beforehand.

Deduction Algorithms

As the proposed building design system is developed in a 3D solid modeler, such solid

primitives as vertex, edge, face, cell, and loop

are used to describe each building objects. The

geometric and topological information about

theses primitives can be extracted from the 3D

CAD system to deduce the spatial relationships

between building objects. Basically, the

relationships between vertices and faces

representing building components determine

spatial relationships between those

components. There are three possible

relationships between a vertex and a face, i.e. the vertex could lies on the face, to the right or above, or to the left or below the face. This

leads to the need for a definition of face

outward normal vectors. For this study, all face

outward normal vectors are defined by the

right hand rule which takes the list of vertices

to be counter-clockwise and specifies the

outward normal to be the one giving the

positive value for points outside the solid

objects, as shown in Figure 1.

Figure 1. Convention for Face Outward

Normal

The building element to be considered for

illustrating the deduction of topological

information in the proposed system is the

space. Depending on the position of a vertex with respect to a face, the value representing

the vertex-face relationships can be assigned to -1,1, and 0, which indicates that the vertex is to the negative side of the face, that is, inside

the building space; 1 indicates that the vertex

is to the positive side of the face, thus outside

the space; and 0 represents those vertices that lie on the face itself.

Example: The algorithm identifies spaces that are adjacent-to, i.e. next-to, above, and below, a given

space, hi other words, the algorithm determines

whether the given space shares a common face

with any other spaces and all vertices other than

those defining the common face are outside the

given space. The development of this algorithm is based on several assumptions as follows.

1. All outward normal vectors of faces are defined by the right hand side mle which takes

the list of vertices to be counter-clockwise and

specifies the outward normal to be the one

giving a positive value for points outside the space.

2. All faces bounding a building space are planar

and defined by the following equation:

Ax + By + Cz -I- D = 0

3. The values obtained by the substitution of the

coordinates of the vertices in the equation of

the faces, i.e. Relation Indexes (RI), could be

positive, negative, or zero, indicating that the vertex is outside, inside, or on the space

respectively.

4. All faces comprising a building space are assumed to be convex. It is noticed that the

configuration of a building space can be either concave or convex, which is a critical issue. A

simple check can be made to differentiate

between the two: if a space has any face that gives a point inside the space with a positive

RI, the space is concave; if there is no such a

face in the space, it is convex. For simplicity,

the building spaces being considered in this work are assumed to be convex.

• Input: SI, S2, and S3 as spaces of a building

where SI 9^ S2 S3 (see Figure 2) • Output: SI is next-to S2 and below S3

• Algorithm:

1. For every vertex of S2 (or S3) and every face

of SI, determine vertices of S2 that lie on a

face of SI (i.e. vertices that give zero RI

values with respect to the face). These vertices

define a common face between SI and S2 (or

S3).

181
2. For vertices other than those of the

common face of S2 (or S3), compute the RI's indicating their positions with respect

to SI.

3. If the RI is positive and the outward

normal vector of the common face is parallel to XY plane, then S2 is next-to S 1

.

In the case of S3 that also shares a common face with Si and the outward

normal vector of the common face is perpendicular to the XY plane, then SI is below S3 or S3 is above SI.

Figure 2. 3D Models of Building Objects

For more elaborate examples and algorithms to deduce other categories of topological

relations, the reader may refer to [Nguyen,

1999].

The Proposed Building Design System:

Topolnfo

The algorithms for deducing the five

categories of topological information (i.e. adjacency, containment, intersection,

separation, and connectivity) have been

implemented into a computer-based building

design system, named Topolnfo. Topolnfo is developed on top of AutoCAD Release 14 that provides the underlying geometric solid

modeler, in which building components such

as columns, beams, slabs, windows, doors, etc. are described as 3D solids. Once the building

components have been inputted as 3D solid

objects, the basic data including geometry and

topology about their primitive representing

elements (i.e. vertices, edges, faces, and loops)

are created and stored in AutoCAD database.

These basic data then can be extracted by means of deduction mechanisms and

algorithms to deduce spatial relationships

between the building components. This can be

done by executing a new command, named

CheckTopo, which has been developed using an AutoCAD application development tool

(e.g. ObjectARX) and added to the AutoCAD

system. The process of the deduction can be

summarized as follows:

First, from the AutoCAD drawing editor, the user

is prompted to input geometric data and dimension

(X-side, Y-side, Z-side, and location) describing

the desired 3D building objects. The AutoCAD

interface provides high-level and precise

mechanisms for manipulating various types of

geometric data structures and high-level geometric

modeling objects such as prism, cylinder, polygon,

line, etc. for creating basic design objects such as columns, beams, slabs, walls ... as shown in Figure 3. These basic objects can be "assembled"

to create more complex building objects such as rooms, floors, or construction zones. At the lowestlevel data structures, the basic objects are represented as 3D solids by means of primitive

elements such as vertices, edges, and faces whose

basic information are stored in AutoCAD database.

Then, a new AutoCAD command (namely

CheckTopo) that is added into the Topolnfo

system is called to extract the basic geometric data

from the AutoCAD database and check for

topological relations between the building objects.

This command basically contains a number of

functions or methods being developed based on the

deduction algorithms described previously. These

functions are implemented into the Topolnfo

system as a deduction engine, which is responsible

for extracting basic 3D geometric information of

building objects and deducing spatial relations

between these objects. Finally, the output

including the deduced topological relations can be

stored and retrieved, when needed, to support

different tasks of building design such as construction planning, constructability reasoning,

and code compliance checking. The output can

also be displayed in AutoCAD screen providing

designers with a quick feedback on spatial

relations (e.g. interference, conflicts) among

building components.

182
i!

{{ Applications of Topological Information

Information about topological relations is

! essential to different AEC professionals

throughout the project life cycle, spanning

from building design to construction planning

and maintenance. Examples of the applications

of topological information to building design

and construction, in general, include the

following:

• Structural engineers require information

about connections between individual

I structural elements for structural performance analysis or constructability

evaluation,

I • Architects are more concerned about the

adjacency and intersection between

building spaces and their boundaries for creation of building shapes and space

layouts,

• Building inspectors need information (e.g.

thermal properties) of the surrounding

walls of a particular type of space for building code compliance checking.

• Lighting designers need information (e.g.

glazing areas) of windows and/or doors

contained in exterior walls for day lighting

load calculations.

• Construction planners need information

about the vicinity among construction zones for determining the

interdependencies of construction

activities to be performed in various

spaces, and

• HVAC engineers use topological relations

between spaces and their enclosing

structures for heat-loss calculations and

thermal analysis.

Conclusion

Various types of spatial or topological

relationships among building components have

been identified and classified into five main

categories, i.e. adjacency, containment,

intersection, separation, and connectivity

which are essential building information to be

repeatedly shared and reused by project

participants throughout the design and

construction process. This classification is

helpful in facilitating the grouping and

management of various topological relations in a computerized building data model. The

implementation of the proposed building design

system, namely Topolnfo, demonstrates the

feasibility and practicality of using 3D solid

modeling environment to develop a building

design system capable of automatically generating

complex building information such as spatial

relations among building components, which can be retrieved to support different building design

activities such as construction planning,

constructability reasoning, and code compliance

checking.

References

Augenbroe, G.: "COMBINE II: Computer Models

for the Building Industry in Europe", Final Report,

Technische Universiteit, Delft, Netherlands, 1995.

Bjork, B.: 'The Topology of Spaces, Space

Boundaries and Enclosing Structures in Building

Product Data Models", the CIB W78 Workshop on

Computer-Integrated Construction, Montreal,

Canada, 56-92, 1992.

BOCA: "The BOCA (Building Officials and Code

Administrators) National Building Code", 12"^ Edition, Building Officials and Code

Administrators International, Inc., Country Club

Hills, IL, U.S.A, 1993.

Fischer, M.: "Automating Constructability

Reasoning with a Geometrical and Topological

Project Model", Computing Systems in Engineering, 4(2-3), Great Britain, 179-192, 1993.

Ikeda, M., Oloufa, A.A., and Sekihara, S. "An

Object Oriented Environment for the Construction

Planning of High Rise Buildings", Proceedings of

the 13"' International Symposium on Automation

and Robotics in Construction, Tokyo, Japan, 411-

420, 1996.

Nguyen, T.H.: "Automated Deduction of

Topological Information in a Computer-Based

Building Design System", Ph.D. Dissertation at Department of Architectural Engineering at the

Pennsylvania State University, University Park,

PA, U.S.A, 1999.

183
Shaked, O. and Warszawski, A.: "KnowledgeBased System for Construction Planning of

High-Rise Buildings", Journal of Construction

Engineering and Management, ASCE, 21(2),

172-182, 1995.

ObjectARX: "ObjectARX Software Development

Kit for AutoCAD Release 14", Autodesk Inc., U.S.A, 1998.

+v / ' /

S3

/

SI S2

/ /

Figure 1 . Convention for Face Outward Normal Figure 2. 3D Models of Building Objects

W| AutoCAD - PDTesIl ^ File EcSt View Inseit Formal Tods Draw Dimension Modify Help

1 #1^1 ^^1 ^4

LlJ jCommand

ri9a3b3i.-306.61 TaaoooQ

' ^'[v;: ; ' MODEL TILE

Figure 3. 3D Model of a Typical Building

184
GENETIC ALGORITHMS FOR ACCESSING ENGINEERING PERFORMANCE

by

Luh-Maan Chang' and Lei Zhang^

ABSTRACT

The performance of engineering activities has significant impacts on the successfulness of

implementing industrial construction projects. Improving engineering performance can lead to better project outcomes. Previous studies on engineering performance improvement have either

focused on the use of certain techniques or products, or looked at specific engineering processes or areas. There has been a lack of a systematic and analytical approach that improves

engineering performance based on the understanding of the relationships between engineering

inputs and project outcomes. The paper proposes a generic model, which integrates genetic

algorithms with artificial neural networks, for modeling engineering performance measurement

and improvement in industrial construction projects. Due to their robust and efficient search

ability in complex situations, genetic algorithms are employed to search for solutions to improving engineering performance with the searching criteria, fitness function, being the neural

networks that establish the relationships between engineering inputs and project outputs.

KEYWORDS: engineering performance, genetic algorithms, artificial neural networks

' Associate Professor, Division of Construction Engineering and Management, School of Civil Engineering, Purdue

University, West Lafayette, IN 47907, 765-494-2246, changlm@ecn.purdue.edu

' Doctoral Research Assistant, Division of Construction Engineering and Management, School of Civil Engineering,

Purdue University, West LafayeUe, IN 47907, 765-494-0696, zhang41 @ecn.purdue.edu

Industrial construction projects have been

experiencing unsuccessful implementation of

projects for a long time. An industry survey

(Post 1998) reported that one-third of the

projects surveyed was over budget and nearly

half was delivered late. The development of an

industrial facility spans over five stages: preproject planning, detailed design, procurement,

construction, and start-up and commissioning

(CII 1997). Early researches addressed the

impact of engineering performance on the

overall outputs of a project. For example, design

errors, changes and omissions could constitute

approximately 10% of the total installed costs of

a project while construction mistakes account

1. INTRODUCTION

for only about 2% (Davis et al 1989). 25% of the

facility owners surveyed by Post (1998) ranked

detailed design as the weak link in the process of

facility development.

The Research Team 156 (RT-156) of

Construction Industry Institute (CII) studied the

industrial project data collected by CII

Benchmarking and Metrics Committee. The

study reported that the detailed design phase was

a prime source of project schedule delays and

that about half of the project scope and

development changes were initiated during the

detailed design phase. The report also pointed

out that design errors were the utmost source of

field rework and that design-related field rework

surpassed that initiated by both owner and

constructor (Georgy et al 2000).

185
Since industrial projects involve huge amount of

investment, even a small percentage of cost overrun or schedule delay will result in serious

economic loss. Therefore, there is an urgent

need to improve project outputs through

improving engineering performance. This

research aims at searching for approaches to improving engineering performance in industrial

construction projects through integrating genetic

algorithms with artificial neural networks.

Engineering refers to the detailed design phase

of an industrial project.

2. PREVIOUS STUDIES ON

ENGINEERING PERFORMANCE

Engineering is a systematic process with inputs

and outputs. Engineering performance

measurement deals with the output side. The

ability to successfully perform the engineering

and design activities on an industrial

construction project depends on various project

input variables (i.e., project attributes and

conditions), which are essential in driving its engineering performance. There was a lack of

analytical scheme that can approximate the

cause-effect relationship between engineering

inputs and outputs until the research work of

Georgy (2000) and CII RT-156, which is part of

the foundation of this research study.

CII RT-156 identified a total of 25 engineering

input variables and ten engineering performance

measures, as shown in Table 1 and Table 2

respectively. A neural-fuzzy system was

developed for establishing the relationships

between engineering inputs and engineering

performance measures. A multi-attribute utility

function was used to aggregate the performance

measures into a composite index to indicate the

engineering performance level (Chang et al

2001 and Georgy 2000).

Researchers in the past tried various approaches

to improve engineering performance, but most

of their approaches are qualitative in nature and

have certain limitations. The limitations come

from the fact that some approaches promote the use of a specific technique or product and some

look at specific areas of engineering and design

activities (Armentrout 1986, Atkin and Gill

1986, Breen and Kontny 1987, Choi and Ibbs

1990, Ginn and Barlog 1993). There is a lack of

a systematic and analytical approach that looks

at improving engineering performance based on

the understanding of the relationship between

engineering performance and its driving factors.

3. THEORIES

3.1 Artificial Neural Networks (ANNs)

ANNs are an information processing technology

that simulates the human brain and nerve

system. Their basic element is also called neuron

(or node). All neurons are organized in layered

structure and connected with weighted links. There is always an input layer where the initial stimulus happens, and an output layer where the

final reaction of the system is shot out. ANNs'

two major functions are learning and recall. Learning is the process of adapting the

connection weights in an ANN to produce the desired outputs in response to inputs. Recall is the process of producing outputs in accordance

to specific inputs using the knowledge obtained

through learning (Tsoukalas and Uhrig, 1997).

3.2 Genetic Algorithms (GAs)

GAs are robust general-purpose search program

based on the mechanism of natural selection and

natural genetics (Holland 1972). Genes and

chromosomes are the fundamental elements in GAs. A chromosome is a string of genes. In a

real problem, genes are the variables that are considered influential in controlling the process

being optimized, and a chromosome is a solution

to the problem. GAs search for the optimal

solution from populations of chromosomes. In

this research, the genes are the 25 input variables

in Table 1. A chromosome is a set of the 25

input variables. There is an objective function

(preferably called fitness function) in GAs. The

search process seeks the maximum or minimum

value of the fitness function.

4. MODELS

The fundamental approach of the research is to employ GAs to search for the engineering

186
performance inputs that lead to optimal

engineering performance. The ANN system

shown in Figure 1 serves as a complicated

fitness function. Two models were built. Engineering Performance Index Model (EPI

Model).

GA-ANN-Integrated Search Model (GAANN Model).

4.1 EPI Model

EPI model is in essence the framework of CII

RT-156. As illustrated in Figure 1 and Figure 2,

EPI model is comprised of two parts. The first part is 10 neural networks that establish the

relationships between the 25 engineering inputs

and the 10 engineering performance measures

respectively. The second part is a multiple

attribute utility function that takes the outputs

from the 10 neural networks in the first part as

its inputs and translates them into a composite

utility score, engineering performance index.

The 10 neural networks, after being trained, can

predict performance measures for given

engineering inputs. The 10 engineering

performance measures depict, from different

perspectives, the quality of outputs of

engineering activities. However, if it is required

to evaluate a project or to compare it with

another one, it will be hard to make the

judgment when 10 varying measures are presented. Therefore, there comes the need for a

single composite measure that indicates the

overall level of engineering performance and

contains the information embedded in the 10

measures. Through multiple attribute utility

function, an engineering performance index is defined on the scale of [0, 1] with 0 depicting

the poorest engineering performance and 1 the

best performance.

Thus, through the trained neural networks, if given engineering inputs, EPI model can make

prediction on engineering performance through

both a group of 10 different measures and an

overall engineering performance index. The set of 10 measures gives a comprehensive view of

engineering performance. The engineering

performance index will be used as fitness function value in GA-ANN model.

4.2 GA-ANN Model

GA-ANN model, as shown in Figure 3, depicts a

typical genetic search process. Its most

distinguished feature is the fitness function, EPI

model, where the GA-ANN integration happens.

GA-ANN model searches the engineering inputs

that lead to better engineering performance. The

genetic search starts with an initial population.

The initial population is comprised of a number

of individuals. Each individual is a chromosome

consisting of 25 genes, each of which

corresponds to an engineering input in Table 1. For a given project, the input variables related to basic project attributes including general project

attributes, general owner attributes and general

designer attributes (refer to Table 2) will be kept

constant throughout the genetic search; all other

input variables subject to the changes in the

actual project execution will be manipulated by

genetic operations in order to form better combinations of the variables.

GA-ANN evaluates all individuals, keeps the

good ones, reproduces the good ones, and

sometimes transforms the good ones to make

even better ones, . . . until satisfactory individuals

are produced. First of all, the individuals in the

initial generation are evaluated through the

fitness function, EPI model. First, Each

individual is presented to the 10 trained neural

networks that predict its 10 corresponding

engineering performance measures. Second, the

multiple attribute utility function transforms the

10 predicted measures into a composite

engineering performance index, which is the

fitness function value of the individual.

Then, the initial generation goes through the

genetic operations: selection, reproduction, crossover and mutation. First, the individuals

with higher fitness function values get selected

and the worse ones eliminated, which means that the engineering inputs that create better engineering performance are kept. Second, the

selected ones are reproduced and crossovered.

Lastly, a certain percentage of the individuals go

through the mutation process which transforms a

certain number of genes of the individuals. The

187
mutation process might make the mutated

individuals better or worse. Thus, the second

generation is formed.

The second generation also goes through fitness

evaluation, selection, reproduction, crossover and mutation. Some individuals better than those

in the second generation are assembled and come into the third generation. The general trend

is that the individuals become better and better from generation to generation. In other words,

the level of engineering performance becomes

higher and higher.

The genetic search process keeps going on until a certain termination criterion is met. Usually

the termination criterion can be a desired fitness

value, the maximum number of generations, or computation time. By the time the process stops, one or more sets of engineering inputs will be

identified as the ones that lead to an engineering

performance level close or equal to the desired

level.

4.3 Relationships Between the Models

EPI model establishes the relationships between

the engineering inputs and engineering

performance measures and aggregates the measures into a composite index to indicate the

level of engineering performance. GA-ANN

model does the genetic search for better engineering performance using EPI model as the

fitness function while EPI model provides

engineering performance prediction for given

engineering inputs.

5. ANTICIPATED APPLICATIONS OF

THE MODELS

For past projects, GA-ANN model and EPI

model work together to search better

engineering performance and the corresponding

engineering inputs. Then, the actual engineering

inputs can be compared with the those searched

by GA-ANN model and the comparison might

be able to indicate what could have been done to achieve better engineering performance.

For future projects, GA-ANN model looks for

the possible better engineering inputs and

outputs for the project. These anticipated project

inputs and outputs might act as the guideline and

goal for the actual project execution.

6. DATA ANALYSIS

The project data for validating the proposed

models are being collected by the authors. The

result of data analysis is expected to be

presented at the conference.

7. CONCLUSIONS

This paper proposed a systematic approach to improving the practice of engineering

performance. The fundamental idea is to find the

possible best practice of engineering activities for a given project. To pursue this, genetic

algorithms and artificial neural networks are employed to build the models. Artificial neural

networks provide the ability to establish the

relationships between engineering activity inputs

and engineering performance outputs, and

genetic algorithms serve as a search engine to find the possible best engineering practice based on the relationships between engineering inputs

and outputs identified through artificial neural

networks.

8. REFERENCES

Armentrout D. R. (1986). Engineering

Productivity Management and Performance

Measurement. Journal of Management in Engineering 2:3, 141-147

Atkin B. L. and Gill E. M. (1986). CAD and

Management of Construction Projects. Journal

of Construction Engineering 112:4, 557-565

Breen W. C. and Kontny V. L. (1987).

Automation's Impact on Engineering Design

Progress. Journal of Management in Engineering 3:4, 275-287

Chang L. M.„ Georgy M. E. and Zhang L. (2001). Engineering Productivity Measurement.

Research Report, RR156-11, Construction

Research Institute, Austin, TX

Choi K. C. and Ibbs C. W. (1990). Costs and

Benefits of Computerization in Design and

Construction. Journal of Computing in Civil

Engineering ASCE 4:1, 91-106

188
CII (1997). Determining the Impact of Process

Change on the EPC pprocess: A Model to Quantify Time Cost Improvements. Report,

IR125-2, Construction Industry Institute, Austin,

TX

Davis K., Ledbetter W. B. and Burati J. L. (1989). Measuring Design and Construction

Quality Costs. Journal of Construction

Engineering and Management ASCE 115:3,

385-400

Georgy M., Chang L. M. and Walsh K. (2000).

Engineering Performance in Industrial

Construction. Proceedings for Construction

Congress VI, ASCE, Orlando, FL

Georgy M. (2000). "Utility-based Neurofuzzy

Approach for Engineering Performance

Assessment in Industrial Construction Projects".

Ph.D. Dissertation, Purdue University

Ginn D. and Barlog R. (1993). Reducing

Complexity and Working with Bottlenecks

Improves an Oil Refinery's Engineering

Performance. National Productivity Review,

Winter 1993/1994, 63-77

Holland J. (1975). Adaptation in Natural and

Artificial Systems, The University of Michigan

Press Post N.M. (1998). Building Teams Get High

Marks. Engineering News Record 240:19, 32-39

Tsoukalas L. H. and Uhrig R. E. (1997). Fuzzy

and Neural Approaches in Engineering, John

Wiley & Sons, Inc.

Table 1 Engineering Input Variables

Category Variables

General project attributes Project size (total installation cost) Contract type

Keiduve size ui projeci compdrcu lo projecis oi ine same inuusiry lype

Relative level of complexity

Site conditions

Legal and environmental conditions

General owner attributes Owner profile and participation

Newness of process technology to owner Owner previous experience with designer

General designer attributes Split engineering practices

Designer qualifications and capacity

Newness of process technology to designer

Project schedule Design schedule

Design-construction overlap

Project information inputs Completeness of scope definition Completeness of objectives and priorities

Completeness of basic design data QuaUty of constructor input and constructability

Quahty of vendor data Level of automation Use of 3D CAD modeling

Use of Integrated Databases (IDB

)

Use of Electronic Data Interchange (EDI)

Project changes Percent TIC scope changes

Change management procedure

Change communication system

189
Table 2 Engineering Output Variables (Engineering Measures)

Category Variables

Detailed design value % design rework

Design document release commitment

% detailed design schedule delay

% detailed design cost overrun

Fabrication and construction value % fabrication and construction schedule delay due to design deficiencies % fabrication and construction cost overrun due to design deficiencies % construction hours for design problem solving and field design

% estimated dollar savings due to constructability

Start-up and commissioning

value % start-up schedule delay due to design deficiencies % start-up cost overrun due to design deficiencies

Engineering

inputs

Input 1 Input 2

Input 25

Neural networks

Engineering

11^ performance

measi»-es

Multi-attribute

utility function

Engineering

Z:^ performance

index

Figure 1 . EPI Model ~ General Idea

Neural network 1 | Measure i |

Neural network 2 - Measure 2

neural network 10 - Measure 10

J--J Multi-attribute

utility function

Engineering

performance

index

Figure 2. EPI Model — Breakdown

Fitness Function - EPI model -

Actual

engineering

inputs

t

Start

Evaluate

fitness function

Are termination

criteria met?

Generate new

population

no

Selection

i

Crossover

Mutation

yes Near optimal

engineering inputs

i

Result

Figure 3. GA-ANN Model

190
Mixed Reality Benefits For Design Perception

by

Phillip S. Dunston', Xiangyu Wang", Mark Billinghurst\ Ben Hampson"*

^Construction Engineering and Management Division

School of Civil Engineering

Purdue University

West Lafayette, Indiana

(dunston @ecn.purdue. edu ) 'Department of Civil and Environmental Engineering

University of Washington

Seattle, Washington

^Human Interface Technology Laboratory

University of Washington

Seattle, Washington

'*The McKinstry Company, Seattle, Washington

ABSTRACT: Design visualization is key to the communication and shared perception of designs

and is essential for meaningful design development and collaborations. The initial development of

an Augmented Reahty Computer Aided Drawing (AR CAD) system for enhancing visuahzation of

models created in standard CAD was presented at the 17th IS ARC. AR CAD features a more

natural mode for changing views of the model and completely understanding the model content. Expected benefits are improved efficiency in the design detailing function, both for the individual

detailer and for design collaborations where maintaining an accurate shared understanding of the design model is critical. An experimental program is under way to examine the impact of AR CAD

upon a user's perception and recall of a design model. Related experiments with desktop and

immersive virtual environments have found that motion cues can indeed markedly improve spatial

cognition. It is expected that we will see the same benefits in our AR CAD system, although until now such studies have not been conducted in an AR environment. This paper presents the rationale for experiments to measure the impact of AR CAD in terms of cognition cost, and it lays the foundation for further appUcation of Mixed Reality (MR) technology to the design, construction,

and maintenance phases of a facihty's Ufe cycle. MR applications may prove promising for

effective communication of designs for prefabrication, site installation, and the planning and

excecution of maintenance operations.

KEYWORDS: 3D CAD; Augmented ReaUty; Mixed Reahty; spatial cognidon; visualization; Virtual Reahty

Recognizing 3D CAD and walk-through software

as the state-of-the-art for visualizing design

details. Augmented Reality Computer Aided

Drawing (AR CAD) was introduced at the 17th

ISARC [1]. In addition to providing an alternative

three-dimensional view of construction models, it

1. INTRODUCTION was proposed that experimentation with the

spectrum of Mixed Reality as illustrated by

Milgram and Kishino [2] in Figure 1 could open

the door to more modes of interaction with design

content than is currently available through typical

CAD software. Alternative interface metaphors can be developed and tailored to facilitate development and communication of designs.

Thus, our work is aimed at determining the

191
appropriate MR modes for planning, design,

construction, maintenance and the associated

interface tools.

Augmented Reality (AR) occupies that place in the

continuum where virtual objects are inserted to a predominantly real world scene. AR also allows

virtual enhancements to physical interface objects.

MR offers a broader range of options for

interfacing with digitally based information. In our

present work we are interested in applying more

innovative AR techniques to the design phase of

the construction process, the AR CAD system is designed for exploring the benefits of supporting

design, and ultimately construction, with various

modes of Virtual Reality interfaces.

The AR CAD system utilizes fiduciary markers in the real world to position the model and allow the user to easily see it from any viewpoint. As such,

it offers the benefit of a very natural mode for

changing views of the model and completely

understanding the content than would be afforded

by visualization systems that have a more

constrained means of navigation. This feature is expected to improve efficiency in the design

detailing function, both for the individual detailer

and for design collaborations where maintaining an accurate shared understanding of the design

model is critical.

An experimental program is underway to examine

the impact of AR CAD upon a user's perception

and recall of a design model. Related experiments

with desktop and immersive virtual environments

have found that motion cues can indeed markedly

improve spatial cognition. It is expected that we

will see the same benefits in AR CAD, although

until now such studies have not been conducted in an AR environment. Positive results from these

experiments would confirm that AR CAD has the

potential to support the reduction of errors during

design detailing and the more rapid and effective

resolution of space conflicts interferences during

design collaborations. This stage of research lays

the groundwork for further application of MR

technology to the design, construction, and

maintenance phases of a facility's life cycle. MR

applications may prove promising for effective

communication of designs for prefabrication, site

installation, and the planning and execution of

maintenance operations.

This paper presents the updated description of the

features of the AR CAD system and also explores some spatial cogniton issues that may arise

associated with the system. We also explain the

rationale for experiments to determine the benefits

of AR CAD over standard CAD (AutoCAD in this instance) in conflict detection. Such experiments

constitute our first attempt to evaluate AR CAD

with regard to spatial cognition issues.

2. ARCAD SYSTEM

The AR CAD system has been modified for

improved performance over its predecessor

version. The current experimental facility can

provide the piping detailer with the ability to explore the CAD design in the non-immersive

(AR) virtual reality mode and still consists of the

following components as first described by

Dunston et al. [1] and shown in Figure 2.

Modeling Computer: The modeling computer runs AutoCAD and a specially designed AutoCAD

plug-in. The CAD detailer designs the model on

this machine and then sends the 3D model

information out to the AR computer using the

AutoCAD plug-in. The plug-in software uses standard network communication code to communicate between computers. Communication

can also be between modules in the same

computer. The current system functions on a

single desktop Pentium 4 PC with 1 .6 GHz.

AR Computer: The AR computer runs an Augmented Reality application that allows a user

to see virtual 3D models superimposed over a real- time video-recorded view of the real world. The

AR application is a custom application that is based on the ARToolKit library [3] and OpenGL

library [4] and a database, containing simplified

3D models of pipe structures in the VRML file format. The AR application receives the 3D model

information through the network communication

and then instantly creates a 3D virtual model of

the design.

192
Camera: Also connected to the AR computer is a Logitech QuickCam Pro 3000 Camera with video

capture of up to 640'^'480 pixels and frame rate of

up to 30 frames per second. The computer

performs image processing on the video image

' from the camera to find specially marked tracking

i cards. The camera's position can be calculated

from a tracking card and a virtual model overlaid on the card. The resultant composite image is fed

back into the desktop display for the user to see. The result is a view of the real world scene with a 3D virtual model overlaid on it (Figure 3). This

tracking technique enables the user to easily view

the model from any perspective above the card.

3. NEW FEATURES IN THE SYSTEM

Several feature modifications or additions have

been made to the AR CAD prototype. These

features are as follows:

l.New Graphics Library: The previous version of

AR CAD relied upon the LibVRML97 library for the rendering of virtual images while the newer version relies upon the OpenGL standard

for greater versatility and generation of more

stable virtual models. OpenGL is a graphics

library that is less memory intensive and

facilitates real-time interactions with the virtual models.

2. Automatic Conflict Detection: The program will

automatically detect any conflict or interference

appearing among the pipe objects. If there is a

conflict, the interfered objects will be

highlighted as wire frame elements on the screen rather than the default solid model

representation (see Figure 4). This task is accomplished using the boundary box feature of

OpenGL. A similar conflict detection function

has been developed by Shiau et al.[5] whose

application uses ellipses to identify interferences

in structures, appliances and piping systems in 3D models.

3.0bjects Selection and Manipulation: If a certain

object is selected (activated), the wire frame of

it will appear on the scene, which makes the

designer easily recognize which object is activated so that the user can use the mouse to move and scale any object activated and also use the keyboard to rotate the object along local

X, y, z axes. Brief information describing the

selected object will be shown as a text string in the bottom of the screen.

A zooming feature has also been added to the AR

module (see Figure. 5). Another potentially

beneficial function under development is a transparency mode. This rendering mode can

provide distant objects with a degree of visibility even if the view is obstructed by nearer objects.

Finally, we are in the midst of adding a fly-in

feature that will provide an immersive VR view of

the design space.

4. SPATIAL COGNITION COST

Since AR CAD presently acts mostly as an

assistant viewing tool for standard AutoCAD, the

chief issues that have arisen are those concerning

human spatial cognition. While 3D modeling is readily accepted as being less abstract and

therefore an intrisically more meaningful graphic

form for representing and communicating

complex designs, there are still open questions due

to the degree of separation from reality that yet

remains, questions relating to control of

perspective and user interface metaphors. Some

features or options of the AR CAD software raise

the question of costs and benefits of AR CAD

with respect to spatial cognition. That is, do the

spatial cognition benefits outweigh the cognition

cost associated with a viewing assistant mode?

Very limited research has been done on spatial

cognition issues associated with AR applications.

However, some testing results done by other

researchers indicate that subjects are able to acquire configuration knowledge of immersive

virtual environments in spite of the fact that the

subjects lack the benefit of spatial calibration

derived from physical movements through a real environment. In this paper, we are concerned with

the time cost of necessary cognitive processes.

193
During construction of spatial mental models,

switching perspective from one scene to another scene exacts a cost [6]. Cognition cost is a kind of

cognitive cost incurred by mental transformations

associated with the such changes as a new referent

object or frame, or change of a viewpoint while

switching perspectives. Perspective switching due

to transitions between AutoCAD and the AR

scene will incur a cognition cost (see Figure 6 for

comparison of AR CAD model and AutoCAD

model). However, presently, we don't know how

much spatial cognition benefit—a more natural

and more smooth navigation between

viewpoints—AR CAD can provide versus the

cognition cost of using the system as we have

designed it to presently operate.

To understand what that cost may be, we need to analyze what perspective switching entails. A

perspective consists of a referent object or frame

and a viewpoint. Each of these components

changes when perspective is changed. Each of

these changes requires different mental

transformations and cognition cost associated with

them. However, the relative costs of the

transformation are not yet fully known.

The method for changing viewpoint in the AR

scene is quite different from that used in AutoCAD. For AR scene navigation, the

viewpoint is embedded in real world background

and keeps changing as the user changes the

relative position between the camera and the

tracking marker. In contrast, standard CAD

software like AutoCAD has a single color

background with only a simple symbol referencing

the coordinate system origin. There is nothing else

in the scene to which the user can reference his or her viewing perspective. Furthermore, the

mechanisms for changing views is often not

intuitive.

Even though the relative position of each object in the AR scene is absolutely the same as the one in AutoCAD, another significant cognition cost will come from additional mental processing demands

for reconciling misaligned headings. When

transitioning between scenes (AR and AutoCAD)

in which models are misaligned, mental

calculations are required to account for the

different headings in each scene. This condition is very similar to alignment effects found for map

usage [7]. If an additional step is necessary to compute the direction of a location for misaligned

headings, there is a resulting processing demand

and cognition cost.

While there is indeed a cognition cost associated

with switching scenes or perspectives, in some

cases, the costs of switching may not be greater

than the cost of staying with the same scene. One

of the major advantages of AR CAD is a natural

and smooth transition between viewpoints making

it easier to locate any point or comer of the virtual scene quickly. However, the big drawback internal

to AR CAD is the cognition cost in transitioning

between the virtual scene in AR and the original

model in AutoCAD. There is a trade-off in utilizing these two viewing environments together.

However, right now, we do not know how much

spatial cognition benefit is associated with AR

CAD, nor how much cognition cost. If a specific

benefit is identified, then the cognition cost for

obtaining it can be measured for standard CAD

(AutoCAD) alone and for CAD equipped with the

AR viewing mode. This approach can be used to validate any sort of viewing assist mode or

function. For instance, conflicts or interferences can be identified in the AutoCAD view by means

of certain visible features or by transitioning to the

AR scene to use the automatic conflict detection

feature and then returning to AutoCAD to make

corrections. The simple measurement of time

indicates the relative cognition cost. We are performing such tests, incorporating statistical design to allow for differences between user

subjects and model complexity. Preliminary trials have indicated the AR viewer assist to be a worthwhile means for identifying conflicts

without increasing a detailer's overall time in

detecting conflicts.

5. CONCLUSION

This paper has presented an update on the

development of an Augmented Reality viewer

assist feature that turns standard CAD into AR

CAD and has discussed the importance of

considering spatial cognition issues in the

validation of this system. Future work will pursue

194
confirmation of AR CAD benefits for design

model perception for both individual users and

collaborating partners. These efforts will also

include feature enhancements to extend AR

CAD's applicability, such as more seamless

generation of the virtual models. The long term

objective is the validation of Mixed Reality as a

j useful technology arena for effecting human

interfaces with digitally based project design

information.

6. ACKNOWLEDGEMENTS

The authors are grateful to the McKinstry

Company of Seattle, Washington (U.S.A.) for

' their continuing cooperation in this research.

7. REFERENCES

1. Dunston, P.S., Billinghurst, M., Luo, Y. and

Hampson, B. 2000. Virtual Visualization For

The Mechanical Trade." International

Symposium on Automation and Robotics in Construction (ISARC), National Taiwan

University, pp. 1131-1136.

2. Milgram, P. and Kishino, F. 1994. "A

Taxonomy of Mixed Reality Visual Displays."

lECE Trans, on Information and Systems

(Special Issue on Networked Reality), Vol.

E77-D, No. 12, pp. 1321-1329.

3. ARToolKit information website.

http://www.hitl.washington.edu/research/share

d space/

4. Woo, M., Neider, J., Davis, T, and Shreiner, D.

1999. OpenGL Programming Guide, 2>rd edition, OpenGL Architecture Review Board,

Addison-Wesley Longman, Inc.

5. Shiau, Yan-Chyuan, Wang, Ming-Teh and

Yang, Chung-Ham. 2001. "The Application of

3D and Interference Detection in Construction

Engineering." Proceedings of the 18th

International Symposium on Automation and

Robotics in Construction (ISARC). E.Bundy

and J. Szlagowski, editors, pp. 95-100.

6. Tversky, Barbara, Lee, Paul and Mainwaring,

Scott, 1999. "Why do speakers mix

perspectives?" Spatial Cognition and

Computation 1(4), pp. 399^12.

7. Levine, M., Jankovic, I.N. and Palij, M., 1982.

"Principles of Spatial Problem Solving."

Journal of Experimental Psychology General

111(2), pp. 157-175.

195
Mixed Reality

Real Augmented

Environment Reality (AR) Augmented Virtual

Virtuality (AV) Environment

Figure 1. Mixed Reality encompasses all combinations of virtual and real.

Modeling

Computer

WndowsPC

AutoCAD®

Rug-in

AR

Computer:

ARTodKit

Computer Application

Network

y

HMD

Camera

Figure 2. Components of the AR CAD

prototype can operate on separate or a single

computer.

Figure 3. The real world scene is overlayed

with a 3D virtual model.

Figure 4. Wire frame representation

identifies object interferences.

Figure 5. A zooming feature allows close up

inspection.

- A

Figure 6. Views in AR and AutoCAD are not

usually so aligned when switching scenes.

196
AUTOMATION CONSIDERATION DURING PROJECT DESIGN

by

MATT M. HEWITT

JOHN A. GAMBATESE

ABSTRACT:

Automation as pertaining to the construction industry is the use of mechanical and electronic means to achieve automatic operation or control to reduce potential exposure, time, or effort while maintaining or improving quality. Contractors utilize automated technologies on projects as a means of saving cost, reducing project durations, improving quality and consistency, and gaining other related project benefits.

Communication between the constructor and designer of the construction means and methods to be used

is often limited as a result of contractual relationships and competitive bidding requirements. This

commonly leads the designer to assume conventional construction equipment will be implemented rather

than specialized automated technologies. For this and other reasons, designer consideration in a project's

design of the use of automated construction technologies is limited. This paper describes a study to investigate the ability of designers to consider the use of automated construction technologies in the

design of a project. The study identifies design practices that facilitate the implementation of automated

technologies and exposes barriers, within both the design process and the overall project development

process, to the consideration of automation in the design. The findings of the study can be used when one

is considering the implementation of construction automation technologies during the design process. KEYWORDS: automation, design, construction, constructability, equipment, robotics

1. INTRODUCTION:

Over the past few decades, improvements to productivity in the construction industry have

been insignificant compared with other

industries. Productivity improvements in other

industries, especially manufacturing, have

stemmed to a large extent from the effective

implementation of new technologies. The

introduction of new technologies in the construction industry to fully automate the building process has been limited. The same is true for heavy/highway construction. The

construction industry remains a craft-oriented

and labor-intensive industry with minimal

automation of tasks.

The lack of automation in the construction

industry can be attributed to many factors. One

of the hurdles to automating the construction

process is the design of a project. That is, the

design of a facility inhibits both the use of

available automated equipment during

construction and the successful development of new automated equipment. Furthermore, the

capabilities of automated equipment are constrained by the physical aspects of the

design. Minor modifications to designs can

potentially enhance the use of automation and

lead to increased construction productivity.

This topic was the focus of a research study to investigate the design practices that facilitate construction automation. This paper describes

the study efforts along with identified design

practices that enable construction automation

and barriers to designing for automation that were exposed.

Department of Civil, Construction and Environmental Engineering

108 Apperson Hall

Corvallis, Oregon 97331-2302

Phone: 541-737-8913

E-mail: john.gambates@orst.edu

197
2. RESEARCH METHODOLOGY:

The goal of the research study was to improve

the ability to prepare designs that facilitate the use of automated technologies in construction

work. Designing for construction addresses the

constructability of a project and, in this case, a subset of a project's overall constructability - "automation constructability". To meet this goal, the research effort included two objectives.

The first objective was to develop and

accumulate recommended design practices

which, when implemented, enhance the ability to automate construction activities. The

recommended practices reflect the capabilities

and limitations of current automated

technologies and the application of current design practices. Secondly, barriers to the use of

automated technologies in the construction

process as a result of design features, methods,

and deliverables were identified. Knowledge of

the barriers provides additional guidance in both

the planning and design processes.

Literature accessible through libraries and the

World Wide Web was reviewed to determine

relevant automated technologies available to the

construction industry. This includes

technologies which were under research and

development, but when ready would be available

to the construction industry. Automated

technologies were found world wide and filtered based on relative potential for use in the United

States construction industry. Technologies were

categorized according to the finished product

which they are used to create.

To determine industry usage of automated

technologies, a survey was sent to the top five

hundred contractors as ranked by Engineering

News Record (ENR). Companies were asked to respond to several specific questions concerning

industry perception, benefits, barriers, etc. of

implementing automated technologies. The

survey included several questions specifically

written to determine whether constructors found

value in implementing automated technologies.

Additional information was obtained through

interviews of industry personnel. Contractors,

designers, fabricators and personnel in other

industries were interviewed. Standardized

interviews were conducted through structured

questions concerning the benefits, barriers, and

limitations of automated technologies.

The contractor interviews were conducted from

the perspective of both the project manager and

equipment operator. Careful considerations were made to obtain a range of companies,

based on annual revenue. Design firms were

selected based on the type of designs produced

and employee count was used to determine their

relative size. Fabricators were also interviewed

to get another perspective concerning

automation. Interviews with fabricators were

based on the grouping of technologies available

to constructors and the potential for influence by

the fabricator. Recognizing that automation

exists in many other industries, interviews of

personnel in other industries were also

conducted to include information concerning

how well other industries have come to include

automated technologies.

3. RESULTS:

The survey of top contractors provided a list of

available automated technologies and questioned

whether each firm uses the technologies, has

considered using the technologies, would

recommend using the technologies to others, and

if there is a perceived value in developing the

technology. The survey intent was to determine

or attempt to quantify the level of automated

technology use by the industry. The survey

revealed that there is a strong prevalence in concrete and masonry construction of automated

mobile screeding, rebar bending, and concrete

surface treatment. In addition, responses

suggest that there is value in developing further

technologies for automating reinforcing cage

fabrication for beams and columns, and for

mobile bricklaying. Excavation and demolition

responses indicate that remote control soil compaction is used exceedingly more than other

technologies within the category. Automated

dump trucks and global positioning system

(GPS) aided excavation appear to be highly

considered applications for implementation, but

with little or no actual implementation. One

such implementation has proven to reduce cost

198
by thirty percent through the use of automated

trenching and pipe placement (Lee, Lorene, and

Bemold 1988). Inspection and surveying

activities show strong prevalence of robotic pipe

inspection; otherwise technologies have not yet

been greatly implemented for these tasks. For

structural steel construction, metal welding and

cutting systems are widely used and are recommended to other industry members. Also,

robotic welders are implemented extensively

amongst industry members. Lastly, material and

asset management technologies appear to have

developmental value amongst industry members.

Interview surveys consisted of questions

concerning best practices, barriers, and changes

to the design process or project design. The

following summarizes the survey results.

3.1 Contractor: PM & Equipment Operators

According to project managers, over seventy

percent of contractors interviewed use some

form of automated technology in construction

and over seventy five percent have considered

the use of automated technologies. Also,

implementation is attributed predominately to

cost, followed by production, and then quality.

Equipment operators perceive production, cost, and quality as benefits of automation and have

found through experience that production, cost, schedule, and quality are benefits of

implementation. Project managers are unified in agreement that having constructors and

designers working together to define automated

technologies that needed to be developed would

be of value.

3.2 Designer:

The survey results indicate that designers

typically do not formally consider construction

automation, but when it is considered, the

decision is based predominately on cost and

quality. Responses also suggest that not many

designers are aware of the automated

technologies available to contractors, nor does

there seem to exist any reference material for individuals seeking information concerning

automated technologies and design. While no

resources may commonly be used at this time, it

should be noted that there exists a website where

designers can go to gain information concerning

emerging construction technologies

(www.new-technologies.org/ECT/Index.html).

3.3 Fabricator:

According to the fabricators interviewed, design

for automation is based on cost and quality,

followed by productivity and safety. Similar

issues to those mentioned previously arise in the

fabrication of products and again there is a great

deal of value placed on the communication

between the designer and the

manufacturer/fabricator.

3.4 Best Practices

Accumulated from the literature review and

surveys were recommended design practices to

facilitate the use of automation during

construction. The practices can be categorized

as project-related and industry-wide. Projectrelated recommended practices are as follows:

• Conduct constructability reviews that incorporate consideration of

construction automation.

• Standardize building elements.

• "In order to optimize the use of

automated technology, it is important

that design principles based on the

technology are considered (Howe,

1998)."

• Provide adequate clearance for

automated technologies to operate.

• Prioritize design objectives (cost,

quality, safety, etc.) and compare design

alternatives. • Use electronic documents and make

them available to the contractor. • Consider the capabilities and limitations

of the automated technologies. Table 1 provides examples of design practices

related to various construction activities in which automated technologies and

equipment are notably evident.

With respect to the construction industry as a whole, it was recommended that the

199
technologies be marketed to designers and

owners. Primarily the technology manufacturers

would undertake this with assistance from

constructors. Many designers and owners

simply do not have enough exposure to projects

that implement automated technologies and, due

to this aspect, there is no benefit

acknowledgement concerning implementation of

automated technologies. Such marketing efforts would expose the designers and owners to the

capabilities and benefits of construction

automation.

3.5 Barriers

The study revealed numerous barriers to the

consideration of construction automation in the

design phase. As with the recommended design

practices, the barriers can be separated into those

that exist at the project level and those are present industry-wide. Project-level barriers are

as follows:

• Automated technology capabilities are limited and create tremendous costs when contractors attempt to match

project variability with automated

equipment variability. • Frequent changes/advances in the

technologies. Technological

advancement and improved design occur rapidly and many users cannot

keep up with the changes.

• The cost of owning and operating

automated technologies. • A lack of standard design elements.

Repetitious elements are likely to lead to

' greater utilization of automated

technologies. • "No two sites present the same

problems, and a layout suitable for one

site maybe quite unsuitable for another

(Cusack 1994)."

• A lack of consideration of the

construction phase by the designer, due

to the means and methods residing with

the constructor. Other barriers exist that are not necessarily

applicable to a specific project, but are representative of the nature and structure of the

construction industry. These industry-wide

barriers are as follows:

• Designers typically have limited

construction experience. There should

be pre-construction consulting between

the designer and constructor concerning

cost saving construction methods.

• Designers typically have limited

knowledge of automated technologies.

There should exist consulting between

designers and constructors concerning

automated technology availability and

potential implementation.

• Designers typically have limited

knowledge of the design practices,

which facilitate the use of the automated

construction technologies.

• A general lack of designer interest in considering automated technologies in their designs.

• The structure of, and the roles associated

with, the traditional design-bid-build

contracting method. Barriers exist

which limit the amount of pre- construction consulting and

communication that can occur.

• The traditional roles and responsibilities

of the designer. Traditionally the means

and methods of construction have been

the responsibility of the constructor. Consequently, a designer's ability to influence the implementation of

construction methods has gone unused

or unrecognized.

• Resistance to change from the

commonly used design practices.

• Some designers view change as high

risk, because there exists a level of

uncertainty and untested consequences.

Particularly risk associated with

implementing automation.

• Conflict of interest on public projects

when contractors are brought in during

design. Publicly funded projects are required to be competitively bid,

limiting the pre-construction

communication between constructors and designers.

200
• Lack of reference material available for

designers to use for consulting.

4. EXAMPLE OF AUTOMATION BENEFITS

The benefits of construction automation, and the

design impacts on the use of construction

automation, can be illustrated using a past

project on which a concrete extruder was

utilized. The project, located near Clackamas,

Oregon, involved the construction of a freeway

overpass. Nearly three thousand feet of MSE

retaining wall rails were constructed during the

two-year project duration, but not all of the

railing was extruded. The only railing that was

extruded was railing attached to wall "H". Wall

H is over 2000 feet long and the extruder

contractor completed the wall in two days.

Although wall H contained the longest stretch of

railing, there were other opportunities to utilize an extruder. Railing extending along another

wall, wall "P", and onto the bridge itself, was

less than 1000 feet in length and took the bridge

contractor over three weeks to complete.

Working crews for both walls were relative in

size. The railing along wall P and the bridge was not extruded, but could have been. The

extruder contractor pointed out that the railing on wall H had a vertical back and curved face,

allowing for optimal utilization of their extruder,

while the wall P and bridge railing did not. Also, there was a height difference between the

railing on wall P and the bridge railing.

Although attached, the height transition added to

the overall cost of extruding. Since the wall P

and bridge railing was under three hundred feet and required a change in shape configuration,

the extruder contractor could not competitively

compete against conventional construction

methods. Also, the railing on wall P and the

bridge had two vertical faces, which magnifies

any inconsistency and adds to the cost of using

an extruder. The extruder contractor added that having at least one curved face helps to reduce

visibility of inconsistencies to the human eye.

5. CONCLUSIONS: Implementation of automated technologies can

be greatly affected through the design process

when consideration is given to the contractor's opportunities for automation applications. This

is made feasible through fluid communication

between the constructor and designer. This

communication should optimally take place

during the design phase. If the designer is not

already knowledgeable about the construction means and methods to be used, it is beneficial if the constructor conveys the means and methods

for constructing the project to the designer and

at a minimum provides some evidence of the

automated technologies being considered for implementation. In addition, owners need to perceive the construction process in its entirety,

starting from the architect/designer and

completing in the hands of the constructor. By

holding each entity accountable for cost, quality,

and safety, owners can indirectly influence the

driver for designers to incorporate designs that will lead to potential cost saving automation and

increased project safety.

6. RECOMMENDATIONS:

Designers and constructors are encouraged to take a non-adversarial approach to communication and information exchange with

digital documentation and plans, as well as

intentions for methods of construction and

project follow through, on the behalf of the

designer. Lastly, constructors and designers are encouraged to develop business relationships

with one another that foster competitive, low

cost, high quality, safe projects and in doing this automation implementation can be better achieved.

REFERENCES:

1 . A. Scott, Howe, "Designing For Automated

Construction", 14"' International Symposium

on Robotics in Construction, 1998.

2. Emerging Construction Technologies,

www.technologies.org/ECT/Index.html. 3. Lee, Junbok; Lorene J. Steven; and Bemold

E. Leonhard. "Saving Lives And Money

With Robotic Trenching And Pipe

Installation", Journal ofAerospace

Engineering. New York, N.Y. 1988.

4. M. Cusack, "Automation and Robotics."

The Industrial Robot, International Fluidics

Services, ltd. 1994.

201
Table 1. Example Design Practices to Facilitate Construction Automation

Automation

Category

Example Design Practices

Concrete

Finishing

Tighter specifications for grade, slope, and smoothness.

Long continuous paving with constant slope.

Keep floor utilities together, not spread out. Pour constrained to machine width; no perpendicular curvature. Eliminate mid-slab protrusions.

Concrete

Reinforcement

Fabrication

and

Placement

Use repetitive sizes throughout building for columns, beams (i.e. Revise

reinforcing and/or concrete strength in lieu of changing member size.).

Use round columns vs. square columns.

Conducive standards for local iron manufacture facility.

Control degree of architectural variability.

Earthmoving /

Excavation

Digital copy of existing surface profile.

Uniformly sloped grading plans with well-defined break-lines.

Precise standards for locating underground utilities effectively.

Depths conducive to the use of automated equipment. (Stronger pipe doesn't

get buried as deep, so automation implementation may balance or lower costs

lIllUu^Il lllCICuoCU piUiiUCLl viiy^

Soil Compaction

Allow for adequate width of equipment.

Use backfill material conducive to the equipment.

Adjust trench slopes to slope range of equipment.

Adjust lift specifications to allow clearance for perpendicular objects. (Pipes,

Shoring supports, etc.)

Site&

Structure Inspection

Level surface or platform free from obstacles.

Visibility between equipment and operator.

Pipe Fab. &

Inst.

Accessibility of welders by leaving two feet between connections and joints.

Structural

Steel

Fab. &

Inst.

Use of Object Based Design process so that design documents can be used to

detail and fabricate material.

Material Tracking

Specifications for use of barcode labels. Industry Standardization of technology.

Design with more interchangeable sequences of work.

Specifications for required participation.

I 202
SESSION 4

DESIGN AND DEVELOPMENT OF

CONSTRUCTION ROBOTS

t

203

A TOOL TO IMPROVE EFFICIENCY IN LARGE SCALE MANUFACTURING

Roger Bostelman, Will Shackleford, Fred Proctor and James Albus

Intelligent Systems Division

Manufacturing Engineering Laboratory

Alan Lytle

Materials and Construction Research Division

Building and Fire Research Laboratory

National Institute of Standards and Technology'

100 Bureau Drive, MS-8230

Gaithersburg, Maryland 20899-8230

roger. bostelman @nist. gov, 301-975-3426

ABSTRACT: NIST is working directly with industry to improve repair and conversion operations of

ships in dry dock. This work allows transfer of technology to construction and other industries requiring

worker-access to large, external surfaces with minimum footprint and maximum system rigidity and

control, while augmenting conventional suspended-scaffold systems and moving toward more

autonomous large-scale manufacturing applications such as building construction.

KEYWORDS: worker access, ship repair, construction, robotics, cable controlled, large-scale

manufacturing

1. INTRODUCTION

The Manufacmring Engineering Laboratory of

the National Institute of Standards and

Technology (NIST) has teamed with Atlantic

Marine, Inc. in Mobile, Alabama to study

efficient methods to repair ships in dry dock or along a pier. This project, called Knowledgebased Modular Repair [1, 2] is under the

auspices of the Navy National Shipbuilding

Research Program Advanced Shipbuilding

Enterprise Initiative, where worker-, equipment-,

and material access to external ship surfaces was

determined to be a key focus area. The concept

developed in this project is called the "Flying

Carpet" and combines two main technologies:

the NIST RoboCrane [3] and commercially

available suspended scaffolding to produce an

effective concept for worker access to ships,

submarines, buildings, and other large objects.

The NIST Intelligent Systems Division

developed the RoboCrane cable-controlled

manipulator over several years [3, 4, 5, 6],

during a project for the Defense Advanced

Research Project Agency (DARPA) that studied crane suspended load control. Since the DARPA

project, NIST has expanded RoboCrane

technology into a viable solution to address

large-scale manufacturing and many other

challenges [7]. The RoboCrane applies the

Stewart-platform parallel-link manipulator

technology to a reconfigurable, cable-driven

No approval or endorsement of any commercial product by the National Institute of Standards and Technology is intended or implied. Certain commercial equipment, instruments, or materials are identified in this report in order to

facilitate understanding. Such idenufication does not imply recommendation or endorsement by the National

Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily

the best available for the purpose. This publicadon was prepared by United States Government employees as part of their official duties and is, therefore, a work of the U.S. Government and not subject to copyright.

205
system. While RoboCrane can lift large, heavy

and awkward loads, its stability and

maneuverability allow advanced programming

techniques more analogous to robots than

cranes. The RoboCrane combines sensors, computers, and lightweight tensioned cable

machines for performing heavy manufacturing

and construction tasks. These tasks can include

lifting and positioning heavy loads;

manipulation of workers, tools and parts for

improved worker accessibility and assembly;

and fixturing, welding, cutting, grinding,

machining, surface finishing and inspection.

Recent research has yielded the Flying

Carpet concept as a movable scaffolding and

worker positioning system that enables workers

to maneuver themselves, parts, and tools throughout a large work volume for tasks such

as ship repair and aircraft paint removal with up

to 20-times improved efficiency over hand-built

scaffolding. The Flying Carpet is a cablesupported platform that uses single-axis jog-,

velocity- and force-control modes. A photograph

of the 1:120 scale concept model is shown in Figure 1.

Figure 1. NIST Hying Carpet 1:120 scale concept model

showing the ship bow/stem access configuration (right) and

the ship side access configuration (left).

Beyond this step is envisioned a combined

closed-loop system, whereby the Flying Carpet can autonomously and rapidly lift, position, and

fixture heavy, bulky steel plates onto ships in dry dock during repair and conversion

operations. Similarly, the system can be used for more autonomous assembly applications on

construction sites. This paper will detail the

Flying Carpet concept, status, and provide a

look to the future toward the construction of

buildings and more autonomous manufacturing.

2. CONCEPT

Small and full scale static physical models, a computer model for studying system work

volume, and a full-scale working prototype were

built to demonstrate the advanced functionality

of the Flying Carpet as a tool for ship repair and

other uses. Figure 2 shows a photograph of the

full-scale working prototype Flying Carpet

configured for ship bow/stem access. Its basic

geometry includes four upper support points,

instead of three, to match the dry dock

configuration. These are connected to three

work-platform points with six cables.

The four upper support points can be

attached to towers mounted to a dry dock, on the

ground, along a pier, to a gantry, or to the

ceiling, walls, or other superstructures. Two

front cable pairs provide platform lift while two

rear cables mount lower to pull back on the

platform, creating a rigid system. Cables can be

multi-part lines for added safety and lift capacity. By suspending the platform from

above, the RoboCrane improves operating

efficiency by "flying" over ground-clutter or landscaping that typically hinders wheeled

vehicles at the work site. Hoists that control each cable's length can be mounted on the support structure or the work

platform. The total hoist rigging capacity of the

prototype, which uses two-part wire ropes, totals 8200 kg. In the prototyped configuration, the

Flying Carpet carries its hoist motors, which

provide a stabilizing counterweight. Motor

location on the platform also eliminates the

problem of mounting motors on the surrounding

support structure, making the platform easier to reconfigure.

206
Figure 2. Full-scale Flying Carpet prototype top view

shown in the ship bow/stem access configuration.

Welders, paint sprayers, or other equipment can be mounted to the Flying Carpet. The platform

allows rapid fixturing of tools, equipment, or cargo to provide direct worker access to the

equipment as needed at the site. The Flying

Carpet cable configuration provides a

constrained and easily maneuvered work

platform as compared to conventional workeraccess systems typically used for ship repair,

thereby aiding ship welding and inspection

tasks.The platform provides minimized sway and

rotation, and can exert forces and torques with

fiill six degree-of-freedom control. Flying

Carpet motion types include Cartesian and joint

modes. Cartesian control allows the worker to very simply move the platform front-to-back,

side-to-side, and up-and-down, as well as yaw

about the vertical axis, all while maintaining

level. Joint mode allows single-hoist motion for setup or cable replacement for normal

maintenance.

Platform levelness is ensured by both the

platform kinematic control and through a redundant level sensor. Operator control is through the tethered joystick, either worn by the

operator or mounted to the platform. With the

platform, an on-board or remotely-located

operator can manipulate and hold attached

materials, such as heavy steel plates, or tools,

such as welders, grinders, robots and other cargo

only dependent upon the platform rated capacity.

Tension sensors in-line with each cable prevent

hoist or platform overloading from occurring.

An on-board supply hoist can also be attached to the platform to bring tools, workers, and

supplies up to the work site while the platform is parked in position.

The full-scale prototype configured for

ship bow and stem access measures 14.5 m

wide X 7 m deep x 2 m high. Six hoists, each

rated to lift 680 kg, can carry 680 kg of

workers, materials, and equipment in

addition to the 1400 kg weight of the

platform itself, with at least a 5 times safety

factor.

Performance measurements and cable

configurations were tested on the full-scale testbed prior to planned testing in a shipyard dry

dock. Constrained by the NIST facility spacing

of 1 8 m simulated tower height x 2 1 m width x

14 m depth for front-to-back attachment point

distance, the full-scale Flying Carpet prototype

demonstrated: 10 m lift, 9 m forward-to-back

motion, 5.5 m side-to-side motion, and yaw of more than ±25° before the cables went slack. The translational work volume should scale well

to the larger dry dock environment.

3. PLATFORM RECONFIGURATION

The Flying Carpet can be reconfigured from ship

bow and stem access to a thin, ship side-access

configuration as shown in Figure 3. Reconfiguration from the bow and stem

access to the side access configuration includes:

removing the hoist platform (computer, power,

and attached cables); removing the rear tmss

assembly; moving the hoists and pulleys to match the new configuration; re-spooling the

cables; and pushing a button on the joystick to

tell the computer that the configuration has

changed. In this configuration, the 23 m depth is reduced to 2 m, allowing it to fit between the dry

dock wing wall and the ship side.

207
Figure 3. Full-scale Flying Carpet prototype top view

shown in the ship side access configuration. The full-scale platform is near a mock ship (photo right) and in this test there was no dry dock wing wall to push against with the platform outriggers.

It took a team of 3 workers 13 man-hours to perform platform reconfiguration over about 4

clock hours. It is estimated that this time could

be reduced to 3 to 6 man-hours (or 1 to 2 clock

hours) with further experience. If a second

platform were used for ship side-access along

with a ship bow and stem access platform, this reconfiguration time would not be necessary.

The demonstrated work volume in the side access configuration with support points spaced

at approximately 8mx21mx8.5m high

allows 6 m platform motion forward-and-back,

5.5 m side-to-side, and moves 6 m high. Yaw

motion is limited to approximately 5° due to the

reduced front-back depth and reduced rear platform depth. The platform in this configuration includes similar rigidity

characteristics as in the bow and stem access

configuration.

For platform heights above the dry dock

wing wall, the cables are at smaller angles with

the horizontal axis and therefore provide the

lateral stiffness necessary for upper ship side- access, at a cost of increased cable tension.

Vertical stiffness is reduced. In this case, all cables are mounted at the same height, where

tv/o cables attach to one of two towers as shown

in the model in Figure 4.

Figure 4. Photograph of the Flying Carpet 1:12 scale model

shown in the ship side access configuration. The 1:12 scale model shows a tower attached to the dry dock wing wall and the platform pushing against the wall.

Two front cables can instead be crossed for even more rigidity, and towers (support points) can be

separated by 30 m or more providing a very

large range of motion side-to-side. Along the

wing wall, similar platform rigidity can be

accomplished by pushing against the dry dock

wall with outriggers that could be adjusted

manually or automatically.

4. APPLICATION TO THE

CONSTRUCTION INDUSTRY

The concept of a Flying Carpet can also be

applied to the construction industry. Figures 5 and 6 show a graphic of this concept and

photographs of a scale model, respectively. For

quick or prolonged and non-intmsive access to external building surfaces, the Flying Carpet can be attached to inflatable columns or other

superstmctures (e.g., building comers,

aluminum or steel columns) and maneuvered

about the building surface. Columns instead of

building comers allow the Flying Carpet to be

attached to unfinished stmctures. The columns

can be made of a lightweight material, such as

sailcloth, light enough for a single worker to set up from the ground. For example, a column 1 m

in diameter, inflated to 70 kPa (10 psi), can

support more than 5000 kg of weight. Given the

208
stiffness of sailcloth, 1-m diameter columns up

to 25 m long should have no tendency to buckle.

Longer columns should be larger in diameter to preclude buckling. A small air pump could be

used to fill the structure and lift the support

points high above the building structure. Guy

wires could be used to stabilize the structure. With this concept, a worker could theoretically

reach all external building surface points for

performing window or wall section insertion,

window washing, brick laying, cleaning, or many other tasks associated with building

construction or maintenance.

Figure 5. Graphic of a model Flying Carpet applied to external building surface access.

Figure 6. Model Flying Carpet front (top) and edge

(bottom) applied to external building siuface access. The

wooden supports simulate inflatable columns or other

superstructure that supports the Flying Carpet. 5. FUTURE CONCEPTS

One of the next steps in the Flying Carpet

development effort is to provide navigation

capabihty for platform operation in semi- or fully-autonomous modes. Although relative

platform movement can be derived from winch

encoders, encoders alone cannot reveal changes

in platform position due to load variation or sway, nor will they easily map to the complex

shape of a ship or submarine hull. A position

reference system (absolute or relative) is desired

to enable flight path trajectory planning for the

Rying Carpet.

The Construction Metrology and

Automation Group at NIST is currently

instrumenting a RoboCrane platform with a

three-dimensional, laser-based site measurement

system (SMS) for absolute position control in all six degrees-of-freedom. [8] The project, part of

the Automated Steel Construction Testbed, will

be used to demonstrate autonomous steel pick

and place operations. Follow-on experiments

will incorporate registered LADAR (laser

detection and ranging) scans of the work site for

task analysis and navigation planning.

A similar navigation package will be

employed for the Hying Carpet using the

registered LADAR scans to map the hull as a boundary surface. The SMS will then be used to track the Flying Carpet along that surface. An

advantage of this method is that the LADAR

data from the scan also provides detailed 3D

information that can be used to map damaged

areas, create cutting/rolling templates for repair

material, analyze surface imperfections, and

generate as-built data for pre- and post-repair.

6. SUMMARY AND CONCLUSION

The Flying Carpet is a reconfigurable cablecontrolled platform based on the Stewart

Platform parallel mechanism. The Flying Carpet

provides the dexterity, precision, and large

work-volume needed for dry dock and/or pier

side ship repair, as well as for other large-scale

manufacturing applications. The Flying Carpet can be reconfigured and can attach to towers or

existing superstructures to eliminate unnecessary

209
equipment costs. Tools and equipment can be

attached to the Flying Carpet quickly and easily

for many worker-assisted tasks. The Flying

Carpet operator can be located at the work site or at a remote location to provide safe and

efficient worker placement. The Flying Carpet is a demonstrated technology, ready for

commercialization. Advanced concepts toward

autonomous construction are also being

considered.

7. REFERENCES

1. Stieren, D., Caskey, G., McLean, C, and

Neyhart, T. "Knowledge-Based Modular

Repair: Advanced Technology Applications

for Ship Repair and Conversion," Proc. of

the 2000 Ship Production Symposium,

Williamsburg, Virginia, August 24-25,

2000.

2. Stieren, D., Sovilla, L., "Rethinking Ship

Repair: Knowledge-Based Modular Repair"

Presentation, Proc. of the Shipbuilding

Decisions 2001 Ninth Annual Commercial

Shipbuilding Conference, Washington, D.C.,

December 4-5, 2001.

3. Stewart, D., "A Platform with Six Degrees

of Freedom," Proc. of the Inst, of

Mechanical Engineering, Volume 180(15),

Part 1:371-386, 1965-1966.

4. Albus, J. S., Bostelman, R. V., Dagalakis, N.

G., "The NIST ROBOCRANE, A Robot

Crane", Journal of Robotic Systems, July

1992.

5. Bostelman, R., Albus, J., Dagalakis, N.,

Jacoff, A., "RoboCrane Project: An

Advanced Concept for Large Scale

Manufacturing," Association for Unmanned

Vehicles Systems International Proc,

Orlando, FL, July 1996.

6. Roger Bostelman, James Albus, Bill Stone,

"Toward Next-Generation Construction

Machines," Proc. Of American Nuclear

Society 9th International Topical Meeting on Robotics and Remote Systems, Seattle,

WA, March 4-8, 2001.

7. Bostelman, R., Albus, J., Dagalakis. N.,

Jacoff, A., Gross, J., "Applications of the

NIST RoboCrane," Proc. of the 5*^

International Symposium on Robotics and

Manufacturing, Maui, HI, August 14-18,

1994.

8. Alan Lytle, Kamel Saidi, and William

Stone, "Development of a Robotic Structural

Steel Placement System," 19th International

Symposium on Automation and Robotics in Construction, Washington, D.C.,

September23-25, 2002.

210
REMOTE CONTROL OF MACHINES FOR REMOVAL OF DAMAGES BEING

RESULT OF DISASTERS, WARS, AND TERRORIST ATTACKS

Adam Bartnicki, Franciszek Kuczmarski, Tadeusz Przychodzien, Andrzej

Typiak, Jozef Wrona

Military University of Technology, Institute ofMechanical Engineering

KALISKIEGO STREET 2, 00-908 WARSAW, POLAND

phone +48 (0-22) 6839419, fax +48 (0-22) 6833211

E-mail: kuczmarski @wme. wat. waw.pl

Abstract: This paper presents an analysis of various natural and civilization disasters being angled as

possibilities of usage of the remote control or autonomous machines. There are determined the requirements for such a systems of theses vehicles or machines which are able to remove effects of natural disasters and local military conflicts or terrorist attacks. Idea of remote controlled working machines with using of external

control, information and observation system is also presented.

Keywords: Remote control, vision systems, machines, disasters

1. INTRODUCTION:

Dangerous events that occur more and more often

in contemporary world, being result both natural

disasters as well as terrorist attacks (e.g.,

contaminations, destructions and mining of

terrains) and local armed conflicts extort necessity

of wide utilization of different machines to remove

(or limit) the negative results of them. However,

the enormous majority of working machines

(excavators, bulldozers, and mobile cranes) or combat engineering machines are used for such

tasks being controlled directly by operator

(without remote control or computer-aided

systems). It is possible to expect that there will occur threats for operators and people who

cooperate with them. Hence, we have to very

intensely develop the remote control systems for such machines.

On the other hand, implementation the fixed

elements on the board of these machines that adapt

their to remote or automatic control is not often

rational (reasonable) from economic point of view.

Hence, taking the attempt to define the general

structure of system to adapt these machines for remote control, but only when it is needed, very

easily, with limited number of elements installed on the bocu-d of machine seems to be reasonable.

It is clear that the core of such a system

(transmitter and control desk) and operator should

be located out of machine (in safe zone for them).

It also requires to make the suitable outside

subsystem of visualization of position of machine

and its working equipment, to define their

coordinates in coordinate system and to counteract

in case of such critical incidents as damage or

standstill of machine or troubles with

communication between machine and operator

(break of transmission of control signals).

The basic efforts of designers of control system of

such machines should be focused on minimization

of their onboard structure through:

applying the simple and reliable elements

of execution system;

minimization of range of information

transmitted from machine (decreasing the

number of sensors and converters);

introduction the "reliable core" of control

system - operating in emergency states; possibilities of automatic reconfiguration

of onboard system in case of breakdowns

and faults. This extorts necessity of extension of external

structure of control system (placed beyond range

of direct influence of surrounding of machine

(vehicle), what causes:

211
necessity of increasing of numbers of

transmission channels and speed of

sending of information and commands;

growth of probability of occuring of errors

- it requires to amplify signal power for

keeping required range of transmission

link; necessity of elaboration of detailed and

complex steering procedures with many

variants of operation.

Such designed control system of umanned vehicles

and machines with various extent of automatic and

autonomous operation can execute wide range of

works such as removal of effects of natural

disasters and local military conflicts or terrorist attacks (see table 1).

2. IDEA OF REMOTE CONTROL WITH

USAGE OF EXTERNAL CONTROL AND

OBSERVATION SYSTEM:

The requirements and conditions which are presented above have allowed to elaborate the idea

of remote control of machines with usage of

external control and observation system that can

be used to remove effects of disasters, wars and

terrorist attacks. It has been presented in figure 1. The area of operation has been divided into three zones: basic, supply and expected. In the basic zone a control post has been located. It has been

equipped with remote control system to control of

machines (1) and (2) and external TV observation cameras with geodesic measurement system of

their position, orientation and observation. One of

this TV camera is located in supply zone and

designated to aid the operation of remained two

TV cameras. Both control and vision signals are transmitted via transmission channels. It allows to obtain data concerning position and to control the

execution elements e.g. levers, pedals of machines

being controlled (1). In adverse conditions

remote controlled unmanned vehicles for

added observation of machine that is remote

controlled in the expected zone can be used.

This unmanned, mobile observation vehicle

(2) plays the role of relay station for control

and information signals between the controlled

machine (1) and control post (3).

Standard vision systems perceive the word in two

dimensions (because of lack of direct ability to measure the distance to the objects and their size).

Thus nowadays the main research problem in

vision system is three-dimensional perception of

the picture (particularly its depth). The data of the

three-dimensional location of the objects which are not included in two-dimensional picture are included e.g. in stereoscopic pictures.

Stereovision allows to achieve relatively high

spatial vision and in comparison with one eye

techniques (one-camera) it leads to quantity

measurements, more direct and unambiguous.

Despite of radar and laser distance measurements

it is suitable for many applications. It particularly concerns to reconnaissance, supervision and

objects' manipulation in an unknown area

detection of vehicles' motion in unknown

surrounding, including metric measurement in photogrammetry, robotics and vehicle remote

control. New vision system was elaborated for these needs.

The system consists of two basic blocs:

observation set and operator position

(see figure 2). Observation set serves to observe the terrain or chosen objects with CCD cameras. Its construction

allows to observe chosen objects with both cameras (carrying out stereovision process) or observation the objects located in different

directions. At the operator position there are TV

cameras, operator panel and microprocessor

controller VME.

In the figure 3 the developed conceptual scheme of

elaborated vision system is presented. In the

system three channels radio link has been applied.

Two one direction channels serves to send

television signal while two direction channel

serves to send steering and measuring signals.

Observation set consists of a steering camera-head

mounted symmetrically on a rotary beam. The

change of the axis of beam rotation is done by its steering head. GPS system mounted to it reads its azimuth and specifies: set location in geographical

coordinates, sea level and terrain slope. The data

from GPS might be plotted on digital map which

would allow to draw e.g. the route of a vehicle

drive (with mounted vision system).

Operator stand allows to control the position of

observation cameras, the change of their focal

length and focus regulation. Steering might be

carried out automatically - with usage of

microprocessor controller or in manual way -

through operator panel. The data about camera

parameters and the location and orientation of

observation set are sent to controller and moreover

might by shown (in any configuration) on the

monitor screen.

212
Microprocessor controller VME has been

designated to automatic control of cameras'

position and it is an element supporting the

operator. Moreover it enables to process vision

signals and determine on the basis of these signals

location of observed object in relation to geodesic

point of reference. The control procedures of

steering cameras" position is used for automatic

monitoring the observed object.

3. CONCLUSIONS:

Resulting conclusions from the above schemes and

examples indicate that presented idea of remote

control vehicles for removal effects of disasters, wars and terrorist attacks is proper. There were

underlined the main problems during realization

proposed control system i.e. elaboration of visual

system for visualization of surrounding of vehicle

or its working area. It makes possible the control

of such machines in real time by average educated

operator.

Presented solutions indicate there is necessary

individual approach for designing of structures of

control systems in depend on expected

technological tasks. The existing dangerous for human life that have

been determined in this paper extort the needs to elaborate the remote and automatic systems for

universally used machines and vehicles to make

them more safe for operators during works after different kinds of natural and civilization disasters. Presented vision system can be used for: localization of observed objects;

surrounding observation and detection

terrain obstacles;

observation position and orientation of

working equipment;

visualization of working equipment

position.

The additional advantage is that it can be mounted

on both engineering machines and separately

placed in the terrain.

Its main aim is supporting the operator while

fighting or while earthmoving works in inaccessible or hazardous terrain. The assumption

of the project was to allow the operator to see working machine (to have with it an eye contact).

On the basis of the picture obtained from cameras

both can be specified - vehicle's position and

external objects location.

The system may be used in armed forces to locate

and indicate the targets as well as to support the

fire control at the battlefield. In further works on the presented system it is assumed that the spatial image will be obtained on

the base of data from the observation cameras. It will allow to implement the pictures of observed

pictures on TV monitors. Thus the soldiers and the

operators of the remote controlled machines and

vehicles will be able to perform their tasks more

precisely.

4. REFERENCES:

1. Bartha M.; Eibert M.; Schaefer Ch.H.:

Robot-motion in unstructured

environment. Twelfth International

Symposium on Automation and Robotics

in Construction, Warszawa 1995.

2. Bartnicki A., Konopka S., Kuczmarski P., Typiak A.: Badania doswiadczalne

sterowania koparkq jednonaczyniowq z systemem wizyjnym, XV Konferencja

Problemy Rozwoju Maszyn Roboczych,

Zakopane 2002.

3. Maslowski A.: Mobilne roboty

interwencyjno-inspekcyjne, Konferencja

Automation 97, Warszawa 1997.

4. Bartnicki A., Konopka S., Kuczmarski P., Typiak A.: Remote control of working

machines with vision system, 18 th ISARC

International Symposium on Automation

and Robotics in Construction,

Krakow 2001.

5. Roberts J.M.; Winstanley G.J.; Corke

P.I.; Issues in obstacle detection for

autonomous mining and construction

vehicles, 16 th lAARC (IPAC) IEEE

International Symposium on Automation

and Robotics in Construction,

Madrid 1999.

213
Table 1. Classification of disasters being angled as possibilities of usage of the remote control or autonomous machines'''

Deep snowfalls,

snowst.orms, blizzards

Strong ivinds

and hurricanes

Long-lasting freeze or droughts, hailstorms or glazes

Plague of rodents

and insects

res

Terrorist attacks

and different threats

of public safety

Destruction damages

of infrastructure in result of terrorist attacks

and local military conflicts

') intensity of gray color indicates extent of usage of the remote control or autonomous machines

Expected area of operation of machine, vehicle ...

Basic, accessible zone of location of control post and elements

of external observation system

Figure 1 . Idea of remote controlled working machines with usage of external control and observation

system

1 - machine being controlled; 2 - umanned, mobile observation vehicle 3 - basic control post (operator

equipped with control panel or special vehicle); 4a, b, c - external remote controlled observation cameras with geodesic measurement system of their position and orientation; 5, 6 - channels for

controlling of the cameras and for transmission of vision and position data

214
X

Deck block

control and

supervision

of TV cameras

and telemeter

Block Aspecyfying the

position of a machine

(vehicle) and its working equipment

in local and outside reference system

Operating system mz

Machine

drive system

Environment

Machme I

steering deck

system

Environment

monitoring system SIMeasurement

block

Couple

block

Visualisation console

TV

pictures' console

Cameras'

location console

(digital map)

Animation console

Indications' console

Figure 2. Structure of remote control of mobile working machines' scheme with vision system

COMPUTERS

MONITOR

Figure 3. Scheme of vision system

215

ADVANCEMENTS IN TELE-ROBOTIC PIPELAYING

Leonhard E. Bernold,

Associate Professor

Bin Li, Intern. Scholar

Construction Automation Robotics Laboratory (CARL.ce.ncsu.edu),

North Carolina State University, Raleigh, NC 2751

1

Abstract: The labor intensive construction industry has a very high accident rate. One of

the key reasons for this is the exposure of workers to a hazardous environment such as heights, confined narrow spaces, and exposure to health threatening fumes, dust, and

noise. Tele-robotic operation, which allows an operator to control a mechanical tool from a safe distance, provides a technical alternative. Because of the need to be

competitive on every project-bid, contractors have to be assured that new technologies

not only work in the rugged environment of a construction site but that they also reduce

cost. This paper will present an example of such a technology, a pipe manipulator that allows the remote installation of large concrete pipes in deep trenches. A second

prototype has been built and successfully field-tested. The comparative evaluation of the new technology shows that it is not only safer but also more economical to use. With the goal to further improve agihty, flexibility, and ease of operation, a third prototype has been readied for further field tests

Keywords: tele-robotics, safety, trenching, remote control, pipe-laying, trench collapse

Introduction

According to the Bureau of Labor Statistics (1999), in 1997 there were 1,137 deaths in the construction industry. This number

equals 18% of the total fatalities from all industries and indicates that construction has

the highest number of fatalities. Another

source shows that the construction industry

employed approximately 5% of the

industrial work force, but generally

accounted for nearly 20% of all accidental

deaths (National Safety Council, 1997). An

analysis by the National Institute for Occupational Safety and Health (NIOSH) of

workers' compensation claims for 1976-

1981 shows that excavation cave-ins were

the cause of about 1,000 work-related

injuries each year. Of these injuries, 140

resulted in permanent disability and 75 in death.

The traditional ways to prevent collapse and

make working in a trench safe are (1)

providing physical supports for each side of

the trench using shoring or a trench box, or

(2) sloping the sides to a safe angle.

OSHA's excavation standard requires

employers to provide sloping (or benching),

shoring, or shielding to protect employees in excavations 5 feet or more in depth. The

only exception is for a trench dug in stable rock, where there is no loose soil or likelihood of a cave-in. Excavations less than 5 feet deep need not be protected unless

a competent person has determined there is a cave-in hazard. As shown in Figure 1, depositing spoil right next to the trench

make even a 5 feet deep trench a death trap. Because of the complex nature of digging

soil, accidents still occur. One way to eliminate the risk, is to introduce a technical

intervention such as teleoperated pipe

manipulator able to lay pipe without a human in the trench. However, in order to be a viable economic alternative to the

traditional methods, such technology needs

to be cost effective as well.

217
Prototyping a Technical Intervention

A first device able to handle large concrete

pipes remotely was designed and fabricated

in 1994. This first-generation pipe

manipulator (PipeMan), shown in Figure 2, was subsequently improved by adding a

laser and video system in order for an

operator to control the entire device

remotely (Lee at al., 1999). Figure 3

presents the overall architecture of the 2

generation PipeMan.

Mechanical Components of PipeMan

The actuation system consists of the

following five functions:

1) H. Actuator (A_Rotl): A hydraulic

actuator provides the limited ±100

degrees rotation of the pipe in order to

line up the pipe.

2) H. Actuator (A_Rot2): A hydraulic

actuator provides a locking mechanism

on the back of the manipulator to prevent it from slipping off the bucket.

3) H. Cylinder (C_Trans): A hydraulic

cylinder provides a linear activation of

the pipe to joint the new pipe to the pipe

already laid. 4) H. Bladders (B_Clamp): Hydraulic

bladders provide an inflating and

deflating mechanism to clamp the

manipulator to the bucket.

5) E. Winch (WJHold): An electric winch

is used to attach the pipe with a quick

release.

Man-Machine Interface

The man-machine interface includes

manipulation and visualization functions.

Two microvideo cameras allow the operator

to have a real-time view during final alignment of the pipe joint. One video camera covers the front of the pipe for

jointing and the other faces the laser targets

to monitor the laser beam for alignment.

In order the provide the operator a convenient and safe method for operating

the manipulator a separate control box,

shown in Figure 4, was designed and

DC/DC converter in order to distribute

24VDC to 5, 9, 12, and 24 VDC as outputs.

The power source to be used is 24VDC from

the excavator. A switchstick control is added for the remote operator's easy control

of the manipulator. The control box also

includes three three-way switches, and one main power on/off switch. Switchstick #1

controls rotational actuation of the hydraulic

actuator (A_Rotl). Switchstick #2 is linked

to the translational actuation of the hydraulic

cylinder (C_Trans). Separate three-way

switches control the actuation of the

hydraulic cylinder (A_Rot2), clamping

actuation of the bladders (B_Clamp), and

locking/unlocking of backstop (A_Rot2).

The LEDs (light-emitting diodes) are used

as a fault detection system. As long as an

electric signal or power is applied, the LED

light remains on. The hydraulic fluid for the

4 different actuation units (two actuators, one cylinder, and two bladders) is provided

by a hydraulic manifold mounted on to the

PipeMan.

Comparative Field Tests

As mentioned earlier, only field tests with

experienced laborers and operators will

show if the innovations works effectively

and economically. For this purpose a comparative field test was conducted on the

job-site of East Park Industrial Subdivision

in Raleigh, NC. The comparative

experiment included two different ways of

laying the pipes: 1) traditional method, and

2) manipulator utilization. Site conditions

including soil, trench width and depth,

pipes, crew members, weather were the same except for a way of performing pipe

laying.

The crew members laid concrete pipes the

way they normally do one day, and the

manipulator was utilized to do the same

tasks the next day. Figure 5 presents the two

methods. The soil condition of the job site was sandy clay and the concrete pipes were

36-inch (0.9 m) diameter and 8 feet (2.4 m)

long. Figure 5 b) depicts the operator lining

218
up a new pipe by adjusting direction and

grade of the pipe using the laser as a guide.

Qualitative Assessment

The technical performance of the new

system was assessed in terms of: 1) Overall

performance, 2) learning curve effect, 3)

acceptance and adoption, and 4) technical

problems.

Overall Performance

Using both, his own laser and the laser- video targets, the operator immediately felt comfortable with the necessary adjustments

and the accuracy of the installed pipes. The

availability of an image showing a close-up

of the pipe joint was praised and felt to be a

special asset when laying pipes into deeper

trenches.

Learning Curve

The workers became familiar with the new

process after only a few repetitions. They

laid the last 2 pieces of pipes at a consistent

shorter time than the first 3 cycles.

Acceptance and Adoption

The operator, pipe-layers, and helpers

accepted the new technology wholeheartedly.

Technical Problems

Although a brand-new winch was used, the

weight of the large pipe used by the contractor was too much for the its baseplate. The test made clear that having two

winches might be necessary. Another issue was the size of the bucket which made the

backstop unworkable. A chain provided the

perfect alternative solution. The inflatable

bags were also not performing as expected.

Cost Comparison

The main cost items consist of: a)

excavation and bedding, b) pipe laying, c)

pipe manipulator rental, d) backfill &

compaction, and e) insurance. Volume of

excavation for the traditional method, 2 1 m\

inrliiHf*; thp hpnrhpQ chnwn in Fionrp S

while the volume for the alternative method,

11.6 m\ is based on vertical trench walls

with a minimal width as required for proper

haunching. As expected, the resulting cost

saving, $ 7.52/m or 54%, is significant.

Overall, the total cost for the excavation and

laying of 36 inch (0.9 m) concrete pipes into a 6 feet (1.8 m) deep trench during the field

tests are $53.7 per meter ($16.37/ft) for the

traditional method and $ 65.54 per meter

($20/ft) for the observed tele-robotic

method. As was anticipated, the tele-robotic

option turns out to be more expensive

mostly as a result of the higher cycle time,

the result of the broken winch. However,

simple improvements should undoubtedly

result in reducing the time for laying one

pipe.

Third Generation PipeMan

Based on the encouraging results of the field

test, it was felt that the basic concept of

PipeMan was solid. One main problem,

however, was the weaknesses of the winch.

A second issue was the inability of adjusting

the grade without the bucket. This

capability would allow an excavator to be

positioned on the side of the trench. The

following section will present an alternative

method of holding the pipe.

A Two Pronged Carriage

The flexibility of the system design allowed

us to consider exchanging the carriage

holding the winch while keeping the base,

holding all the controls. It was decided to fabricate an alternative to the original

carriage that was based on the flexibility

provided by prongs. Figure 6 presents the new design. As indicated, the pipe will be

lifted simply by inserting the prongs into the

pipe. A mechanical stop-plate is automatically engaged when the weight of

the pipe is taken over by the prongs. This

stops the pipe from sliding off.

Adding a Third Degree of Freedom

One weakness of PipeMan was the fact that

it could only be used in the axis of the trench

cinrf* thp <:1r>r>p r»f thp ninf haH hf^ nfliii<:t(»H

219
using the bucket. In order to allow a backhoe to lay pipes from the side of the

trench, a degree of freedom had to be added.

Figure 7 indicates that this was

accomplished by allowing the prongs to

rotate at one while actuating the other end

with the help of a hydraulic cylinder.

Summary

Traditional trenching and pipe laying

requires workers to enter the trench,

resulting in many fatalities due to the nature of the soil in the trench walls and other work

related circumstances. The telerobotic

concept promises to drastically reduce the

risk to human life by keeping the worker

outside of the trench. This paper presented

the major components and functions of the

newest version of the teleoperated pipe

manipulator that has been designed and

fabricated to handle pipes that use o-ring

connection. The new technology proved its technical feasibility by laying 8 piece of

concrete pipes without any workers in the

trench. The field test highlighted too that with the help of technical modifications, the

system would also be cost effective. These

modifications have been implemented to create the third generation PipeMan.

Acknowledgments

Funding for the work has been provided by

Public Health Service-National Institutes of

Health under contract 5 ROl CCR413051

02 and IROl 0H04201-01. Its content is solely the responsibility of the writers

and do not necessarily represent the

official views of NIH.

References

Lee, J., Lorenc, S.J., and Bemold, L.E.

(1999). "Saving Lives and Money with

Robotic Trenching and Pipe Installation,"

ASCE Journal of Aerospace Engineering,

Vol. 12, No. 2, ISSN 0893-1321, April

1999, pp. 43-49.

U.S. Department of Labor, Occupational

Safety and Health Administration, Title 29

of the Code of Federal Regulations (CFR)

Part 1926.650-652.

Fig 2. PipeMan Generations 1 and 2

220
LCD

, Base with Valves

Fig. 4 Control Box for Operator

a) Side View with Loaded Pipe

a) Laying Pipe Traditionally

b) Laying Pipe with PipeMan

c)

Fig 5. Comparative Field Test

b) Front View with Loaded Pipe

Fig. 6. Pipe Carriage With Prongs

Base with Hydraulic Valves

Hydraulic Cylinder

Fig 7. Third Degree of Freedom

221
Man-Machine

Interface

Visualization

TV monitor

Feedback

Manipulation

Pipe Manipulator

Operator

cor trol

Electro- hydraulic Valves

joystick

act /s4ion

Excavator

cor trol

hlectrotiydraulic control system

joystick

Laser Beam 2

Target #1

Target #2

Actuation \.

1. H. Actuator: rotational actuation

2. H. Actuator: rotational actuation

3. H. Cylinder: translational actuation

4. H. Bladders: inflation and deflation

5. E. Winch: wind-up and release

Hydraulic (1-4) &

Electric (5) Power

ac Nation

1. H. Cylinder #1: Boom

2. H. Cylinder #2: Stick

3. H. Cylinder #3: Bucket

Hydraulic Power

pipe manipulator mounted

to the bucket of excavator

A_Rot1 A_Rot2

C_Trans B_Clamp

W Hold

cylinder #2

Fig 3. Layout of PipeMan Attachment

222
MOTION PLANNING TAKING INTO ACCOUNT

THE DYNAMIC MODEL OF VEHICLES : APPLICATION TO THE COMPACTOR

Charles-Eric Lemaire * Pierre-Olivier Vandanjon * Maxime Gautier** Frcingois Peyret *

* Laboratoire Central des Fonts et Chaussees (LCPC)

Route de Bouaye, BP 4129, 44341 Bouguenais, France

charles- eric. lemaire/pierre-olivier. vandanjon@lcpc.fr

** Institut de Recherche en Cybemetique et Communication de Nantes (IRCCyN)

1 rue de la Noe, BF 92101, 44321 Nantes Cedex 3, Prance

maxime.gautier@irccyn.ec-nantes.fr

ABSTRACT: Motion planning is a necessarj-' step before automation in road construction. This paper deals with motion planning for compactors. The compactor is an articulated frame steering vehicle used in road construction. Generally, motion

planning uses the kinematic model of the robot. In the case of the compactor, this model is far away from reality because it does not take into account compactor

masses and particular drum-soil contact forces. A motion planning which uses both

the kinematic and the dynamic model of the compactor is presented in this paper. The advantages of this motion planning are: • To generate feasible motion for the robot which implies a smoother control law

for mechanics,

• Limited slips.

KEYW^ORDS: Compactor, Mobile robots. Motion planning, DjTiamic model

1. INTRODUCTION

This article focuses on the compaction process during the road construction. This process is made

up of several trajectories of several compactors.

In the frame of automation in road construction,

it can be seen that the compactor must follow an efficient trajecton,^ defined in position, velocity

and acceleration according to compactor degrees

of freedom to guarantee the homogeneity and the expected density of considered compacted material. Those features should be improved taking

into account a dynamic model compared with a

simple path tracking using kinematic model. The

compactor motion planning, presented here, is based on the dynamic modelling and identification of the compactor (Guillo et ai, 1999). Necessary

elements of modelling are presented in this paper

before the presentation of the method of motion

planning with simulation results.

Fig. 1. A typical compactor: Albaret VA12 DV

223
2. COMPACTOR MODEL 2.1 Geometric model

A planar motion of the compactor is considered. Let Rg be a Galilean reference frame attached to the rolling plan 11. In these conditions, a vector of three generalized coordinates is needed to specify

the compactor posture.

The front frame is chosen to be the reference body

Cr of the compactor, i.e. its situation gives the

compactor posture.

According to classical robot manipulator descrip- tion (Canudas de Wit et al. 1997), the compactor

is considered as a mechanical system S composed

of a tree structure of n = 7 rigid bodies Cj where

Cq is the base body and with the following body

definitions (see Figure 2):

• Ci, Ci are two virtual bodies (i.e. without mass and inertia) used to define the compactor position with respect to the frame Rq,

• C3, C5 are the front and rear drums,

• C4. C7 are the front and rear frames,

• Ce is a virtual body (used to define a second

frame R% attax:hed to C5).

The system E is provided with a frame Rj re- spectively attached to each of the {n-V \) bodies

Cy Let Rj be defined as Rj = {Oj,Xj,yj, zj) (see Figure 2).

Classical tree structure description using the

DHM notations (Khalil and Kleinfinger, 1986)

applied to the system E defines the geometric

parameters of the compactor (see Table 1 and Fig.

2) with respect to the position and orientation of the body Cq.

Table 1. Geometric parameters of the compactor

j

i = a{j) ^.7 aj dj

1 0 1 tt/2 0 7r/2 ri 2 1 1 7r/2 0 it/2 r2

.3 2 0 n/2 0 63 0

4 3 0 -n/2 0 04 0

5 3 0 0 -Ds 6:, 0

6 5 2 0 -De 0 0

7 6 0 -n/2 0 07 0

According to the DHM description of the compactor, the vehicle motion is completely described

by the vector q (see eq. 1) of six generalized co- ordinates where the vector ^

gives the compactor

posture.

The Direct Geometric Model (DGM) gives bodies

situation with respect to the reference frame Rg

as a function of q, the vector of joint variables.

For example, equation 2 gives the situation of the

rear frame (Ce) of the compactor with respect to the frame Rg. The symbolic modelling software

SYMORO-I- (see (KhaUl and Creusot, 1997)) had

been used to determine the expression of equation

2 from the table 1 of the geometric parameters of the compactor.

»P6 =

'003(63 +05) - sin(6>3 -I- 6I5) O' sin(6>3 -l-6>5) cos(6>3 -1-615) 0

Vi - D5 • cos 6»3 - De • cos(e3 + 65

)

r2 - D5 sin 63 - De- sin(6l3 + 65) 0

(2)

2.2 Kinematic model

In the previous section, the geometric description

of vehicles using robotics formulation is presented.

From this description, the Direct Kinematic Model

(DKM) of vehicles can be developed. It is composed of nt relations (see eq. 3) corresponding

to the velocity of each of the nt vehicle terminal

bodies (wheels, drums, tools,...). The equation 3 gives the kinematic wrench of a vehicle terminal body Cj with respect to the

reference frame RoLg.

V3,9 ' q (3)

where V^^ and u)j^g respectively are the velocity

of the point Oj and the rotation velocity of the

body Cj with respect to the reference frame Rg.

^j ^ is called base jacobian matrix of the vehicle.

2.2.1. Conditions of pure rolling and non-slipping Let be assumed that the contact between the

rigid drum and the soil is reduced to a single

point Bj of the rolling plan 11 (see Figure 3). The contact between the drum and the soil is supposed to satisfy both conditions of pure rolling

and non-slipping along the motion. This means

that the velocity of the contact point Bj is equal

to zero and implies that the two components of

this velocity, respectively parallel to the plan of the drum and orthogonal to this plan (see eq. 4), are equal to zero.

q = r2 6^3 (1) VJ,9 Vi

(4)

224
(a) Bodies definition (b) Equivalent tree structure (c) Projection frames definition

Fig. 2. Geometric description of the compactor using the MDH notations.

• L is a vector depending on the internal forces between the vehicle bodies: motor torques,

friction, lumped elasticity. • Q*^ is a vector depending on the external contact forces between the soil and the drums.

2.3.1. Internal forces The vector L of internal

forces is composed of three components :

• the actuation vector L° which is composed of motor torques,

• the friction vector L-'^ which is composed of

friction component on different joints, • the elastic forces vector L,^ which represent

the stiffness of joints.

2.4 Contact forces between drums and the soil

Fig. 3. Contact between a rigid drimi and the soil reduced to a single point.

The constraints can be written in the general

matrix form

J{q)q = 0 (5)

This means that whatever the type of vehicle, the

velocity q is restricted to belong to a distribution Ac defined as

qeAc = span{col(5(g))} (6)

where the columns of the matrix S{q) form a basis of ker(X(g)). This is equivalent to the following statement: for all time t, there exists a timevarying vector Tj{t) such that

q = S{q)v (7) The relation 7 is called the Inverse Kinematic

Model under constraints of the vehicle.

2.3 Dynamic model

The Inverse Dynamic Model (IDM) of a vehicle is written as following

M{q)q + H{q,q} = h + Q' (8)

where:

• M{q) is the mass matrix of the system S.

• H{q,q) is the vector of centrifugal, Coriolis and gravity terms.

Using the principle of virtual powers, the vector

Q"^ of external forces is developed to obtain

Q^ = E^^?^''^S^c, (9)

j

where ^"^n' points out the wrench of the

resultant contact forces between the soil 11^ on

the drum Cj at point Oj projected in frame Ri.

2.5 Linearity property of the inverse model

The expression of kinematic and potential energies are linear in relation to a set of (rip = 11) pa- rameters, Xs- Consequently, the expression of the

Inverse Dynamic Model is also linear in relation to the same set of parameters and then it is possible to write it as following

Ys = Ds{q,q)Xs (10)

with n = L".

225
Using this property of the Inverse Dynamic

Model, a Weighted Least Squares method of identification is proposed by (Gautier, 1997) to obtain

the vahies of the dynamic parameters Xg of robot

manipulators and applied to a mobile machine,

the compactor, in (Guillo et al., 1999).

2.6 General expressions of the dynamic model

The general expression of the Inverse Dynamic

Model is given by the relation 8. According to the expression of the internal and external forces which take part in the model, there are two

possible expression of this model:

• The conditions of pure rolling and nonslipping are satisfied. Then, the Inverse Dynamic Model has the following expression

f M(q)q + H{q, q) = L'' + L'= +Jiq)'^X

\

J(.q)q = 0

(11)

• The conditions of pure rolling and nonslipping are not satisfied. Then, the Inverse Dynamic Model has the following expression

M(q)q -I- g) = L" + L-f + <Q

(12)

3. MOTION PLANNING

Motion planning is to determine joint position,

velocity and acceleration. The method developed

is composed of four steps

(1) Path determination in order to respect the geometric constraints of the compactor task.

(2) Timing law determination in order to respect the kinematic constraints of the compactor

task.

(3) Generalized coordinates determination us- ing the inverse kinematic model under constraints.

(4) Actuator torques and drum-soil contact forces determination in order to compare them with

physical limitations.

3.1 Path determination

According to the geometric model, a planar motion of the compactor is considered. The path is determined by the compactor posture

i = [ri r2 e:,f = [x{s) y{s) e{s)f (13)

where :

• 6 IS the path orientation,

• X and y are the path cartesian coordinates.

The path is characterized by its curvature K along

the arc length s

dd = Kds

d{s) = do+ I K{u)du

Jo

x{s) = xo+ / cos{6{u))du

Jo

y{s) = yo + / sin(^(u))dii Jo

(14)

(15)

(16)

(17)

Concerning asphalt compaction, the compactor

has to compact the bituminous mix spread by the

paver. But a paver is wider than a compactor,

so the compactor path is composed of juxtaposed

tracks (see figure 4).

Fig. 4. Compactor typical path

The compactor path is essentially composed of

straight lines and track changing. Determination

of the path along a straight line is obvious.

K = 0

eis) = eo x{s) = xo + scos{6)

y{s) = yo + ssm{e)

(18)

(19)

(20)

(21)

A track changing path is characterized by its width D and its maximum curvature Kmax Para- metric equations are determined in this way : there are two symmetrical parts in the path, if the path length is Al then the curvature K{u) is an odd function for u = s — 2l. These specifications are enough to compute K{s) for s G [0,2/]. The path curvature must be smooth to be compatible with the compactor dynamics. Constraints

of symmetry lead to a second order function for the curvature such as :

K(s) = kQ + kis + k2S^ (22)

K{0) = 0, K{21) = 0, Kit) = Kmax (23)

Solution for K{s) with s e [0, 21] is

(24)

226
Cartesian coordinates could not be computed explicitl}-. so they are computed numerically. But all these calculations need the path length which is not known. To solve this problem, this equation is used : D

ym = (25)

that makes it possible to compute / according to D and Kmax3.2 Timing law

This section deals with the compactor kinematics

along the path which determines the timing law

of the motion. According to the compactor task,

different timing law are used :

• Acceleration.

• Braking,

• Constant speed.

For each timing law, acceleration must be contin- uous in order to respect physical characteristics of actuators. A polynomial of the second degree is used to respect the constraints of continuity. For an acceleration from 0 to Vmax- the velocity law

is given by :

v{t) r

31-;

3 ^max(2i — 3r)i

2^„

(26)

(27)

with

• ^'max is the top speed of the motion,

• 7max is the top acceleration of the motion,

• r is the duration of the acceleration.

For the braking timing law, the acceleration is inverted, but the idea is the same. Generalized

coordinates of the motion can be computed by

combining the path and the timing law to generate inputs of the inverse kinematic model imder

constraints.

-v{t)

vit) =

uj{t)

(30)

(31)

So the generalized coordinates are computed :

(lit) =<!o+ q{u)du

Jo (32)

The compactor motion is entirely defined by joint

position, velocity and acceleration. The generalized coordinates have been computed with four parameters, the width (D) and the maximum

curvature (Kmax) for the path and the top speed

(^max) and the top acceleration (jmax) for the

timing law. The Dynamic model is used to tune

this parameter in order to respect the capacity

of actuation and the limit due to the drum-soil

interaction.

3.4 Dynamic tuning

It is possible to compute motor torques and drumsoil interaction forces with the inverse dynamic

model. In this equation :

M{q)q + H{q, g) = L" + + J^(g)A (33)

the Lagrange multipliers A = [Ai...A4]-^ corre- spond to tangential contact force between drums

and soil such as the pure rolling and non-slipping

constraints are respected; the generalized actuation vector L° correspond to motor torques. As

drum-soil interaction forces and motor torques are computed, it is possible to analyze them and to tune motion parameters to optimize them.

4. SIMULATION RESULTS

3.3 Generalized coordinates computation

The motion is specified by the path curvature

function of its arc length and by the velocity

function of the time. The path curvature can be

computed as a function of the time :

s{t)= I v{u)<lu (28) Jo K{t) = K{s{t)) (29)

Inputs of the inverse kinematic model under constraints can be computed :

Two sample motions to test this method have

been used. The path is a 1.5 meter width track changing which is a typical compactor path (see section 3.1). Parameters of these motion are set

in tables 2 and 3. The motion described in table 2

is a base motion, the motion described in table 3

is the base motion which has been optimized with

our method.

Track width D = 1.5 m

Maximum curvature Krnax = 0.15 m~-^ Top speed Vmax = 1-4 m.S~^ Maximum acceleration Imai- = 3 m.S"'-^ Table 2. Motion planning parameters

227
Track width D = 1.5 m

MaLximum curvature Kmai = 0.17m"^ Top speed V'mai = 1-4 m.s~^ Mciximum acceleration ImaT = 1-2 m.S~2 Table 3. Optimized motion planning pa- rameters

These motion have been used as a reference in our compactor simulator. Simulation results are presented in Fig. 5 Fig. 6 and Fig. 7.

Fig. 5. Actuator torques for the base motion

Fig. 6. Actuator torques for the optimized motion

Time (seconds}

Fig. 7. Actuator torques for the optimized motion

These results show actuators torques which saturate and reach motors characteristics limits (Fig.

5). With our motion planning, it is possible to avoid saturation of actuators (Fig. 6). This optimization of the motion leads also to limited slips of the compactor drums on the soil (Fig. 7) which

implies a better quality of asphalt compaction.

In the frame of compaction automation, this op- timized motion planning allows to design more

efficient control laws. Indeed, with an optimized

motion, the control of the compactor will be focus on rejecting modelling errors and external per- turbations (the wind, ...). While with ordinary

motion, the control law will also try to follow an

unfeasible motion which implies important slips on the asphalt so a lower quality for the road.

5. CONCLUSION

A motion planning which takes into account the

dynamic model of the compactor is presented in

this paper. Path computing for specific tasks of compaction and the computation of timing laws

have been developed to this purpose. Then the dynamic model of the compactor is used to check if the computed motion respects physical limitations of the compactor.

Motion planning is a necessary step in the implementation of a dynamic control for the compactor.

It uses all works done on the compactor automation in the past years, as well for modelling as for the identification of the compactor. Now, we can

consider the automation process of the compactor

in order to improve compaction quality.

6. REFERENCES

Canudas de Wit, C, B. Siciliano and G. Bastin

(1997). Theory of Robot Control. Chap. 1, pp. 4-29. Springer-Verlag. London.

Gautier, M. (1997). Dynamic identification of robots with power model. In: IEEE International Conference on Robotics and Automation. Albuquerque, pp. 1922-1927.

Guillo, E., M. Gautier and M. Froumentin (1999).

Dynamic modelling and identification of a

compactor. In: Proceedings of International

Symposium on Automation in Road Construction. Madrid, Spain.

Khalil, W. and D. Creusot (1997). Symoro+: A

system for the symbolic modelling of robots. Robotica 15, 153-161.

Khalil, W. and J.-F. Kleinfinger (1986). A new

geometric notation for open and closed-loop

robots. In: Proceedings of IEEE International

Conference on Robotics and Automation. San

Francisco, California, pp. 1174-1180.

228
Facade Cleaning Robot for the Skyscraper

Thomas Bock, Alexej Bulgakow, Shigeki Ashida

The Chair for ReaHzation and Informatics of Construction

The Faculty of Architecture, Technical University of Munich

Arcisstr. 21 80333 Munich, Germany, Tel. +49-89-289-22100, Fax. +49-89-289-22102

Email: Thomas.bock(g)bri. ar.tum.de : bulgakow(a),bri.ar.tum.de : ashida@bri.ar.tum.de

ABSTRACT: Considering all available basic conditions, a semiautomatic cleaning version can be best implemented under technical, organizational and economic constraints. All cleaning processes are executed by means of a service robot. The robot is controlled by just one operator. The cleaning quality

of surface remains constantly excellent and the cleaning efficiency increases significantly.

KEYWORDS: Cleaning Robot, Fa9ade cleaning. Semiautomatic, Vacuum suction. Nacelle traveling,

Skyscraper

1. INTRODUCTION

The fa9ades of skyscrapers have to fulfill above all a representative function for the companies. The

appearance of the surface of facades plays thereby

for the entire corporative identity. The

environmental impact results in an intensive

contamination of facades. The modem building

materials react quite differently to influences of the

climate. Even high-quality natural stone facades

attract visible tracks of the pollution. Therefore

facade surface must be cleaned regularly. The

frequency of the cleaning can be executed in the

cycle of decades depending on degree of pollution.

The cleaning cycle and intensity are determined by

economic constraints. Recently self-cleaning glass

facades are available. But as far as existing fa9ade

are concerned a reduction of labor cost share by

robotic maintenance is required. The higher the

degree of pollution is, the more intensive cleaning

agents and instruments must be used or shorter

cleaning intervals.

The first skyscraper with anodized aluminum

facades was built in the seventies in Munich. These

facades were offered as maintenance-free. The

cleaning was not considered necessary, because the

anodic oxide coating is hard and weatherproof The

experience showed however that anodized facades

get dirty by environmental strains. A further

important argument for cleaning was not considered

likewise; because the more dirty a facade is, the

higher is the corrosion grade. Additionally the

contamination increases the original surface, which

makes it more absorptive and vulnerable for larger

quantities of corrosion stress. By neglecting

cleaning the fa9ade can deteriorate as far as it will

be impossible to keep its original quality. Therefore

repetitive low impact maintenance by robotic

cleaning anticipates real estate valueless.

Photo 1. Skyscraper with anodized facades

229
Cleaning of anodized facades by robots is required

for the following reasons: Reduction

of chemical pressure

of contamination

of structural changes of the original

surface

Cost-profit optimum

of maintenance

of fa9ade appearance

of real estate value

2. Kinematic Solutions

2.1. The cleaning operation

The basic cleaning of an anodized aluminum surface

takes place in two levels: Pre-purifying and main

cleaning. Pre-purifying consists in spreading the

cleaning agents on the surface and washing off with

soft brushes. For the available exterior wall sections

it is optimal to use rotary soft brushes. At the same

time three exterior wall sections are processed. For

the setbacks between the exterior wall sections

brushes of an appropriate diameter must be used.

These three brushes that are propelled with an

electrical servo actuator form the first part of the

cleaning and into those one another current waves

are accommodated. At the start of the purification

process three brushes are inserted into the cracks

and three others received meanwhile the contact with the lamella surface. The contact pressure of

rotary brushes to the surface can be determined

before the cleaning and depends on the degree of

pollution of the surface. The solvent is supplied by

the conditioning plant and led back by a special

suction procedure completely into the system.

Thereby a closed cycle is implemented.

The main cleaning of the surface with a cleaning

agent is executed with the help of the second section

of the cleaning (Fig. 1). The brushes are exactly the same arranged, whereby for the anodized aluminum

surface fine wool is used. Both brush series are arranged to each other with a distance from 30 cm. Washing the cleaning agent which arrears off must

take place right after the main cleaning, so that the

waste water does not dry up. In addition the third

series of cleaning brushes are used. The module

with two brush series can be changed, in order to execute the job of a thin water-repellent protective

film with following polishing out.

Fig. 1. Brushes in the Main Cleaning Step

2.2. The robot platform

The mobile platform of the facade-cleaning robot

serves as carrier system for the cleaning operation.

The necessary contact pressure to four telescope

rods with vacuum plate to the facade surface is ensured at the cleaning process. Additionally they

enable an occurring of the back-up ring

constructions of the towers (Fig. 2).

Beside the cleaning brushes on the platform the

spray nozzles are arranged for the job of a waterrepellent protective film. This platform does not need guide rails at the facade, presupposed the robot

autonomously, without nacelle. The progressive

movement of the robot can take place via a successive separation and new positioning of each

of the four suction cups. The switch-selectable bars

form a basic yoke construction for the robot. This

construction is completed by two rails for the

progressive movement of the cleaning operation. All

components of the kinematics are coordinated. The

robot can be operated in automatic and

semiautomatic process and used at different facades.

The load entry into the facade is small. The twocoordinate construction of the robot can be served

230
Fig. 2. Structure of the Mobile Platform

quite easily. This kinematic pattern of the facade

cleaning of robot presupposes itself a problem-free

in the fulfillment of safety requirements.

3. Applying concept

3.1. Implementation

Considering all of available basic conditions, a semiautomatic cleaning version can be best

implemented under technical, organizational and

economic request. The robot is accommodated

thereby on a nacelle of the traveling unit, adjusted

while the whole cleaning process to complete and

with the transfer of a user (Fig. 3). The function of

the user exists in the monitoring of the cleaning

process and in the execution of the cleaning of the

facade surface in difficulty accessible zones by

hand.

Table 1. Technical data of

Nacelle of the traveling Unit

The latter enables a simplification of the robot

system and thus a cost saving.

The robot can be used also at surfaces of other type,

e.g. for the window surface cleaning.

3.2. Application of the cleaning operation

When an electromechanical system (power supply,

engines, transmissions) is designated for the drive of

the cleaning, it activates the cleaning brushes. The

main parameters of the drive are performance, rate, precision, controllability, dimensions, weight and

price. The special feature of the electric drive

consists of the fact that they are indicated

particularly by the small dimensions, an easy

control, high precision, maximum stress and

reliability (Fig. 4).

the facade cleaning robot

Type of cleaning Brushes

Brush size Length: 300 mm

Thickness: 50 mm

Drive Automatic guidance of the cleaning heading

Heading pressure Manual adjusts

Dressing plant Negative pressure system

Capacity 4,0 kW

Cleaning performance 50 mVh

Advantages Small personal expenditure

Good and safe cleaning quality

Weight 75 kg

231
LR ; Position regulator, GR ; Speed regulator, SR ; Power regulator, i U ; Converter, M ; Motor, LG ; Position sensor, GG ; Speed sensor, SG ; Power sensor

f

Fig. 4. Main Scheme of electrical operation

Regardless of the relatively low performance and

quite high price, the electric motors at the best fit for the cleaning robot of the facade.

3.3. Application of the robot platform

The platform of the robot is equipped with a pneumatic drive. The vacuum cups serve above all in order to protect the contact pressure of the robo^

to the surface during the cleaning process. Additionally they permit a progressive movement in up and downwards along the facade. The robot is held by the wire rope of the traveling unit. The vacuum attraction is stopped normally as a function

of the entire mass of the robot, either by the degree

of the vacuum or by the number of suction cups. These adjustments will be made before beginning of

the work and do not need to be corrected during the

job.

Adaptive vacuum cups react completely differently.

At the Fig. 5 an appropriate structural variant is represented. The vacuum cup consists of the

pneumatic cylinder (1), where the lower output the

suction cup is in form of an open vacuum chamber

(2). The vacuum chamber is connected through the

connecting piece (3) with a vacuum pump. The

entire device is connected by the coupling (5) with

the lifting machine. The axle (4) forms a link

connection to the piston rod (6) of the cylinder. The

vacuum chamber has additionally a valve (7), which

is a connection to the outside. Between the housing

of the pneumatic cylinder and the coupling the

torsion spring (8) is arranged. When releasing the

instruction for touching the object, the valve is closed. In the vacuum chamber a vacuum is created

by the compressor. If the load (e.g. because of the

wind conditions) exceeds the nominal value, the

housing of the pneumatic cylinder shifts relative to the coupling downward, the torsion spring stretches,

the piston space of the cylinder becomes larger, so

\; '

Fig. 5. Adaptable Vacuum Sucker

232
that the vacuum in the vacuum chamber correspond

to the load of the robot increases. Suction force

increases, and holding of the robot becomes more

reliable. The more largely the difference between

the nominal and the actual value of the load, the

larger the shifts of the housing of the cylinder, the

volume of the piston space and thus the suction

force of the grip arm.

3.3. Control concept

The facade-cleaning robot can be differently

served. In the case of a semiautomatic version the

adjustment of the robot is executed in the working

position and monitoring of the trial process of a

user, who is with the robot in the nacelle of the

traveling unit. The robot can be controlled also by means of a remote maintenance (Fig. 6). The

parameters of the cleaning are controlled thereby

with a monitoring camera and different sensors. The user has the function to start the purification

process and react if necessary to occurring

messages. A permanent monitoring of the system

by the user is not necessary. However the use of a monitoring camera increases substantially the price

of the cleaning robot. The electric power supply of

the robot can take place by cables or via a cable

attached on the nacelle.

4. CONCLUSIONS

Considering all of available basic conditions of

technical, organizational and economic constraints,

semiautomatic cleaning version can be best

implemented. The cleaning process is executed by

the robot. The check of the process and adjusting

the robot are implemented by an operator. The

second worker can be saved. The quality of the

surface remains constant and the cleaning efficiency

increases significantly.

Emergency Stop Control

Indicator

A.

Joystick

Fig. 6. Remote Controller

233
I
DEVELOPMENT AND APPLICATION OF AUTOMATED

DELIVERY SYSTEM FOR FINISHING BUILDING MATERIALS

Doyama Atsuhiro, Hamada Koji, Kaneko Tomoya, Shiokawa Takashi

Building Construction Engineering Department, Teclinical Research Institute,

OBAYASHI Corporation http://www.obayashi.co.jp/

4-640 Shimokiyoto, Kiyoseshi Tokyo 204-8558, Japan

E-mail; doyama @tri.obayashi.co.jp

Abstract: The authors have developed an automated deUvery system for finishing building

materials with the aim of reducing dehvery costs and improving efficiency. This system is composed of two kinds of automated equipment, and managed by a deUvery scheduUng

system via the Internet. It has been applied to the construction of a high-rise building in Osaka City, where it performed all deUvery tasks with high efficiency. Furthermore, the dehvery scheduhng system reduced the time spent by all foremen and managers on dehvery

work. This paper describes functions and features of the system and some application

results.

Keywords: Automation; Delivery Schedule; Finishing Work; High-rise Building; Internet

1. INTRODUCTION

Delivery of finishing materials and

equipment via a construction lift or elevator

(henceforth, EV) is a bottleneck in construction of high-rise buildings. It is therefore very important to improve delivery

performance. Moreover, transportation does

not add value to a building, so it is important to evolve its mechanization and automation.

Therefore, an automated delivery system was

developed for a 56-story high-rise building in 1995 As a result of its application, the

following problems remained: 1) to enable the

system's application to a smaller construction

site in an urban area, 2) to reduce the number

of temporary EVs by using the automated

delivery system even at midnight, and 3) to reduce the manpower required to input data

into the system.

Delivery efficiency would be increased by

solving these problems. Furthermore, by

reducing the number of installed EVs, it is possible to cut down delivery costs. We have

been improving the automated delivery system

since 1997. During this period, partially

improved systems or individual pieces of

automated equipment have been applied to more construction projects.

2. GENERAL STRUCTURE OF

AUTOMATED DELIVERY SYSTEM

A new automated delivery system has been

developed, and was applied to the construction

of a 24-story high-rise building in Osaka City

in 2000, as shown in Table 1. This new system

is composed of two kinds of automated

equipment: an automated device that can

transfer materials to an EV (henceforth.

Transfer Equipment) and an Automatic Guided

Folk-lift (henceforth, AGE). It is managed by a web delivery scheduling system via the

Internet (henceforth, WSS). Its structure is shown in Fig. 1

A multi-stage rack suitable for a narrow

space was adopted that enabled materials to be

easily removed from every rack. As a result,

the area of the storage facility was decreased to about 30 percent that of the previous

application. WSS can access the Internet, which enables the EV to be applied without an

operator needing to visit the construction site. By sharing the schedule information among

several sub-contractors, it is possible to allocate the EVs hours of use. The Internet was used to obtain the input from the subcontractors' office, also achieving labor

saving.

Table 1 Specifications of The Applied Building

Location Osaka Japan

Building Use Office Building

235
structure and Steel-Frame

Size B3F/25F/PH3F

Total Floor Area: 64,621

Mar. 1 yyo u uci.^uu i Period

3. AUTOMATED EQUIPMENT

The authors planned to cut down the number

of installed EVs by applying the automated

delivery system. We estimated the overtime

work at a maximum of 4 hours per a day

during the height of finishing work. The

automated equipment was mainly used for

delivery during overtime work for basic

materials such as gypsum plasterboard and

lightweight steel. The layout of the ground floor used as a

storage facility is shown in Fig.2. Trucks

carrying materials enter the building and the

materials are unloaded onto the floor. The

AGF operates automatically from its home

position, and then unloads the materials onto

the multi-stage rack. During the automated

delivery work, the AGF automatically removes

the materials from the multi-stage rack and

conveys them to the front of the EV (HCE2800

in the figure). AGV's operations are repeated

according to the operator's pre-inputted orders.

After the automatic Transfer Equipment in the

EV loads the materials, the EV is taken up to the delivery floor by an elevator operator.

When it arrives at the delivery floor, the

automatic Transfer Equipment automatically

unloads the material from the EV.

3.1 AGF and Multi-stage Racks

The AGF's rated capacity is 1500 kgf. It runs along an electromagnetic guide wire. This

guidance system is more reliable than others

such as light reflex or magnetic tape. An AGF

removing material from a multi-stage rack is shown in Fig.3. We reduced development costs by adapting a standard machine to an AGF by

attaching a sensor and radio equipment needed

for construction work. If the AGF detects any

obstacles in the traveling direction with its photosensors or supersonic sensors, it begins to slow down to avoid contact with them.

Moreover, the AGF and Transfer Equipment

have a collision avoidance system that utilizes radio signal communication. The AGF can

deliver materials safely and efficiently in a narrow space. We applied 2m- and 4m-wide

Construction

Elevator Multi-stage Rack

Delivery Scheduling System

via the tnteujjgt AutpniSlio Guided

Transfer Equipment

Folk-! ift.

Fig. 1 The Structure of Automated Delivery System

(D

® © ® © ©

®

Transfer

Equipment

©

©

©

EV

(HCE2800BS

TTTl'ITm.

lilif

u

017

mm.

236

Elevation View of the MultiType Rack
racks adapted to the form of object materials.

An address number was set for each rack. After the operator inputs the address number

into the AGF's control panel, it continuously

delivers materials up to 99 times.

3.2 Automatic Transfer Equipment

The Transfer Equipment shown in Fig.4 is attached to an EV. Materials are loaded and

unloaded automatically by an elevator

operator. By automating the unloading work, it

is possible to reduce delivery time and achieve

labor saving. The Transfer Equipment is as

light as 800 kgf, whereas its rated capacity is 2000 kgf. It is supplied power directly from the

EV via a flexible cord, so it does not need to carry a heavy battery. Moreover, when an EV

is used to transport workers or lightweight

materials, the Transfer Equipment can be

easily removed from it in order to maximize its capacity.

4. WEB DELIVERY SCHEDULING

SYSTEM

4.1 Structure of Web delivery scheduling

system

The structure of the Web delivery scheduling

system (WSS) is shown in a Fig. 5. It is composed of three kinds of hardware: a TAterminal for application; a WS-Web shared

new reservations, deletions, modifications, and

confirmations for use of an EV. The WS

implements script in response to requests from

Fig. 3 Automatic Guided Folk-lift

Fig.4 Transfer Equipment

_ Web Browser

Web Page for Application

Web Page for Expression

of schedules

TA

Terminal for Application

Web Page for Application

Script of Application v__/

Reservation

CGI/

Perl

Web Page for Expression

of schedules

Script of Schedules

Schedules

of EV

WS

Web Shared Server

Database in charge of E

V

TM

Terminal for Management

Fig. 5 The structure of The Web Delivery Confrol System

server; a TM-terminal for management. The the TA. Since a CGI pearl is used for script, a TA is a computer installed in each hosting service provided by a general Internet subcontractor's office, which accesses the service provider can be used. The TM is a

Internet and processes several assignments: computer installed in a construction office,

237
which downloads data for a definite period and

makes a schedule based on a predetermined

algorithm and uploads these data to the WS as fixed information. Moreover, the TM is operated by the EV's manager and makes EV

regulations such as holidays and regular

services, and uploads these data to the WS.

Consequently, an EV reservation can be

restricted. In addition, the TC can indicate past

records of an EV in contrast to plans. Fig. 6 is a calendar indication that shows application

conditions. Detailed application conditions

obtained from the bar chart can be confirmed

by choosing the reservation day (Fig.7).

4.2 Management of Transfer Web delivery

scheduling system

The EV's manager and subcontractors held a

: ±-B ' 1 ri± ± R HI am

Fig.6 Calendar Indication of WSS

the EV's manager downloaded the application

data and closed the applications. After the EV

schedule's adjustment, the administrator

uploaded the determined schedule to the WS.

5. APPLICATION RESULT

5.1 Automated Equipment

We analyzed the EV's operating rate - Or - described by:

Tn = To - Ti

Or = Tn/To (1)

Where: Tn is net EV operating time, To is EV operating time, and Ti is EV downtime

(waiting for materials, workers, etc.). Fig.8 shows the EV's operating rate transition every day during the operating

period. Fig.8 contrasts the Or of this system

with that of the conventional system for the

— Sl51fFg»«JU —

Fig.7 Bar Chart Indication of WSS

Automated Delivery System

Conventional System

lAverage wte of Operation

UEIe\mto!;77.;%-

Lapsed Days Fig.8 The Transition of EV's Operating Rate

meeting once a week to adjust the EV schedule same construction scale. Fig.8 indicates that for the following week. Before the meeting.

238
the automated system average was higher than

that of the conventional system.

Fig.9 compares the delivery performances of

the conventional and automated systems. The

conventional system's performance is assumed

to be 100. The average weight between the two

systems is approximately equivalent, whereas

other items of the automated system exceed

those of the conventional system. In particular,

the automated system shows a delivery

manpower saving of nearly 45 %. By

comparing the two systems, we confirmed that the delivery capacity per unit time of the

automated system was 1.44 times that of the

conventional system.

It thus follows that the automated delivery

system is more efficient than the conventional

system. The main reasons are:

1) The application of full-time material

transportation workers - these workers can

deliver materials stocked on multi-stage

racks in the EV's spare time

2) Setting of multi-stage racks - this enabled

the EV to deliver materials even when there was a delay of delivery trucks

3) Introduction of two kinds of automated

equipment - these enabled a reduction of

delivery work and labor saving

5.2 Web delivery scheduling system

We analyzed logs stored in the server of the

Web delivery scheduling system for seven months from August 2000 to March 2001.

Fig. 10 shows the transition of the number of

log-ins according to the type of business. This

shows that the total number of log-ins was

2700, and the average weekly logins was 84. Furthermore, the number of log-ins decreased

gradually with time. The number of log-ins

according to the type of business confirms that the percentage for building equipment was

55.4 %, and the percentage for building

finishing work was 26.4 %.

Fig. 1 1 shows the percentage of access points

to the WSS. As shown, the access points to the

WSS were mostly out of the construction

|E3Conventional System BAutomoted System

Monpower

Rote of Operation of ElevotoruKuj

Average Cycle

Time(min)

0 20 40 60 80 100 120

Fig.9 The Comparison of Delivery Performance

office.

7%

Construction office

Tfie others

93%

Fig. 1 1 The percentage of access points to the WSS

^JV BConcrete,RebQr J pinery .Gloss DFinishing BPIumbing 13 Air-conditioning BErectric Instrotion Elevator

Fig. 10 The Transition of The Number of Log-ins

239
Fig. 12 shows the number of log-ins

according to the time period. As shown,

reservations during regular working hours (8 a.m. -5 p.m.) occupied 60 % of the total, whereas those during holidays or from

midnight to early morning occupied 40 % of

the total. We carried out a questionnaire survey of

about twenty users of the Web delivery

scheduling system. The findings of this questionnaire survey include:

1) Although there were many inexperienced

users, the average log-in time was short,

about ten minutes, and the operability and

speed were highly rated. 2) There were many positive comments on

the laborsaving ability.

3) The assignment, such as data input and

adjustment, of the EV's manager was

reduced by 20%.

In view of the results so far achieved, we

concluded that it is very effective to use the

Internet for EV management, because the EV

can be reserved any time and from any place.

6. CONCLUSION

An automated delivery system has been

developed for reducing delivery costs and

improving delivery efficiency. Results show

that the delivery capacity per unit time of the

automated system is 1.44 times that of the

conventional system, and it achieves a 45%

delivery labor saving. In addition, using the

Web delivery scheduling system reduced the

manager's assignment of the EV. We covered

development costs of automated equipment for one project. Results show that total delivery

costs can be as little as initial costs because of

the reduced number of installed EVs.

We believe that delivery costs can be reduced even further by expanding the application

range of the automated delivery system.

Moreover it is hoped that the automated

delivery system will develop into construction

logistics by improving the management

method in a storage facility and expanding the

WSS's functions.

0 2 4 6 8 10 12 14 16 18 20 22

Logi ned Ti rre ( hour

)

Fig. 12 The Number of log-ins According to The

Time Period

References

[1] Hamada, K et al. (1996) "Development of an Automated Material Transportation System

for a High-rise Building", Report of Obayashi

Corporation Technical Research Institute,

No.52, 113-120.

[2] Hamada, K et al. (2002) "Development of

Automated Delivery System for Finishing

Building Materials", Report of Obayashi

Corporation Technical Research Institute,

No.64, 1-6.

[3] Doyama, A et al. (2002) "Development and

Application of Automated Delivery System for

Finishing Building Materials", 14th

Construction Robot Symposium, 19-26.

240
UNMANNED CONSTRUCTION SYSTEM: PRESENT STATUS AND

CHALLENGES

Yoshio Ban^

ABSTRACT: This report analyzes past unmanned construction system done at the

Unzen-fugendake and Usuzan volcanoes to organize the present status of

unmanned construction systtem from varied perspectives, describes challenges and

countermeasures, and introduces future prospects.

Unmanned construction systtem have been done to perform emergency

countermeasure work and restoration work at disaster sites. Remaining challenges

include development of methods of performing remote hillside reforestation in devastated areas, remote traveling crane operation. Turning to the future, it is proposed that noise and vibration be provided around the operator's seat in remote

control rooms to create a sense of realism. Unmanned construction systtem should

be used not only at disaster restoration sites, but also used effectively to increase

safety at ordinary construction sites. KEYWORDS: Unmanned construction, remote operation, hillside reforestation,

traveling crane, rough terrain crane

1. INTRODUCTION

Unmanned construction is work performed by

remotely operated construction machinery that corresponds to an operator controlled robot.

Unmanned construction was used in civil engineering work for the first time in Japan in 1969 when an underwater bulldozer was used

to excavate and move deposited soil during

emergency restoration work at the Toyama

Bridge that had been blocked by the Joganji

River disaster. Since then, unmanned

construction by excavators inside pneumatic

caissons and by backhoes have been carried

out, but the restoration work following the

volcanic eruptions that began in 1994 at the

Unzen-fugendake Volcano and restoration

work executed following the eruption of the

Usuzan Volcano in 2000 were the first executions of large-scale unmanned

construction and have spurred rapid progress

in unmanned construction technologies and

encouraged their wide use.

This report analyzes recent applications of the

unmanned construction method including

those at Unzen-fugendake and Usuzan

Volcanoes, outlines the present state of

unmanned construction from multiple

perspectives, discusses fiiture challenges and measures to overcome them, and concludes with

future prospects for the method.

2. ANALYSIS OF THE PRESENT

STATE OF UNMANNED

CONSTRUCTION

The following are analyses of unmanned

construction executed at the Unzen-fugendake

and Usuzan Volcanoes.

2.1 Work Categories

Past executions can be broadly categorized as emergency works executed at the time of a

disaster and later restoration works. The method

has often been used after disasters including

those caused by debris flows and pyroclastic

flows, the collapse of soil caused by earthquakes

and so on.

The following are the principal categories of

work performed by this method.

'Advanced Construction Tecknology Center, 2-15-6 Otsuka Bunkyo-ku, Tokyo, Japan (T) 03-3942-3992

(F) 03-3942-0424 E-mail ban@actec.or.ip

241
Table 1 . Principal Categories of Work Performed

by this Method

Work Category Description of the works

Rock removal work Excavation, loading,

transporting

Structure demolition and removal work

Crushing and pulverizing concrete and cutting steel reinforcing bars, loading and

transporting the products

Large sandbag placing

work

Transporting and placing

Concrete block work Removing obstructions,

leveling ground, placing

Temporary road work Cutting, filling, and

compaction

Erosion and sediment

control dam work

Excavation, embanking,

backfiUing, compaction,

pouring concrete Watercourse work Excavation, pouring concrete, placing foot protection blocks

Tree felling work Cutting, stumping, transporting

RCC work Transporting, spreading and

leveling, compaction, spraying,

laitance removal

Ready-mix concrete workInstalling form materials, pouiing and compacting

concrete SoU form work Excavation, loading,

transporting, removing form

materials

2.2 Remotely Operated Construction

Machinery

The following are types of remotely controlled

construction machinery that have been used

frequently.

Table 2. Frequently Used Remotely Controlled

Construction Machinery

Machine Type Standards Back hoes 0.6 to 4.3 m^

Bulldozers 16 to 80

1

Dump trucks 32 to 80

1

Crawler type trucks (large tracked

trucks) 6 to 12 t

In addition, towed transport vehicles, trucks,

tractor shovels, crawler cranes, self-propelled

cranes, crane trucks, vibrating rollers, etc. have

been used.

2.3 Unmanned Construction Equipment

The following are the types of unmanned

construction equipment that have been used

according to the radio transmission distance.

Table 3. State of Use of Unmanned Construction

Equipment

Radio

transmission

distance

Remote

operation room

Radio

relay truck

Mobile camera

vehicle

Stationary camera

Shorter than 50 m

Used according to circumstances

50 m to 150 m

Longer than 150 m

Unmanned mobile camera

Unmanned backhoe and unmanned bulldozer

Remote operation room

Figure 1. Configuration of Unmanned Construction

Equipment

2.4 Types of Radio Equipment

The frequencies of radios used for unmanned

construction are 400 MHz, 2.4 GHz, 50 GHz etc. Various innovations include lowering their transmission power to limit their range, thereby

avoiding the need for licensing. Each radio base

station is selected according to the transmission

distance, rectilinearity, channel capacity, data

transmission capacity, licensing requirement,

and other differences, and according to the work

environment.

2.5 Transporting, Assembling, and

Modifying the Macliinery

The number of days required to obtain the

machinery is a problem that must be resolved,

particularly when performing emergency

242
restoration at the time of a disaster. The

number of days required to acquire the

machinery varies sharply between cases where

machinery abeady equipped with remote

control systems is transported to the site and

cases where the hydraulic circuits of

construction machinery are modified. In the

past, it has taken a few days in the former

cases and a few months in the latter cases.

2.6 Work Efficiency

It is said to be roughly 60% to 70% of that of

manned construction, but the efficiency falls sharply in cases where the machinery moves,

where materials are transported in dump trucks

for example, and in cases where high precision

work is necessary.

2.7 Controlling and Inspecting the

Construction

Work requiring extensive finished work

control is now done by manned methods. The

following systems are used for unmanned

construction.

1 ) Automatic tracking type total station

A prism that functions as a target and a marking spray device are installed on the

front of a remotely controlled back hoe, and

the automatic tracking total station measures the target to mark the position to

install the back hoe and to confirm its position is correct.

2) GPS precise real time positioning system

This technology accurately computes the

position of each working machine by

combining information about the position

of the machines obtained by RTK-GPS

with status information provided by sensors

installed on various parts of the

construction machinery. For example, in some cases, GPS receivers and prisms have

been installed on bulldozers or vibrating

rollers etc. so the system can perform

coordinate control by obtaining measured

data to control the spread thickness or the

compaction frequency.

Photograph 1. Unmanned Measurement Systems

3. FUTURE CHALLENGES FACING

UNMANNED CONSTRUCTION

AND MEASURES TO OVERCOME

THEM

3.1 Work Categories (introduction of

unmanned hillside reforestation)

It is expected that in addition to various work

categories in sediment and erosion control work

such as permeable dam construction or precast

block masonry work, unmanned executions will

play an important role in hillside work in

devastated areas carried out to prevent disasters

and to conserve the environment.

Hillside work is broadly categorized as hillside

foundation work and hillside reforestation work.

Hillside foundation work is done to lay the

foundation for a future forest by stabilizing

deposited sediment, while hillside reforestation

refers to introducing trees directly on hillsides to form forests that will prevent the runoff of

sediment. Execution methods that can be used

for the former, hillside foundation work, are concrete block masonry work, placing large

sandbags, and placing boulders at the site: methods that can be executed with existing

technologies. The latter, hillside reforestation,

has been done as unmanned reforestation

spreading work: spreading seeds and other

materials with a high speed belt conveyor type

spreading machine. And although it has not been

done unmanned, seeds have been sown from the

air by manned helicopters for several decades.

243
Photograph 2. High Speed BeU Conveyor Type

Spreading Machine

But on devastated ground where the soil condition is poor and the sediment moves,

reforestation by transplanting seedlings is more

reliable than seeding work, so there is a demand for unmanned transplanting methods.

Hillside work

Hillside foundation work

Hillside

reforestation work

The wood frame block root pot method has

been proposed as an unmanned transplanting

work method. Seedlings are grown inside

wood framed blocks consisting of a wooden

frame, (approx. 1.0 m»1.0 m), net (palm fiber

etc.), water holding material, and leaf mold,

and the frames are placed in rows by an unmanned backhoe equipped with a holding

device. This method does not require separate

works such as digging holes and mulching, and

it can be used on any slope where a backhoe

can be operated. It should be introduced as a working system in the future.

Figure 2. Image of Unmanned Transplanting

3.2 Remotely Operated Construction

Machinery (introduction of

unmanned traveling cranes)

In June 2002, the Ministry of Land,

Infrastructure and Transport of Japan announced

that it had begun to develop unmanned operating

technology for traveling cranes. Till now,

medium and large traveling cranes have never been remotely operated and developing the

world's first successful unmanned operating

system for large cranes will be a great

achievement. Because cranes may be installed in narrow places and on slopes, the crane chosen

for the development project was a rough terrain crane, a type that can be kept in a horizontal

attitude with an outrigger and handled in narrow

spaces, (lifting capacity: 50 tons)

A rough terrain crane, which is a type of

wheeled crane that is propelled by a single

engine and can perform crane work, travels easily over uneven ground because it is a four

wheel drive vehicle and all four wheels can be

steered. Traveling and crane work are controlled

from the same operating cab. Although

externally it appears more compact than a track

crane, it provides comparable lifting capacity. In Japan, therefore, most cranes manufactured are

traveling cranes.

The first step in the development is to decide

which traveling crane functions will be

performed remotely. Because cranes work while

installed in dangerous locations, almost all traveling and crane operation functions must be

remotely operated. Because unmanned

construction is performed rarely, it must also be

possible for the crane to be operated by an

244
operator sitting in the cab when it is used in safe places.

The next problems is attaching and detaching

loads. It is extremely difficult to attach loads to and detach them from the hook by the remote

control method. An automatic load detachment

device operated by a weak radio wave has

already been developed and is in use on small

cranes. The following two solutions are being

considered. One is to replace hooks with a newly developed device that attaches a load by

grasping it. The second is to limit attachment

work to manned areas. (If attachment work is limited to manned areas, the working range of

a 50 t class rough terrain crane will be about

60 m from the boundary of the manned and

unmanned areas.)

The next problem is the "prohibition on

leaving the operating location." Japanese law

includes a provision that states, "The operator

of a traveling crane shall not leave the

operating location while a load is still suspended by the crane" (Regulation for Safe

Operation of Cranes Etc.). Therefore, to comply with the Regulation for Safe Operation

of Cranes Etc., an operator's seat must be

provided in the remote control room and it must be equipped with a device that can

provide the same information available at the

operator's seat in the crane. Specifically, it is necessary to provide a system that converts the

boom angle, rotation angle, and other

quantities representing the state of the crane, overload warnings, and visual information

about the load and the wire (visual data) into

electronic data and transmits this data to the operating room.

When unmanned crane work has been realized,

it is counted on to be applied to various kinds

of work in dangerous locations. Expanding the

working radius of unmanned construction will not only permit execution of construction work

in previously inaccessible locations; it is also

counted on to permit the installation of larger

blocks, increasing work efficiency.

4. FUTURE PROSPECTS

4.1 An operator's Seat with a Sense of

Reality

When unmanned execution is too far away for

the operator to see the site, the operator remotely

controls the execution in a remote control room

while watching images transmitted from

television cameras. Even when relatively simple

work such as backhoe or bulldozer work is executed, the operator uses two or more

television cameras that provide views of the

overall scene and the view from the cab of the

machine. To perform work requiring detail operations or depth perception, special measures

are taken at each site, installing another camera

providing a view from the side.

But during manned work (when the operator sits in the seat in the cab of the construction

machine), the operator operates the machine

while unconsciously obtaining information other

than visual information (noise, vibration,

deviation from the horizontal, etc.), and this difference is the cause of gaps in execution

efficiency, execution precision, and reliability

between manned and unmanned work.

In the future, the operator's seat must be made

more realistic by adding noise, vibration, and

other information useful for operators so that they can make the maximum use of their five senses.

4.2 Changeover to Safer Construction

Methods

Unmanned executions can be divided into the

following three stages.

(1) Emergency measures work at a disaster

location

(2) Restoration work at a disaster location

(3) Ordinary work at dangerous locations

Now that unmanned construction has been

firmly established and has gained a good

reputation as disaster site restoration work

method, it is expected to advance to the next

step: as a method of achieving safer work at normal construction sites.

The following are considered to be dangerous

places to execute civil engineering works.

245
• Slopes at risk of failure (sediment control

dam work, hillside work, slope work)

• High places (slope work, concrete dam

work)

• Riverbeds and lake bottoms (dredging work)

• Seabed (dredging work, leveling riprap)

• High pressure environments (pneumatic

caissons)

• Places at risk of a gas explosion (vertical shaft excavation)

• Places exposed to radiation or dioxin and

other hazardous substances (structure

demolition and removal work)

Adopting unmanned construction for work at such locations can be counted on to have the

following effects.

• Improved safety

• Reduction of temporary work costs and

safety measure costs

• Improved operating rate (shortening

construction periods)

• More precise higher quality construction

For example, seabed dredging has been done

from the surface using a conventional crab

barge or pumping barge, but if dredging is done by an unmanned machine traveling on the

seabed, the work can be done safely during

heavy seas, sharply increasing the operating

rate (work period) and execution precision

(quality). This technology has already been

used for more than ten years remotely

controlled by a wired system.

5. CONCLUSION

The development and popularization of

unmanned construction will have many effects: improving the safety of construction work at the same time as it shortens construction periods and

guarantees high quality. This will, in turn, improve the image of the construction industry

that tends to be negative in Japan and spur

progress in IT and robotics.

In the future, we wish to accurately assess the

present state and challenges facing unmanned

execution technologies and work to popularize

their use.

REFERENCES

1) Advanced Construction Technology Center

(ACTEC) (editor): Handbook on the use of

unmanned construction in emergencies

(published in August 2001)

2) Ito H.: Understanding traveling cranes (published in December 1994)

246
Report of the NIST Workshop on Automated Steel Construction

by

Alan M. Lytle^ Kamel S. Saidi", William C. Stone", and John L. Gross^

ABSTRACT: The Building and Fire Research Laboratory of the National Institute of Standards and Technology, in cooperation with the American Institute of Steel

Construction, sponsored a workshop on automated steel construction. The purpose

of the workshop was to investigate the development of new technologies to

facilitate automating the steel construction process. Desired outcomes included a

clear definition of issues and constraints, the identification of candidate

breakthrough technologies, and the development of a research roadmap. A

description of the workshop structure, agenda, and preliminary results are presented.

KEYWORDS: construction automation, automated steel erection

1.0 INTRODUCTION

Productivity, reliability, and safety are the three

predominant issues facing the steel construction

industry today. In both industrial facilities and

commercial buildings, hot-rolled steel members

are typically joined together either by welding

or using high strength bolts. These processes

require a significant amount of skilled labor,

and in the case of high-rise construction,

constitute one of the most dangerous specialties

in the already hazardous construction industry.

Inspection is difficult and time consuming, and

often, the connections are the weakest link in

the resulting structure.

The steel construction industry faces significant

challenges to remain competitive. The

following two statements succinctly summarize

the issue [1]:

"The U.S. construction industry must begin

to move away from a nearly exclusive laborintensive business and towards automation

to be competitive in the ever-shrinking

global marketplace."

"Decreasing fabrication and erection time

for steel frame buildings, while increasing

the safety of workmen during construction

are issues that must be addressed, and

provides the motivation for automated

construction."

According to the American Institute of Steel

Construction (AISC), a 25 % reduction in time

required to erect a steel frame structure is needed. In response to this stated need, the

NIST Building and Fire Research Laboratory

(BFRL) and AISC co-sponsored a workshop on Automated Steel Construction at the NIST

campus in Gaithersburg, MD on June 6 and 7, 2002. The workshop brought together steel

' Official contribution of the National Institute of Standards and Technology (NIST); not subject to copyright in the United States.

' NIST, BFRL, Materials and Construction Research Division, Mail Stop 86 U, Gaithersburg, MD 20899-861 1; alan.lytle@nist.gov, kamel.saidi@nist.gov, william.stone@nist.gov, john.gross@nist.gov.

247
producers, fabricators, designers, erectors, and

construction automation experts to discuss

factors affecting the steel construction industry

and to identify possible courses of action to

assist the industry. The desired outcome from

the workshop was a clear definition of issues

and constraints, identification of candidate

breakthrough technologies, and the

development of a research roadmap. This

report presents information contained in the

keynote addresses and results of the working

group breakout sessions.

2.0 WORKSHOP FORMAT

The workshop convened over a period of 2 days,

during which the participants discussed the

challenges faced by the US steel construction

industry and the various technologies that could

be used or developed in order to meet those

challenges.

There were a total of 17 non-NIST attendees at the workshop. Participants included

representatives from 3 steel producers, 3 steel fabricators, 2 steel designers, and 6 steel erectors, as well as 3 construction robotics and

automation researchers. NIST researchers

included personnel from BFRL's Materials and

Construction Research Division and the

Manufacturing Engineering Laboratory's

Intelligent Systems Division.

The workshop was divided into three sessions over a day and a half. Each session included a

topical presentation^, a breakout session, and a

full group discussion.

3.0 DETAILED AGENDA

3.1 Day One

Day one began with an introduction by the NIST

Construction Metrology and Automation group

(CMAG) leader. Dr. William C. Stone.

^All workshop presentations available on the CMAG

website: www.bfrl.nist.gov/861/CMAG/index.html

The introduction was followed by a presentation

by Dr. Carl T. Haas of The University of Texas

at Austin entitled "Automation in Steel

Erection" [2]. Dr. Haas" presentation included a

definition of industry problems, possible

opportunities for automation, and a review of some previous construction automation research

and development activities. Specific

opportunities for automation discussed included:

• Robotics and process integration in the

fabrication shop

• Materials tracking using radio frequency

identification (RFID) tags, bar codes, etc. • Design of connections for compliant

assembly

• Pre-assembly to minimize field connections

• Integrated project processes, databases, and

4-D models

• Positive control of members and

subassemblies using manipulator arms,

inverse Stewart platforms, etc. • Automated welding, bolting, adhesion, etc. • Global positioning and locating systems

Examples of previous applicable research and

development presented included:

• Lehigh ATLSS connection [3] • NIST RoboCrane [4] • Japanese automated building systems [5,6,7] • UT Large Scale Manipulator [8]

Following the first presentation, the workshop

participants were divided into 4 groups. Each

group was tasked with forming a list of

technologies that could benefit the steel construction industry and a corresponding list of

criteria that could be used to rank those

technologies.

The lists of technologies from the 4 breakout

groups were then presented to all the workshop

participants and discussed. A single list of the

most promising technologies and a single list of

evaluation criteria for those technologies was

then developed by the workshop participants.

These lists are presented in Tables 1 and 2.

248
The afternoon session of day one began with a presentation by the president of National

Riggers and Erectors, Inc. (Plymouth, MI), Mr.

Robert Dunn, entitled "Steel Erection and

Challenges" [9]. Mr. Dunn reviewed the

challenges facing the steel industry including

safety, quality, workforce aging, and the cost of

construction. He then reviewed various

elements of the erection process, presented a

cost breakdown of those elements, and projected

potential cost benefits of various process

improvements. Mr. Dunn stated the areas with

the greatest opportunity for potential cost savings include:

• Ground Operations (receiving, etc.) • Hoisting

• Ground Assembly

• Temporary Bracing

• Detailing

In his conclusion, Mr. Dunn outlined the

following 4 recommendations for application of

automation to steel erection and the corresponding potential cost savings:

1. Pre-assembly and/or modularization of

roof/floor/wall components can save 10 %

to 20 % of ground operations/hoisting costs which constitutes 45 % of total erection

cost - a 4.5 % to 9.0 % overall savings.

2. Optimizing crew sizes and using innovative

lifting/storage devices can save 15 % to 20 % of hoisting cost which comprises

30 % of the total erection cost - a 4.5 % to 6.0 % overall savings.

3. Use of "snug-tight" bolts in bearing

connections can realize savings of from

30 % to 35 % of this cost driver which

accounts for 30 % of erection costs - a 9.0 % to 10.5 % overall savings.

4. Semi-automated welding practices can save 2 % to 5 % of overall erection cost.

Following Mr. Dunn's presentation, the

workshop participants were again divided into 4

groups. Each group was tasked with forming a

list of challenges that the US steel construction

industry faces and a corresponding list of criteria that could be used to rank those challenges.

The lists of challenges from the 4 breakout

groups were then presented to all the workshop

participants and discussed. A single list of the

most important challenges and a single list of

evaluation criteria for those challenges was then

developed by the workshop participants. These

lists are presented in Tables 3 and 4.

Once the lists of technologies, challenges, and

corresponding evaluation criteria were

developed, each workshop participant was then

asked to choose what they felt were the 5 most

important technologies and the 5 most important

challenges. The participants were then asked to rank their chosen technologies and challenges in terms of their relative importance to one another.

The participants were also asked to repeat the same process for the lists of criteria corresponding to the technologies and

challenges; however, in this case the participants were asked to choose only three criteria from

each list.

3.2 Day Two

Based on the ranking of the technologies and

challenges (and their corresponding criteria from

day one) day two of the workshop began with

the participants scoring the top 5 technologies

and challenges (and the top 3 criteria for each)

using the Analytical Hierarchy Process (AHP),

which is described in section 4.0.

The scoring process was followed by a presentation by Dr. Jim Ricles of Lehigh

University (Bethlehem, PA) entitled "Next

Generation Steel Structures." Dr. Ricles

reviewed steel framing, structural requirements

for connections, and current connection

schemes. To establish the need for automated

steel construction research. Dr. Ricles provided

the following summary statements:

• Construction industry comprises

approximately 8 % of the U.S. Gross

National Product.

249
• U.S. construction productivity has shown an

average annual net decrease of nearly 1.7 %

since 1969.

• Procedures for erecting building structures have changed very little over the past 80

years (although rivets have been replaced

by bolting and welding). Erectors perform

strenuous tasks in a highly dangerous

environment.

• Incidents of occupational injury reported for

construction workers comprised over 10%

of all cases.

• Workers' Compensation Insurance for steel workers is 19.3% of wages, the highest of

all construction workers.

• Percentage of fatalities in the construction

industry (limited to building erection) from

falling is 43%.

Dr. Ricles then discussed required connection

characteristics for automated construction and

provided examples of connection ideas for

automated construction. Characteristic features

required of next-generation beam to column

included [10]:

• Self-alignment - The connection must be able

to guide the beam toward the proper location once contact is made between connection

elements located on the beam and column.

• Tolerances - The connection must have

tolerances which allow for misalignment or out-of-plumbness.

• Adjustment - Because of the tolerances that must be built in, it is unlikely that the

connection will be precisely in its correct position after erection. Therefore, the

connection must have the ability to be

adjusted easily. • Stiffness, Strength and Stability - The

connection must be strong enough to carry

erection loads while possessing a suitable

amount of stiffness to control deflections.

Furthermore, the connection must be stable enough to allow erection of the structure to continue until the final fastening.

• Modularity - The connection should be able

to be mass-produced with a standard shop

fitting operation and with quick, automatic

erection capabilities.

Following the presentation, the workshop

participants were once again divided into 4

groups. The purpose of the last breakout session

of the workshop was to brainstorm ideas for new

connection technologies for use in steel construction.

The ideas that resulted from the breakout

sessions were then discussed among all the

workshop participants. The primary feedback

from the group centered on three needs. These

included better production and fabrication

processes to reduce tolerance requirements in the connector, the application of automated

welding technologies - common in manufacturing - to steel erection, and machinery

to eliminate or reduce the human involvement in the bolt-up process.

4.0 ANALYTICAL HIERARCHY PROCESS

The Analytical Hierarchy Process (AHP) is a

multi-criteria (or multi-attribute) decisionmaking tool that was originally developed by

Thomas L. Saaty in the early 1970' s [11]. AHP

is particularly useful when trying to rank

alternatives based on the qualitative opinions of

a group of experts. Since ranking the

technologies and challenges that resulted from

the workshop could not be carried out

quantitatively without in-depth analyses, the

opinions of the assembled steel industry experts were used with the AHP to rank the technologies

and challenges.

The AHP is based on the pairwise comparison of

the given alternatives taking only one criterion

into consideration for each set of comparisons.

Therefore, given n alternatives, the possible

number of non-duplicative pairwise comparisons

of the alternatives is

;=1

250
If we are to rank these alternatives based on m

criteria, then the above pairwise comparisons

must be repeated m times (once for each

criteria). For example, if n = 10 and m =5, then

225 comparisons would be required to complete

the AHP! Hence, when using the AHP to rank

several alternatives one must be careful to limit the number of alternatives and number of criteria

in order to avoid an unwieldy number of

comparisons. It was for this reason that the

workshop participants were asked to choose only

the top 5 technologies and challenges and only

the top 3 criteria for each (resulting in a total of

60 comparisons).

The AHP also provides a means of checking the

consistency of the pairwise comparisons so as to get a measure of the reliability of the data.

5.0 RESULTS

The results presented herein are limited to the

results of the workshop's first two breakout

sessions and the AHP analysis of those results.

5.1 Breakout Session One

The first breakout session resulted in a list of 12

technologies that the 17 workshop participants

felt would be helpful in improving the

productivity of steel construction. This session

also resulted in a list of 10 criteria that the

participants would use to rank the technologies.

Tables 1 and 2 show the technologies and

criteria, respectively, ranked in order of

importance from top to bottom (based on the

conglomeration of the participants" individual

direct rankings).

5.2 Breakout Session Two

The second breakout session resulted in a list of

22 challenges that the 17 workshop participants

felt the US steel construction industry currently

faces. This session also resulted in a list of 9

criteria that the participants would use to rank

the challenges. Tables 3 and 4 show the

challenges and criteria, respectively, ranked in order of importance from top to bottom (based

on the conglomeration of the participants'

individual direct rankings).

5.3 AHP Results

In order to limit the number of pairwise

comparisons conducted during the application of

the AHP, only the top 5 technologies and

challenges and the top 3 criteria were

considered. For example, although in Table 2 the

safety criterion ranked 4'^ in importance, it was

not selected for the AHP analysis for the above

reason. Ideally the AHP analysis would be

conducted with all the technologies and

challenges and all of their corresponding

criteria.

Tables 5 and 6 show the results of the AHP

analysis for the technologies and challenges,

respectively. Table 7 shows the number of valid

responses from which Tables 5 and 6 were

generated. The valid responses were chosen

based on an acceptable consistency ratio calculated as part of the AHP analysis [2].

Comparing Tables 1 and 3 with Tables 5 and 6, respectively, shows that the AHP results agree

closely with the results of the workshop

participants' manual ranking of the technologies

and challenges. The AHP analysis also shows

that apart from the "Material tracking" and

"Material handling" technologies in Table 5 the

final weighted scores in Tables 5 and 6 are not

sufficiently different from one another to produce clear winners.

6.0 CONCLUSIONS AND FUTURE WORK

The workshop participants responded positively

to the potential introduction of new technologies

to the steel construction process and agreed that automation was needed in the industry. Many

attendees volunteered to support future site visits and pilot studies. Based on the workshop

response, the American Institute of Steel

Construction is forming a steering committee to guide future research and the NIST Construction

Metrology and Automation Group is making this research area a primary focus. A recommended

research roadmap for automating steel

251
construction will be presented in a forthcoming

publication. This publication will include

further analysis of the workshop results followed

up by site visits and interviews with industry

experts.

REFERENCES

1. Ricles, J., "Next Generation Steel

Structures," Presentation delivered at the

NIST/AISC Automated Steel Construction

Workshop, Gaithersburg, MD, 6-7 June,

2002.

2. Haas, C. T., "Automation in Steel Erection,"

Presentation delivered at the NIST/AISC

Automated Steel Construction Workshop,

Gaithersburg, MD, 6-7 June, 2002.

3. Fleischman, R., Viscomi, B.V., and Lu, L.- W., "Development, analysis and

experimentation of ATLSS connections for

automated construction," Proc, 1" World

Conf. On Steel Struct., Acapulco, Mexico,

1992.

4. Albus, J. S., Bostelman, R. V., Dagalakis, N.

G., "The NIST ROBOCRANE, A Robot

Crane", Journal of Robotic Systems, July

1992.

5. Yamazaki, Y. and Maeda, J., "Construction

process innovation through SMART

system," Proceedings of the 1st Congress on Computing in Civil Engineering, Jun 20-22

1994, Washington, DC, USA, p 1583-1590.

Table 1. List of Helpful/Desired Technologies.

Rankin

Technology

Most New connector technology

Desired 3D/4D CAD and data interchange

Automated welding

Material tracking technology (logistics) Piece movement technology (material handling)

Plumbness technology

Simpler method for installing and tensioning bolted connections Technology to locate components and objects

Technology to create as-built models

r New steel technology

Least Jack-up construction technology

Desired Deck-sheet sidelap fastening technologies

6. Wakisaka, T., Furuya, N., Inoue, Y., and

Shiokawa, T., "Automated construction

system for high-rise reinforced concrete

buildings,".. Automation in Construction,

v9, n3, 2000, p 229-250.

7. Sakamoto, S. and Mitsuoka, H.; "Totally

mechanized construction system for highrise buildings (T-UP system)," Proc, 11th

International Symposium on Automation and

Robotics in Construction, May 24-26 1994,

Brighton, UK.

8. Owen, F., Park, G., Haas, C, Gibson, G., and

Traver, A., "Performance Testing of a Large

Scale Manipulator to Determine Relative

Utility of Several Operator Interfaces,"

Proc, 14th International Symposium on

Automation and Robotics in Construction,

Pittsburgh, PA, June 1997

9. Dunn, R., "Steel Erection and Challenges"

Presentation delivered at the NIST/AISC

Automated Steel Construction Workshop,

Gaithersburg, MD, 6-7 June, 2002.

10. Ricles, J. and Schlafly, T., "Next Generation

Steel Structures," White paper delivered at the NIST/AISC Automated Steel

Construction Workshop, Gaithersburg, MD,

6-7 June, 2002.

U.Saaty, T. L., Multicriteria Decision Making:

The Analytical Hierarchy Process -

Planning, Priority Setting, Resource

Allocation, 2"'' Edition, RWS Publications,

Pittsburgh, PA, 1990

Table 2. List of Criteria for Ranking the

Technologies.

Ranking Technology Criteria Most

Important

Least Important

Cost savings

Quality

Speed/productivity

Safety

Minimization of rework

Ease of Use

Durability

Time until 100% ROI

Tolerance accommodation

Make task attractive to labor

252
Table 3. List of Challenges Faced by the US

Construction Industry.

Ranking

Most

Imponant

Reduce overall time to construct Reduce time from design to erection Need to optimize man-hours/ton

Connection technology

Efficient supply chain management from

shop to erected state

Facilitate information exchange

Maximize efficienc) of hoisting equipment

Minimize cost of moment connections Reducing number of pieces (design stage) Standardize perimeter framing

Inspection is labor intensive, time consuming, etc Minimize fall risk

Least Important

Challenges

Confirming foundation accuracy Optimize bolting process on current connections Shop drawing time reduction (project critical path)

Changing mind-sets of engineers, designers,

constructors, etc. Accurate installation of base detail Streamline the code acceptance process Expand ability to use prefab modules

Determining actual location of piece in lay- down area

Ability to coordinate multiple cranes Improve quality control (tighten tolerances) of steel members

Erection process susceptible to weather

restrictions

Table 4. List of Criteria for Ranking the

Challenges.

Ranking Challenges Criteria Most Overall cost benefits Important Safety

Productivity

Quality

Size of market

Non-proprietary

r Code acceptance possibilities Least Time to market acceptance

Important Durability/performance of end product

Criteria

(weights)

Technology.

Quality

(0.41)

Cost

Savings

(0.34)

Productivity

(0.25)

Final Weighted

Score

Connectors 0.20 0.27 0.27 0.24

3D/4D CAD and

data interchange

0.25 0.21 0.21 0.23

Automated

welding

0.26 0.17 0.22 0.22

Material

handling

0.15 0.18 0.15 0.16

Material tracking 0.14 0.17 0.15 0.15

Table 6. AHP Results for the Top 5 Challenges

and Top 3 Criteria.

Criteria

(weights)

Challenges

Overall Cost

Benefits

(0.41)

Productivity

(0.35)

Safety

(0.24)

Final Weighted

Score

Reduce time

from design to erection

0.30 0.19 0.15 0.22

Connection

technology

0,20 0.18 0.30 0.21

Reduce overall time to construct 0.17 0.24 0.20 0.20

Need to optimize

man-hours/ton

0.14 0.23 0.17 0.18

Efficient supply

chain

management

0.20 0.17 0.17 0.18

Table 7. Number of Valid Responses for Each

Pairwise Comparison.

Comparison of: Valid

Responses

Pairs of challenge ranking criteria 7 Challenge pairs vs. Overall cost 10

benefits Challenge pairs vs. Productivity 9

Challenge pairs vs. Safety 13

Pairs of technology ranking criteria 8 Technology pairs vs. Cost savings 14 Technology pairs vs. Quality 12 Technology pairs vs. Productivity 14

Table 5. AHP Results for the Top 5

Technologies and Top 3 Criteria.

253

Error Modeling for Automated Construction Equipment

by

Yong K. Cho*, Carl T. Haas**, S.V. Sreenivasan***, and Katherine Liapi

ABSTRACT: This paper introduces the statistical error modehng approach for a computercontrolled large-scale manipulator (LSM). The LSM is sufficiently representative of several types of

construction equipment to be able to serve as a general test bed. In the analysis, three factors which

are measurable in real time: distance, hydraulic pressure, and payload, were varied to determine their influence on position errors in the LSM. It was shown that with an integrated multi-variable regression model, about 30% of the mean positioning error of the LSM can be reduced without the mid of fixed external reference systems.

KEYWORDS: automation; kinematics; manipulator; position error; regression analysis

1. INTRODUCTION

Hydraulically actuated construction equipment is rapidly being retrofitted with robotic control

capabilities by several major manufacturers such

as dozers, graders, and excavators equipped with

various position sensors reflects a movement in the construction industry towards improving

productivity, efficiency, and safety [6].

The reduction of the cumulative position error caused by backlash, deflection, sensor error and

other factors, however, still remains as one of the

key issues in operating autonomous or semiautonomous construction equipment. Further,

large scale construction equipment, particularly

the ones actuated hydraulically, possess lower

end-point positioning accuracy than electrically

actuated robotic devices used in controlled

environments.

Understanding the causes and propagation of

errors in automated construction equipment is very important for precise operation in a field environment. Large manipulators such as

forklifts, excavators, and the LSM pose

particularly difficult equipment control problems.

Much of the manipulator error is due to accumulated feedback errors of the rotary and

prismatic joint sensors, and lost motion due to backlash. Working conditions such as variations

in hydraulic pressure supply and presence of large

payloads influence the error attributes as well. Kinematic and dynamic states are also an

influence.

Most errors arising from the operation of the

manipulator are considered random errors which

are unavoidable and are usually reduced through

stochastic experimentation [1]. Even if it is theoretically possible to derive a mechanistic

mode of all sources and their interdependence, it

is computationally untenable for real time

manipulator control, and sensor requirements for independent input variables are currently

unfeasible in a construction environment.

Position error of an economically sensor equipped manipulator can be reduced by

providing the correction factors resulting from a

statistical analysis of on-hand samples. The

results can be organized into statistical equations

with correction factors for real-time equipment

* Corresponding Author, Assistant Professor, Dept. of Industrial Studies, University of Wisconsin, Platteville, WI 53818. Tel.: +1-608-342-1604 ; fax: +1-608-342-1254. E-mail: chovo@uwplatt.edu

** Professor, Dept. of Civil Engineering. The University of Texas, Austin, Texas 78712 "*

Associate Professor, Dept. of Mechanical Engineering, The University of Texas, Austin, Texas 78712

****Assistant Professor, Dept. of Civil Engineering, The University of Texas, Austin. Texas 78712.

255
feedback control, much like those used for

artillery fire control.

2. OBJECTIVE AND METHODOLOGY

The main objective of the research presented here

is to improve automated manipulator positioning

capability based on regression modeling of

manipulator position errors and working

conditions.

The methodology pursued includes the following

basic steps:

1) Select a set of well distributed known

positions in a manipulator's working space,

2) Command a robotically controlled

manipulator's end-point to the selected

positions,

3) Measure actual positions of the resulting endpoint, and calculating position errors, 4) Repeat the above steps for varied working

conditions as defined by the following causal

factors: distance, hydraulic pressure, and

payload,

5) Analyze the results with the regression

modeling method, and

6) Develop an algorithm based on the regression

modeling and apply the algorithm to adjust

the commanded positions to reduce errors.

3. KINEMATICS

Inverse and forward kinematics equations,

computer algorithms, feedback encoders, control

interfaces were implemented from the previous

research efforts for the various control strategies

for the LSM [4]. An illustration of the large scale

manipulator is shown in Fig. 1. As seen in the

figure, the LSM has swing, lift, telescope, rotate,

roll, and pivot joints in total 6 degrees of freedom

(DOF).

The LSM control system calculates a series of

joint angles through which to move the joints in order for the end-effector frame to move from its initial location to its final location. Then, the link

transformations can be multiplied together to find

the single transformation that relates a frame to another frame. As with vectors and rotation

matrices, a symbol T is called a transformation

operator [3]. Here, pl^'^^T describes Pivot frame

relative to Base frame and forms the following

transform equation:

Baser Base 'J-' Swing rj^ ^'ft'T' Telc-p Rotaic-p Rollr-p Pivot ^ ~Swing ^ Lift^ Tc'le^ Rolaw^ Roir Pivor

Each joint angle can be computed from the

transform equation.

4. ACCURACY TESTS

Accuracy may be defined as the magnitude of the

difference between the desired value and actual

value of a measurement. In this study, accuracy is measured relative to the manipulator's base

coordinate system (see Fig. 2).

4.1 Sample Regression Analysis

There are many existing random error sources

affecting the final position of the manipulator's

end-effector. Thus, in this study, to predict and to adjust for the position errors from the uncertain

random error sources, the sample regression

modeling method was selected to determine

whether or not a relationship exists between error variables and to predict the nature of the

relationship of correlated random variables.

To ensure a consistent test process, six different

kinematic states of the LSM were chosen as known target positions (Table 1). They were

chosen to represent the full range of configuration

that was anticipated to affect the various random

error sources under the different conditions of the

chosen three independent variables: distance,

hydraulic pressure, and payload.

4. LI Accuracy with respect to Distance

Errors with respect to the distance variable were

analyzed under several different conditions: five

different payloads and five different hydraulic

pressures in the six fixed positions.

In this study, the distance is defined as the Cartesian positional difference between a base

point (0,0,0) of the LSM's test bed and the

kinematically calculated position (x, y, z) of the

end-effector.

256
The accuracy test result for individual axial

accuracies with signed values were tested by

distances ranging from 0 to 4.5 m. The desired

position was calculated from the kinematics

equations, and the actual position was manually

measured. Then, the actual positions of the endeffector were compared to the kinematically

calculated positions. Then the directional (axial) error attributes with respect to the distance

variable were analyzed with collected sample data

(see Table 2). Here, n indicates the sample size (5 pressures x 6 positions + 5 payloads x 6 positions = 60 samples).

While distance increased, as results, the

directional errors in the Z axis increased, which

relates to or is explained by the fact that angular

joint error increases with respect to distance.

Correlation analysis might be useful to determine

the deflection in z coordinates according to the

directional distance in X and Y axes + y) ) which describes how far the arm is cantilevered out.

4.1.2 Accuracy with respect to Hydraulic

Pressure

The current LSM"s hydraulic system

configuration is a single power source that feeds a

parallel network of actuators, with a single branch

for each joint. The computer control signal

determines the strength of the current to the valve

solenoids and thus the opening of the control

valve. This determines the floW' rate of fluid into

the actuator. According to the LSM payload and

location in workspace, the control signal strength

changes and thus the flow rate. To keep the joint

moving at a steady speed under an increasing

load, the valve opening increases as the load

increases. This can be done by the pressure compensation valve. So even with an increasing

load, the LSM's pressure compensation valve

keeps the actuator velocity steady [5].

Even with the advanced hydraulic flow control

.system, the LSM still exhibits more stiction. slop,

and backlash in the joints and hydraulic actuators than conventional industrial robots which are

small, fast, electrically actuated. Besides, the LSM

can be manufactured to lower tolerances than can

be the industrial robots. Thus, as another variable,

hydraulic oil pressure was selected to be examined

in order to find the error attributes of the LSM.

Due to maintenance concerns, hydraulic pressure was Umited to a maximum of 10345 kPa (1500

psi).

LSM Table 3 shows the directional error attributes with respect to the hydraulic pressure. All the

linear regression equations indicate the error decreases toward zero while the hydraulic

pressure increases.

Similar to the previous accuracy test toward

distance, hydraulic pressure showed some

relationship with the directional error in the Z

axis. The directional error in the Z axis decreased

while hydraulic pressure increased. The increased

hydraulic strength increases the joint speed, which

might ultimately reduce the error caused from

stiction and load. In a sense, the system is stiffer as well.

4.1.3 Accuracy with respect to Payload

As another variable, payload was examined in order to find the error attributes of the LSM.

Payload affects the inertia and speed of the

manipulator, which can yield an overshoot error and more deflection. Four different pipes were

used for this test. The weight of the pipes ranged

from 40 kg to 386 kg.

To ensure a consistent test process, the experiment was performed under 8276 kPa (1200 psi) of

hydraulic pressure. Each pipe was lifted into the

chosen kinematic states of the LSM. Fig. 3 shows

one of the chosen kinematic states.

The directional (axial) error attributes with respect

to the payload variable were analyzed and

summarized in Table 4.

The coefficient of determination for the X axis

(0.507) and the Z axis (0.531) indicate that the

payload significantly affects the accuracy of the X

axis and the Z axis. It is clear that payload

accentuates the deflection which explains the

increased error in Z coordinates. In addition,

payload makes the LSM move sluggish which

257
might cause in more errors toward the X axis

which has a 4.5 m range than toward the Y axis

which has 2.2 m range. Payload makes the lifting

and telescoping motions more sluggish, which

might ultimately cause some systematic

relationship with errors in x and z coordinates.

Also, X and z coordinates relate to degree of

cantilever and therefore deflection.

Although there was almost no relationship

between payload and the directional error in the Y

axis, the systematically increased conditional

variance of accuracy in the Y axis might be

caused from erratically applied error sources such

as stiction and overshoot to the swing joint.

4.2 Error Adjustment with Multi-variable

Regression Models

The multi-variable regression analysis of the

LSM"s position with respect to distance, hydraulic

oil pressure, and payload was modeled to adjust

the error of each axis of the end-effector as follows:

AX=-1.229-h0.182Dist_.._ + 0.0000528Pr,

0.00264 Payload, (r'=0.262)

AY=0.627-0.1D,„ - 0.0000 18P,essure +

0.0000988Pay,oad, (r=0.028)

AZ= -0.884 - 0.141 D,„ + 0.0001075 Pressure

" 0.00397 P«yw,(r=0.483)

Here, AX, AY, and AZ indicate the regression of

the multi-variable model on the LSM's axial

position error

By applying the three multi-variable equations to the same data set obtained from the LSM's

position accuracy test, given the three conditional

variables, there were some error reductions

(30.7%) in the overall accuracy shown in Table 5. In a theory, the substantial number of the unsolved

errors (69.3%) may be statistically solved by

adding more conditional variables.

While the average errors of the X axis and the Z

axis were reduced by 18.88% and 50.55%

respectively, the average error of the Y axis

somewhat increased by using the multi-variable

equations. This means that the multi-variable

equation (AY) does not explain the Y axis errors very well. Also, it can be inferred from the

equation in which r' is 0.028, that the multiple

variables have little effect on the Y axis accuracy. Therefore, while adjusting the X and Z axis values

based on Equation AX and Equation AZ, the

kinematically calculated original Y axis value was

not adjusted.

4.3 Final Performance Test

The obtained three equations were then applied to the original forward kinematics equations to adjust for the original x-y-z coordinates. Then,

the inverse kinematics provides adjusted six joints

angles based on the adjusted position data. To

verify the error attributes found from the error modeling tests, several material placement tests were conducted on the LSM's test bed. This

paper introduces one of the tests here. A stylus was attached to the test load (386 kg) in the LSM's jaws pointing toward a target (see

Fig.4). By using a developed laser rangefinder

system and string encoders [2], a Cartesian

coordinates of a center of cross hairs on a target

plane was measured (325.63cm, 10.77cm,

77.09cm). The purpose of this test was to compare

the LSM's accuracy when its error was adjusted

and unadjusted under a certain working condition

(with 3.348m distance, a 386 kg test load, and a 8276 kPa ( 1200 psi) hydrauhc pressure supply). A

test result shows that the LSM has better accuracy

when a commanded position was modified based on the developed error modeling as follows:

a) Error without adjustment: 4.29 cm

b) Error with adjustment: 1.97 cm

Here, the errors were measured by the distance

between the center of the cross hairs and the end

of the stylus.

5. CONCLUSION

The error attributes of a hydraulically actuated

large scale manipulator were analyzed by using

regression analysis. In the regression analysis,

three variables, distance, hydraulic pressure, and

payload, were individually varied to find the

position error attributes of the LSM. Distance had

258
a somewhat significant effect on the directional

error in the Z axis (as distance increased, random

errors in the Z axis increased). Hydraulic pressure

and payload had significant effect on the overall

error (as hydraulic pressure decreased and payload

increased, random error increased). Although, the

testing was performed in a small working volume

due to the limited mobility of the LSM on its fixed

frame, this study reduced about 30% of the

average positioning errors of the LSM with an

integrated multi-variable regression model. Thus,

it is sufficient to indicate whether a descriptive

model or a regression model is feasible. The

substantial number of the unsolved errors (about

70%) may be statistically solved by adding more

conditional variables which possibly affect the

manipulator's position errors.

6. REFERENCES

[1] Barry, B.A. (1978j. Errors in Practical

Measurement in Science, Engineering, and

Technology. John Wiley & Sons, Inc., New York.

[2] Cho, Y., Haas, C, Sreenivasan, S., and Liapi,

K. (2002). "A framework for rapid local area modeling for construction automation." Journal of

Automation in Construction, 1 1(6), pp. 629-641.

[3] Craig, J. (1986). Introduction to Robotics:

Mechanics & Control. Addison-Wesley.

[4] LeBlond, D., Owen, F., Gibson, G., Haas, C,

and Traver, A.(1998). "Performance Testing and

Characterization of Advanced Construction

Equipment." ASCE Journal of Construction

Engineering and Management. 124(4), pp. 289-

296.

[5] Owen, F.C. (1998). "Development of Smooth

Resolved Motion and Computer- Assisted

Teleoperation for a Large Scale Manipulator.

Ph.D. Dissertation, Dept. of Mechanical

Engineering, The University of Texas at Austin.

[6] Singh, S. (1997). "The State of the Art in Automation of Earthmoving." ASCE Journal of

Aerospace Engineering, Vol 10 (4), October.

259
Table 1 . Chosen Kinematic States

Kinematic States

Calculated Global Position ofEndeffector (cm)

Swing

I& n

Lift C)

Telescope

(cm)

Rotate C)

X Y Z

(1) -20 11 0 20 157.9992 -54.0685 73.5178

(2) 5 50 30.48 0 364.4036 31.8821 186.7875

(3) -10 36 60.96 0 321.0855 -56.6166 95.7560

(4) -2 31 16.76 -10 276.6731 -11.3020 112.2213

(5) 10 21 0 0 216.2586 38.1335 95.5121

(6) 0 54 48.77 0 393.9296 0 197.3946

(The values of Roll and Pivot joints are 0°)

Table 2. Directional (Axial) Error Attributes with respect to Distance

Axis Regression Model n r X Ax= -0.962+0.180 D,„ 60 0.059

Y Ay=0.493-0.1 A« 60 0.026

z Az=0.0318-0.2411 A„ 60 0.122

Table 3. Directional (Axial) Error Attributes with respect to the Hydraulic Pressure Axis

X Ax=-0.58+0.00001412P.,

Y

Regression Model

Ay=0.549-0.000043 P„

Z Az=- 1. 29+0.00008942 R

30

30

30

0.003

0.033

0.178

Table 4. Directional (Axial) Error Attributes with respect to the Payloac

Axis Regression Model n X Ax=0. 151 -0.00397 P^to^ 30 0.507

Y Ay=0. 1 24+0.000243 IP.wo.rf 30 0.003

z Az=-0.267-0.00459 Payioad 30 0.531

Table 5. Axial Error Adjustment for Test Data Set

Average

Accuracy

X Y Z

Total Accuracy

Before

Adjusted

(cm)

0.5731 0.3859 0.7309 1.1717

After

Adjusted

(cm)

0.4649 0.4009 0.3614 0.8115

%

Reduced

18.88 -3.66 50.55 30.74

260
Fig. 1 . 6 DOF Kinematic Configuration for the LSM

Fig.2. Illustration of the Accuracy Method relative to the Base Coordinate System

Fig. 3. One of the chosen Kinematic States

261
4. 1 he Accuracy i esl was conducted with a Stylus and a Test Load

262
11

Development of a Robotic Structural Steel Placement System

by

Alan M. Lytle", Kamel S. Saidi", and William C. Stone^

ABSTRACT: The NIST Construction Metrology and Automation Group, in cooperation with

the NIST Intelligent Systems Division, is researching robotic structural steel placement as part of

a project to develop an Automated Steel Construction Testbed. This project was initiated in response to industry requests for advanced tools and methodologies to speed the erection of steel structures while maintaining or enhancing standards for worker safety and facility reliability.

This initial effort integrates and extends prior NIST research in robotic crane employment, tele- operated steel beam placement, laser-based site metrology, construction component tracking, and

web-enabled 3-D visualization.

KEYWORDS: construction automation, path planning, robotics, VRML, 3-D coordinate

measurement systems

1.0 INTRODUCTION

The American Institute of Steel Construction has

expressed a need for a 25 % reduction in time to

j erect steel structures. In response to this request,

{' the NIST Construction Metrology and

'! Automation Group (CMAG) is developing a

robotic structural steel placement system for the

testing and validation of advanced tools,

methodologies, and standards for automated steel construction. This effort, the first phase of

CMAG's Automated Steel Construction Testbed

[j (ASCT) project, extends prior NIST research in construction component tracking [1] and real-time

construction metrology [2]. The work also

extends prior efforts in tele-operated steel beam

I placement [3] to include autonomous control of a

six degree-of-freedom (DOF) robotic crane.

(' The base platform is the NIST RoboCrane, which

I is an inverted Stewart platform parallel link

manipulator [4]. RoboCrane' s Real-Time Control

System (RCS) is augmented with absolute

cartesian position feedback from a laser-based site measurement system (SMS) for trajectory

planning and dynamic control. Robot and

construction component position data is displayed

in a virtual world model of the steel placement

operation for supervisory review and control.

The steel structure to be assembled consists of a beam and two columns connected with the

ATLSS"* quick connector. The ATLSS, developed

at Lehigh University [5], was chosen because it requires no bolting or welding.

This paper will discuss the concept, current development and future implementation of the

robotic structural steel placement system.

2.0 OPERATIONAL CONCEPT

Four laser transmitters are positioned on the site perimeter to illuminate the work volume of

RoboCrane with reference beams (Figure 1). A

field worker using the SMS digitizing wand then

' Official contribution of the National Institute of Standards and Technology (NIST); not subject to copyright in the United States.

; ' NIST, BFRL, Construction Metrology and Automation Group, Mail Stop 86U, Gaithersburg, MD 20899-8611;

} alan.lytle@nist.gov, kamel.saidi@nist.gov, william.stone@nist.gov.

i ' Certain commercial equipment, instruments, or materials are identified in this report in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by

the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment

I identified are necessarily the best available for the purpose.

263
creates a digital model of the construction plane

including any obstacles.

This world model is then updated with the

positions of the as-built structure and the target

beam by the field worker through a process of

automatic part identification (barcode), part model

database access, and part fiducial point

measurement (Figure 2). The current pose of

RoboCrane is measured from onboard SMS

sensors, and the path planner calculates the

required transformations for beam pickup and

delivery. RoboCrane then executes the

movements (Figure 3). The world model,

including dynamic tracking of RoboCrane, is displayed to an operator through a visualization

system based on the Virtual Reality Modeling

Language (VRML).

3.0 SYSTEM OVERVIEW

The current configuration of the Automated Steel

Construction Testbed has five primary

components. These include:

• RoboCrane

• Site Measurement System

• Component Tracking System

• High-level ASCT Controller

• Visualization System

2.1 RoboCrane

RoboCrane is an innovative, cable-driven,

manipulator invented by the NIST Intelligent

Systems Division (ISD) and further developed and

adapted for specialized applications over a period

of several years [6,7,8]. The basic RoboCrane is an inverted Stewart platform parallel-link

manipulator with cables and winches serving as the links and actuators, respectively. The

moveable platform, or "lower triangle," is kinematically constrained by maintaining tension

in all six cables that terminate in pairs at the

vertices of an "upper triangle" formed by the

cable support points. This arrangement provides

improved load stability over traditional lift systems and enables 6 DOF payload control.

The version of RoboCrane used in this project is the Tetrahedral Robotic Apparatus (TETRA). In the TETRA configuration, all winches, amplifiers,

and motor controllers are located on the moveable

platform. The upper triangle only provides the

three tie points for the TETRA cables, allowing

the device to be retrofitted to existing overhead

lift mechanisms.

2.2 Site Measurement System

The SMS uses commercially available positioning

technology (3D-I) produced by Arc Second, Inc. in the Constellation and Vulcan product families''. (3D-I, Constellation and Vulcan are registered

trademarks of Arc Second, Inc.) These systems

use stationary, active-beacon laser transmitters

and mobile receivers to provide millimeter-level

position data.

2.2.1 SMS Description

Both Constellation and Vulcan systems use eyesafe laser transmitters to triangulate the position

of a tuned optical detector. Each transmitter emits

two rotating, fanned laser beams and a timing

pulse. Elevation is calculated from the time

difference between fan strikes. Azimuth is referenced from the timing pulse. The field of

view of each transmitter is approximately 290° in

azimuth and +/- 30° in elevation/declination. The

recommended minimum and maximum operating

ranges from each transmitter are 5 m and 50 m,

respectively.

Line-of-sight to at least two transmitters must be

maintained to calculate position. The

Constellation receivers each track up to four

transmitters and wirelessly transmit timing

information to a base computer for position

calculation. The Vulcan system is a self- contained digitizing tool with two optical

receivers on a rigid pole. A vector projection

along the line formed by the two optical detectors

allows 3-D measurement of the tool tip. Vulcan

can track only two transmitters at one time;

however, the transmitter selection can be

manually switched between any of the four

available. Recovery of positional data following

264
momentary signal blockage takes approximately one second.

2.2.2 Prior 3D-// Mobile Robot Integration

Early efforts to use 3D-I laser technology for

mobile robot navigation showed that although the

system was capable of guiding a mobile robot [9],

its use was restricted due to loss of track at relatively low vehicle speeds [10]. Upgrades to the positioning technology continued and a

successful combination of indoor 2-D map

creation and autonomous navigation was

demonstrated in a research project at the

Rochester Institute of Technology [11].

Subsequently, a single receiver Constellation

system was installed on an autonomous lawn

mower at the Carnegie Mellon University Field

Robotics Center and provided positional reference

in a large outdoor setting [12].

2.2.3 The SMS on RoboCrane

Three SMS receivers are mounted on RoboCrane

at the vertices of the lower triangle (see Figure 4).

The receiver locations are registered to the

manipulator during the initial setup process in the

local SMS coordinate frame. For convenience, all measurements are calculated in the local SMS

coordinate frame, though if required, mapping to an existing world coordinate frame could be

accomplished. Receiver timing signals and

diagnostic data are wirelessly transmitted to a base station computer running Arc Second's

proprietary position calculation software.

Position and SMS diagnostic information are polled at approximately 7 Hz using a NISTdeveloped data communications application.

Position data from the three receivers is used to calculate RoboCrane' s pose (position and

orientation). Diagnostic data such as number of

visible transmitters, excess signal noise or multipath reflections is also provided for each

position calculation and is used to assess the

quality of individual position fixes.

2.3 Component Tracking System

The NIST Construction Metrology and

Automation Group has conducted research in

construction component tracking for several

years. NIST developed the "Comp-TRAK"

system, which combines field-wearable

computing, automatic identification (barcode and

RFID), laser metrology, wireless database access, and VRML-based 3-D model visualization to enable tracking of discreet components on a

construction site. The feasibility of such a system was shown during a study tracking delivery and

final placement of structural steel members on a NIST construction project [13]. During this study, the Comp-TRAK system was successfully

used to identify components, remotely access component library data, guide the field user in measuring current part location, and remotely

update a project management database with part

data including location within the site coordinate

frame.

Elements of Comp-TRAK will be used in the

robotic structural steel placement system to locate

randomly-placed target components and update

the world model through the following sequence:

(a) The field user identifies the component.

(b) The component library is accessed and a model is displayed with specified

measurement points (fiducial points).

(c) The field user measures observable fiducial

points with the SMS digitizing wand.

(d) The component position and orientation is calculated and transferred to the world

model.

2.4 High-level ASCT Controller

A high-level ASCT controller will provide the

following task and data management functions for

the overall system:

• Goal state management

• World model maintenance

• Navigation

• RoboCrane controller interface

The master goal of "pick and place steel beam" is divided into various sub-goals by the ASCT

controller. These sub-goals define various states RoboCrane must achieve to execute the overall

task. Examples include (1) maneuver to proper

265
gripper orientation, (2) lower gripper onto beam,

(3) grasp beam, (4) maneuver to pre-dock

position, and (5) dock beam.

The existence and locations of components of

interest are maintained in the ASCT world model.

Data to update the world model are provided

either by the component tracking system or by

tracking RoboCrane's pose when the crane is carrying an object.

RoboCrane's pose within this world model will be

estimated through Kalman filtering of both the

SMS position fixes and the RCS position

estimates derived from winch encoder feedback.

Based on world model component locations,

RoboCrane's pose, and volume operating limits, a

series of waypoints will be calculated for each

goal state. The required platform transformations

for the state changes and corresponding cartesian

velocity commands (Translation: x, y, z; Rotation:

roll, pitch, yaw) are calculated and sent to the

RoboCrane controller via a communications

interface. The RoboCrane controller, a version of

the NIST Real-time Control System implemented

by ATR (Advanced Technology & Research

Corporation)\ then converts the cartesian velocity

commands to winch controller input to execute

the desired movement. Closed-loop position

feedback from the SMS position fix enables

periodic modification of the path by the ASCT

controller until the desired goal state is reached.

2.5 Visualization System

A VRML-based 3-D visualization system will

also be used to provide remote visual feedback to an operator or supervisor. Elements of the world

model - the construction plane, RoboCrane, and

the target components - will be modeled in VRML 97 [14] and displayed within a browser

environment giving an observer 3-D "fly-through"

review capability. A socket connection between

the ASCT controller and the VRML environment

will provide pose updates for RoboCrane,

components being moved, and other elements of

interest. The VRML object models within the

visualization system will then be repositioned by a Java applet using the External Authoring Interface

browser extension. This provides a nonproprietary, open standard, low-bandwidth

method of displaying a 3-D representation of

robot operations within the work site.

3.0 CONCLUSIONS

This project will demonstrate autonomous steel structure assembly (pick and place) using a

robotic crane and a laser-based SMS. A digital

model of the work site is created with the SMS

and then the same measurement system is used for

closed loop feedback to precisely control the pose

of the steel components during assembly.

4.0 FUTURE WORK

Although this work will demonstrate the ability to perform autonomous steel beam pick and place, it will do so in a fairly structured environment that remains static after initial measurement. The

measurement process itself, although simple, still requires a human operator within the site to provide the initial digital model. There are currently no sensors, external or on-board

RoboCrane, which would enable any reaction to dynamic changes within the work site without

human intervention.

CMAG is currently researching automatic scene meshing and object recognition using highresolution LADAR (laser detection and ranging)

systems. In future work, LADAR and/or standard

optical imaging systems will be used to develop

and maintain the world model as well as provide

obstacle avoidance and docking support. The use

of the SMS technology to provide autonomous

control of cable suspended robots will also be

studied for other applications such as aircraft maintenance and shipbuilding. As additional

sensing systems are employed, the SMS

technology will also be used to study the

performance metrics of other tracking

technologies. The ASCT treats sensor input in a modular fashion; thus, future versions could use

other positioning technologies such as phase

differential GPS in certain applications to replace

the present laser-based SMS.

266
5.0 REFERENCES

1. Furlani, K. M. and Pfeffer, L. E., "Automated

Tracking of Structural Steel Members at the

Construction Site." Proc, 17"' International

Symposium of Automation and Robotics in Construction, Taipei, Taiwan, Sept. 18-20,

2000.

2. Stone, W. C, Pfeffer, L. E. and Furlani, K. M.,

"Automated Part Tracking on the

Construction Job Site." Proc, 4"' ASCE

Specialty Conference and Exposition/

Demonstration on Robotics for Challenging

Situations and Environments, pp. 96-103,

Albuquerque, New Mexico, Feb. 27 - Mar. 2,

2000.

3. Stone, W. C, Reed, K. A., Chang P. C,

Pfeffer, L. E. and Jacoff, A. S., "NIST

Research Toward Construction Site

Integration and Automation." Journal of

Aerospace Engineering, Apr. 1999, pp. 50-57.

4. Stewart, D., "A Platform with Six Degrees of

Freedom," Proc. of the Inst, of Mechanical

Engineering, Volume 180(15), Part 1:371-386,

1965-1966.

5. Fleischman, R., Viscomi, B.V., and Lu, L.- W., "Development, analysis and

experimentation of ATLSS connections for automated construction." Proc, V World

Conf On Steel Struct., Acapulco, Mexico,

1992.

6. Albus, J. S., Bostelman, R. V., Dagalakis, N.

G., "The NIST ROBOCRANE, A Robot

Crane", Journal of Robotic Systems, July

1992.

7. Bostelman, R., Albus, J., Dagalakis, N.,

Jacoff, A., "RoboCrane Project: An Advanced

Concept for Large Scale Manufacturing,"

Proc, Association for Unmanned Vehicles

Systems International, Orlando, FL, July

1996.

8. Bostelman, R. , Albus, J., Stone, W., "Toward

Next-Generation Construction Machines."

Proc. OfAmerican Nuclear Society 9th

International Topical Meeting on Robotics

and Remote Systems, Seattle, WA, March 4-8,

2001.

9. Beliveau, Y. J., Fithian, J. E., and Deisenroth,

M. P., "Autonomous Vehicle Navigation with

Real-Time 3-D Laser Based Positioning for

Construction." Automation in Construction,

(5) 1996.

10. Lytle, A. M., "Development of a Remotely

Piloted Vehicle (RPV) with Real-Time

Position Measurement (RtPM) for Hazardous

Waste Site Characterization." Master's

Thesis, Virginia Tech, Blacksburg, VA, 1994.

1 1 . Rochester Institute of Technology, Society of

Manufacturing Engineers (Student Chapter

18), Robot Construction Project, 2001.

www.rit. edu/~smewww/proj ect/rc/rc .html

12. Batavia P. H., Roth S. A., Singh S., "Autonomous Coverage Operations In SemiStructured Outdoor Environments." Proc,

IROS, Lausanne, Oct. 2002.

13. Furlani, K. M., Latimer, D. T., Gilsinn, D. and

Lytle, A. M., "Prototype Implementation of an Automated Structural Steel Tracking System."

Proc, 19"' International Symposium on Automation and Robotics in Construction,

Gaithersburg, MD, Sept. 23-25, 2002.

14. ISO/IEC 1477-1, "The Virtual Reality

Modeling Language (VRML)." 1997,

www.web3d.org

Figure 1 : Graphic denoting the illumination of

the work site with the SMS.

267
Figure 4: Photograph of RoboCrane with the SMS.

268
ROBOTS FOR SPACING OF WOOD

Thomas Bock*, Dimitry Parshin**, Tatjana Souetina, Aleksei Boulgakov***

^Technical University Munich, bulgakow@bri.arch.tu-muenchen.de ** Rostov State Building University, RUSSIA, pragma plus@maU.ru *** Moscow Building University, t_a_souetina@mail.ru

Abstract: Construction is of great interest for using of woodprocessing robotics. The structure, kinematic and dynamic models of robots for material location and spacing as well as woodprocessing have been considered in the paper. Taking into account specific features and

dynamic characteristics of robot, the recommendations on movements planning and forming

laws of control have been given. In conclusion recommendations for obtaining truthful measuring data and on the composition of robot software have been provided.

Keywords: Motion control; robot kinematics; wood processing.

1. INTRODUCTION

When producing elements of prefabricated wooden

houses a great deal of work on location tmd spacing

of wood and shaping of holes, recesses, decorative

patterns is done. The projects individual

pecuUarities require the apphcation of technological

equipment with quick readjustment and opportunity

to prepare control programs on the model during a

short period of time. While solving this problem

much attention is paid to the robotization of the mentioned above operations and creating robotic systems. The successful solution of robotization

tasks is first connected with the development of

original kinematic structures and competent

structural analysis. One more significant problem of

robotization of wood processing operations is setting the trajectory for cutting tool movement and

provision of its purposeful movement along these

trajectories with definite orientation.

2. ROBOT STRUCTURE, KINEMATICS AND

DYNAMIC MODELS

The analysis of jobs connected with location and

spacing of wood as well as shaping of holes and

decorative patterns has shown that in the basis of

the robotic system there should be a rectangular 3- coordinate gantry robot (fig.l). This cell provides

the working tool movement in the plane of a working table as well as lifting, lowering and

pressing of the tool. The second cell is an orienting

working head providing changes in the tool position

relative to the working plane or its rotation around

the axis Z. The main kinematics relations defining

the nature of the wood processing robot motions are presented by the system of the form

x{t) = (t) + 1 sin(^4 (0)sin(^5 (0)

;

y{t) = q, (t) + 1 cos(^4 (r))sin(^5 (t)) ;

z(t) = q^(t) + lcos(q^(t)),

where q^ (t) are generalized robot's coordinates, /

is the length of the end link. The laws of changing the tool phase coordinates

y(t), z(t) and its orientations dit), yit)

are determined by shape and view of the pattern

being fulfilled. The angle 0 specifies the tool pitch

relative to the plane XY , and the angle y - the

direction of the inclination being read from the axis X. The values of these parameters and the laws of

their change in time are formed at the stage of

planning robot motions. The kinematics of

orienting degrees of freedom has been chosen so

that the tool pitch angles 0 and the pitch directions y

are given separately by the degrees of freedom qs and ^4: d(t) = q^ (f), y{t) = q^ (t) . In this case

the laws of the generalized coordinates changes of

the transportable degrees of freedom are described

by the following:

q, (t) = x(t)-l sin(6'(r)) cos(7(0)

;

q. (0 = y(t) - 1 sm{d{t))sm{Y{t)) ;

q^{t) = z{t)-lcos{d{t)).

To simplify the controlling functions and increase

the accuracy of tool positioning a special-purpose

269
orienting head has been developed, its rotation axis of the last degree of freedom has been brought onto

the plane of tool cutting. While rotating it allows to retain the center of the tool coordinate system on

the rotation axis ^4 and obtain the main kinematics

ratios of a simple kind:

[x{t),y{T), z(tmtir(t)] =

[q^ (t), (t), (/), q^ (t), q^ (t)]

Dynamic models have been used to control robot

and develop control programs. For translation degrees of freedom in the basis of dynamic models

the equation for the forces balance is used

Im.

where m. weights of movable parts; - control

force of degrees of freedom; Fj - disturbing effects

incorporating frictional forces in movable parts of

the mechanism and load forces on the working tool. Control force F^ is connected with a moment M.

Of the drive by the ratio F^ = M i^. G I r

,

where is the drive gear ratio; G is the gear box

efficiency; r is an effective radius of the mechanism

transforming rotational motions into translatory ones. The drive dynamics for each degree of

freedom in models is presented in a linearized form

by the system of equations

a{s) u(s).

where a is the angle of the motor shaft turn; u is the motor control voltage.

Degree of freedom along the coordinate Z has

double function. One of them is connected with tool

lifting and lowering and second - with creating necessary pressing force on the working surface. When resolved force control is applied to drive Z

coordinate the relationships connecting the moment

and control voltage have been incorporated in the model:

k s(Js+ f)

5(r„,5 + i)

where J ,T^^,k^^ are inertia, time constant and

gain factor of the drive.

3. MOVEMENT PLANNING AND CONTROL

The specific feature of controlling robots for location and spacing of wood is the necessity of

forming programmed trajectories of cutting tool movement. On their basis the prediction of

displacements according to the coordinates is made

and control voltages for each of them are detemined. In the foundation of the programmed

robot control is the principle of setting movement

trajectories for a cutting tool and movement

program with help of the pattern being performed

with CorelDraw vector graphic editor. While

composing patterns their accurate scaling in a

special file is provided, this file is then used as an

assigning file while carrying out control. On the

pattern for material location and spacing or for performing decorative cutting the coordinates of the

initial point, and the starting point of the process

trajectory are assigned, transition Hnes between

closed figures of the pattern are assigned as well. While processing each figure pattern scanning with

digitization step T and read-out of information

about the coordinates of the next positioning

x[kT + Y\,y[kT + 1} are fulfilled. After the coordinates having been obtained control voltages

are determined u^[kT-\-\\ and U^{kT + 1'\

, and

motion speeds along the coordinates x and y during

the next control step are calculated as well. In order

to reduce the effect of quantization as a control means in the interval <t< we choose:

w[rj = 0.5[i/(r„) + w(f„^,)].

270
f

This ensures minimization of maximal deviation

ll[t^ ] from the truth-value when monotonous

change u{t) takes place. When applying graphical means for setting movement trajectories there appears necessity to build algorithms ensuring the proper tool orientation in each point of the

trajectory. To solve this problem different kinds of

interpolation have been analysed and in the algorithms of robot control a paraboUc interpolation

in the interval [{n — l)T, {n + l)T] is selected as a basic one. In this case for the time moment

t = (n + l)T a predictive calculation of

coordinates for the point of tool position is made

and according to the coordinates of three points

coefficients of an interpolating equation are defined:

x-[{n-\)T] x[{n-l)T] iV

x'[fiT] x[nT] 1

x-[(n + l)T] x[(n + l)T] 1

y[{n-\)T]

y[nT] .

Il [y[in + l)T]_

Next the obtained values of coefficients Qj are checked:

\ y[(n + \)T] = flo + a^x[(n + \)T] + a,y[(n + l)T]

and in case of identify the angle of normal to the

trajectory in the point t[{n + \)T] is calculated

j e[(n + l)T] = O.Stt - aictg(2a^x[(n + 1)7] + a^

I After determining the vector of tool position and

orienting and the vector of generalized coordinates

q[{n + l)T] for the next step of control the values

of tool motion speeds x, y and the angular speed

of rotation 9 are calculated. The accuracy of

I development of the movement trajectory depends !on the accuracy of fulfilling the task mentioned

above. The simplest algorithm is the linear dependence

\ v^iin + \)T] = (x[(n + l)T] - x[nT])/T

i Vy[(n + l)T] = (y[(n + l)T] - y[nT])/T

coe {(n + \)T] = ln{e\_(n + 1)7] - e\nr\)l 360 • T

. To perform high-quality patterns we have

I incorporated highly precision control algorithm.

«0

For this purpose the trajectory of tool movement is interpolated by a polynomial of the 3-d degree and

according to the interpolating function 5,, (7) the

derivative S\{n-\-\)T\ is determined. The

obtained derivative values are applied for calculating generalized speeds:

vj(n+i)r] = 4,[(n + i)r] =

V„cos(arctg(5„[(n + l)r])),

v,[(«+i)r] = ^,[(n + i)r] =

y„sin(arctg(5J(/7 + l)r])),

6;,[(« + i)r] = ^j(« + i)r] =

(5„[(n + i)r]-5j«r])/r.

Taking into account the fact that during the functioning of control algorithm we can form

sampled-data functions <5'[;27'] describing the

trajectories of links movement, then to determine

derivatives in the points of tool movement

trajectory it is advantageous to use control algorithms for the model. While simulating the process of motion differentiation of digital sequences is presented as a sum of the kind:

where V^[/t] = q[n] — q[n — 1] - inverse

difference; m - number of terms of a degree series; m

fl. =(—1)'^A' 'Cj[. ; C'j. - binomial

/=o coefficients.

Besides the considered control method on the graphical model it is necessary to include

algorithms of programmed control by the path

reference point into mathematical calculations and

software. In this case reference points P[x, y] and

angles of tool orientation in each of them are assumed. Taking into account these values we form

the data base to develop the laws of generaUzed

coordinates changes. Motions planning thus is fulfilled on the basis of interpolation with cubic

3 spUnes; S-^{t) = ^^,^,1.?^ •

Coefficients df^ are calculated in each section of

interpolation having assumed that the trajectory is continuous and smooth. Planning of robot's movement is carried out with account of limitations

in degrees of freedom which are preset with

reference to the table of Umit values for each

coordinate q'TM" < <7y < qf^

i

271
The authenticity of the measured is of great

importance for control. In the encoding position sensors being used there may be abnormal short- Term imperfect data that can lead to short-term

limit accelerations and deviations from the

trajectory. Casual character of some charges of

these sensors makes us to introduce predictive and

correcting algorithms of simple calculating

structure into the algorithms of robot control. In the applied algorithms expected values of position

along the coordinates for the period of change T are predicted in each control step with help of m degree

polynomial. Meanwhile we apply algorithms of

single prediction, which is based on Lagrangian

interpolating polynomial.

where fc= 1,2,3 - prediction step. The analysis of prediction errors has shown that algorithms of double prediction should be applied

for robots and values in three points (m=3) are to be

taken. For convenience in usage of predictive

expressions and reductions of calculations it is better to use recurrent form of the analysis.

A robot software solves the following problems:

analog and discrete information about the parameters of robot condition is obtained, interface with drivers of analog inputs and outputs, output of

discrete and analog control signals, formation of

technological and emergency information, data

display in real time. The programs can function in the environment of Windows and other versions

and use all possibiUties of this environment. Drivers

for data exchange are formed as dynamic libraries DLL. The software includes robot models, which

allow to carry out check of algorithm operation.

The material is prepared on the basis of the authors'

research, which was carried out while developing

robotic system for wood processing. The presented

kinematic structure, algorithms of motions planning

and control have been investigated on the models.

Computer simulation of robot motions has shown

the effectiveness of the described methods and

algorithms. The obtained results of simulation were appHed while developing and designing robots for cutting and spacing of wood.

4. CONCLUSION

272
SESSION 5

ECONOMIC ASSESSMENT OF

AUTOMATION AND ROBOTICS

TECHNOLOGIES

273

An Economic Assessment of Selected

Integration and Automation Technologies

Robert E. Chapman

Office ofApplied Economics, Building and Fire Research Laboratory (BFRL)

National Institute of Standards and Technology (NIST), Gaithersburg, MD 20899

robert.chapman@nist.gov

Abstract: This paper presents a critical analysis of the economic impacts of past, ongoing, and planned

research of BFTlL's construction systems integration and automation technologies (CONSIAT) program. The

CONSIAT program is an interdisciplinary research effort within BFRL to develop key enabling technologies, standard communication protocols, and advanced measurement technologies needed to facilitate the dehvery of

fully-integrated and automated project process (FIAPP) products and services to the construction industry.

BFRL is participating in a public-private partnership focused on early commercialization of FIAPP products

and services. The results of this analysis demonstrate that the use of FIAPP products and services will generate

substantial cost savings to the capital faciUties industry. The present value of savings nationwide expected

from the use of FIAPP products and services in capital facilities over the next 15 years exceeds $3.5 billion. The present value of cost savings due to the pubUc-private partnership's efforts focused on early

conmiercialization of FIAPP products and services is expected to exceed $280 million.

Keywords: Building economics; commercial buildings; construction; impact evaluation; industrial facilities

L INTRODUCTION:

The capital facilities industry' is facing several

significant competitive challenges that will affect

its future growth potential. Owners of capital

facilities and contractors engaged in the

construction of those facilities are pressing for

reductions in delivery time as a means of

improving their competitive positions. Owner

concerns over both the first costs and the life-cycle costs of capital facilities and tightening profit

margins for contractors are also affecting the

competitive positions of each stakeholder. One

means of improving the competitive position of

each stakeholder in the capital facilities industry is through the development, adoption, and use of

The capital facilities industry covers constructionrelated activities and the associated supply chains

throughout the life cycle of industrial facilities and

commercial buildings. Industrial facilities include

utilities, government facihties, and facilities where the manufacturing of products or commodities takes place.

Commercial buildings include private- and publicsector office buildings, institutional buildings, and

service businesses.

fully-integrated and automated project process

(FIAPP) products and services.

FIAPP products and services offer the potential to reduce capital costs, reduce the delivery time of

capital projects, and improve safety performance

during construction. But investments in and the use of FIAPP products and services will be

forthcoming only if the capital facilities industry

perceives that the economic benefits outweigh the

costs of using such products and services. Being

able to demonstrate net economic savings from

using FIAPP products and services will encourage

their acceptance and use. The focus of this paper

is on documenting how the use of FIAPP products

and services in the capital facilities industry will

generate significant net economic savings to the owners, operators, and managers of those facilities and to the contractors engaged in the construction

of those facilities. These savings are based on

results published in two economic impact

assessments of BFRL's CONSIAT-related

research and development effort [1,2].

275
2. A CASE STUDY OF THE CAPITAL

FACILITIES INDUSTRY:

The case study is divided into two sections. The

first section focuses on data and assumptions. The

second analyzes the cost savings from FIAPP

products and services in the capital facilities industry.

2. 1 Data and Assumptions

The base year establishes the anchor point for all calculations. The base year for computing all FIAPP-related costs and savings is 1997, a year for which authoritative and comprehensive

construction industry cost data are available.

The diffusion of FIAPP products and services into

the capital facilities industry employs two sets of

diffusion models: one set for industrial facilities and one set for commercial buildings. Each set employs a primary diffusion model. The primary

diffusion model, P,^ (t), gives the proportion of

potential users who employ FIAPP products and

services in time period t, where t = 1 corresponds

to 2005, the anticipated time of first commercial

use. In each set of diffusion models, the subscript

7] designates the market saturation level. The

diffusion of FIAPP products and services into the

marketplace is modeled up through 2017. By

2017, the use of FIAPP products and services is expected to be widespread. For more about the

diffusion models, see [1,2].

In order to estimate costs and savings due to the use of FIAPP products and services, it is necessary

to specify both a base case and a FIAPP

alternative. The term base case is used to represent the configuration that maintains the

status quo (i.e., the "average" use of traditional

design, information, and construction

technologies). The FIAPP alternative is the

configuration that provides equivalent or enhanced

performance for all features of the base case through the use of FIAPP products and services.

There are two key differences between the two

configurations. First, the degree to which

construction activities (e.g., materials

management) and facility service features (e.g.,

maintenance and repair procedures) are integrated,

automated, and controlled is significantly higher in the FIAPP alternative. The second difference is that the FIAPP alternative has the potential to achieve enhanced performance for selected

construction activities (e.g., better control of

project cost and schedule) and facility service

features (e.g., reduced maintenance and repair

costs). These differences, although interrelated, are crucial in structuring differences in costs (e.g.,

due to the installation of additional equipment and

software to generate improved systems integration,

automation, and control) and savings (e.g.,

maintenance and repair cost savings due to the

availability of electronic "as-buik" information)

between the two configurations

The enhanced performance of the FIAPP

alternative vis-a-vis the base case produces five

types of cost savings. These cost savings are: (1)

lower first costs; (2) lower maintenance and repair

costs; (3) fewer construction-related accidents; (4)

reductions in delivery time; and (5) higher net income for contractors. Lower first costs are registered through a reduction in a typical project's

total installed costs (i.e., all project-related costs with the exception of land costs). Lower

maintenance and repair costs are registered

through reductions in future costs. Fewer

construction-related accidents are registered

through reductions in direct jobsite costs (e.g.,

medical costs), indirect jobsite costs (e.g., lost productivity of the crew due to the accident), and

liability costs (e.g., claims costs). Reductions in delivery time are registered through increased

opportunities for product sales and rental income.

Higher net income for contractors is registered

through the contractor's increased capability to control cost growth during the project delivery

process. Cost savings accrue to owners and

contractors in different ways. Lower first costs, lower maintenance and repair costs, and savings

stemming from the earlier start-up of operations accrue to the owners and operators of capital

facilities. Cost savings due to fewer constructionrelated accidents and higher net income accrue to contractors.

If capital facility owners, operators, and

contractors employ the FIAPP alternative rather

than the base case, they can expect to bear three

types of additional costs. These costs are: (1)

276
higher evaluation costs; (2) increased costs of

adapting new building products and services to industry use; and (3) increased training costs. These three costs may be classified as newtechnology introduction costs. Ehlen and Marshall

[3] define new-technology introduction costs as those costs covering the activities that bring the

material/product from the research laboratory to

full field implementation. New-technology

introduction costs include the extra time and labor

to design, test, monitor, and use the new

technology. Ehlen' s and Marshall's research on

new-technology introduction costs is particularly

relevant for this case study because they

demonstrate that new-technology introduction

costs disappear once the designer is satisfied with

the technology's performance, the technology

enters full implementation, and its application has

become routine.

In performing the calculations presented in this case study, as well as those presented in [1, 2], a conservative approach to the estimation of savings

and costs was employed. Potential cost savings

are estimated based on project data from the

Construction Industry Institute (CII)

Benchmarking and Metrics Database." These data were provided to NIST by CII as part of a research

collaboration on the use of design/information

technologies [4]. Because these technologies are commercially available now, they do not include

the full potential for savings expected from FIAPP

products and services. Thus, the cost savings

reported here are lower-bound estimates of the

savings expected from the use of FIAPP products

and services. On the other hand, new-technology

introduction costs are held constant throughout the

study period. Since these costs are expected to decline over time, the estimated values for net economic savings reported here are also lowerbound estimates.

2.2 Analysis Results

Three types of information were combined to generate an estimate of cost savings nationwide.

These three types of information are related to: (1) the diffusion models; (2) the cost savings due to

All data provided to NIST by CII have been

aggregated in a manner that precludes identification of

an individual company's or project's performance.

reductions in first costs, maintenance and repair

costs, and construction-related accidents and the

increases in net income for owners and contractors due to reductions in delivery time and higher

contractor profit margins; and (3) new-technology

introduction costs. Estimates are produced for each year from 2005 to 2017. Each year's net cost savings was then discounted to a present value and

summed to get the present value of cost savings

nationwide. All present value calculations are based on standardized practices [5].

Table 1 summarizes how cost savings by category

and in total are calculated. The years for which

cost savings are calculated are listed in Column 1 of Table 1. Annual values for each category of

cost savings are recorded in Column 2 for first costs. Column 3 for maintenance and repair costs. Column 4 for reductions in delivery time. Column

5 for higher net income for contractors, and

Column 6 for construction-related accidents

avoided. Note that no cost savings for any

category occur until 2005, the year in which

FIAPP products and services are expected to first become commercially available.

Reference to Columns 2 through 6 of Table 1 reveals different rates of change for cost savings.

Cost savings increase slowly at first and then

increase rapidly during the middle years (e.g.,

2009 through 2013). The middle years of the

study period correspond to the greatest rate of

penetration of FIAPP products and services into

the market place. Market penetration is modeled

through application of two sets of diffusion

models. As the rate of penetration into the market

place slows, cost savings level off. In the case of

the maintenance and repair category (see Column

3), cost savings peak in 2014 and then decline.'' The differing rates of change have implications for

net cost savings nationwide, which are presented

in Table 2.

In addition to annual cost savings by category.

Table 1 also contains total cost savings by year.

^ Reductions in maintenance and repair costs are measured on an annually recurring basis from the date of installation until the end of the study period in 2017.

Thus, installaUons in the early (e.g., 2005) and middle

years (e.g., 2012) have more years to generate savings than those occurring at the end of the study period.

277
These cost savings are recorded in Column 7. Total cost savings for each year equal the sum of

each category's cost savings for that year. Total

cost savings, denominated in millions of 1997

dollars, increase steadily between 2005 and 2016.

Table 2 summarizes how the present values of net

cost savings nationwide by year and in total are

calculated. The table also includes information on

total cost savings, additional FIAPP-related

installation costs, net cost savings, and the

discount factor needed to translate yearly net cost savings into yearly present value cost savings

nationwide. The years for which present values

are calculated are listed in Column 1 of Table 2. Column 2 contains total cost savings by year in

millions of 1997 dollars. The total cost savings for

each year is transferred from the respective row of

Column 7 of Table 1. The new-technology

introduction costs associated with investments in

FIAPP products and services for each year are recorded in Column 3 of Table 2. The difference

between total cost savings and new-technology

introduction costs equals net cost savings. Column

4 records net cost savings for each year in millions

of 1997 dollars. Note that net cost savings

increase steadily until 2015. The calculated value

of the single present value factor for each year is recorded in Column 5. All entries are calculated

using a real discount rate of 7 %. Because 1997 is the base year, the single present value factor takes on a value of 1 .0 for that year. For years following

1997, the single present value factor is less than

1.0. The present value of net cost savings

nationwide by year is recorded in Column 6. It equals the product of the net cost savings, in

Column 4, and the single present value factor, in Column 5, for that year. Note that the present

value of net cost savings nationwide increases

steadily until 2015.

Because the entries in Column 6 are in present

value terms, they can be summed to get total cost savings nationwide over the entire study period.

Total cost savings nationwide resulting from the

three sets of baseline analysis calculations are more than $3.5 billion ($3 532 million in present

value 1997 dollars); see the bottom of Column 6 in Table 2.

Reference to Table 2 demonstrates the magnitude

of the savings to the nation from using FIAPP

products and services in the capital facilities industry. These cost savings nationwide also

provide a basis for measuring the value of the

public-private partnership's contribution. BFRL's

dual role as a facilitator and developer of key

FIAPP enabling technologies is expected to speed

up the introduction of FIAPP products and

services into the commercial marketplace.

Because of the public-private partnership, FIAPP

products and services are expected to be

commercially available in 2005. Without a viable

public-private partnership, the commercial

introduction of FIAPP products and services is expected to be delayed until 2009. Information

from subject matter experts and similar economic

impact assessments suggest a range of values from

two to five years for the likely delay. See [ 1 , 2] to examine how variations in the likely delay were

modeled.

Because the public-private partnership's efforts are expected to result in faster introduction of FIAPP

products and services, those savings which would

have been foregone in the event of a delay are

attributable to the public-private partnership.

Therefore, any savings over the first four years

(starting with 2005), prior to the "delayed"

introduction of FIAPP products and services in 2009, would have been foregone. Such an

accounting framework may be handled through

use of a 0 or 1 weighting factor. For those years in which savings are attributable to the public-private

partnership, the weighting factor takes on a value

of 1 . The present value of those four-year' s worth

of savings exceeds $280 million, a strong

indication of the value added of the collaborative

efforts of the public-private partnership.'*

3. CONCLUSIONS:

The $3.5 billion magnitude of national cost savings is impressive. Does it indicate, however,

that investment in FIAPP products and services by

individual owners and contractors will be cost

effective? The answer to that question is almost

certainly yes. Consider the case of the earliest

I

CONSIAT-related research and development costs by

BFRL are not included in the results presented in this

article. Readers interested in how these costs were used

to estimate the return on the public sector's CONSIATrelated investment are referred to [1, 2].

278
i adopters of FIAPP products and services, those owners and contractors expected to invest in 2005.

j The aggregate investments, as measured by newi technology introduction costs, made by these

owners/contractors is estimated as $24.0 million

(see column 3 of Table 2). Their total cost savings

are estimated as $71.6 million (see column 2 of

Table 2). Thus, every dollar invested in 2005

generates nearly $3.00 in return. However, this is an incomplete picture, since the savings and costs accruing to owners and contractors are not evenly

distributed. A more complete picture is provided

through reference to Table 1. In Table 1, the

different streams of cost savings are recorded

' according to whom they accrue. The owners of

capital facilities capture the cost savings recorded

i in Columns 2, 3, and 4, whereas contractors capture the cost savings recorded in Columns 5

I and 6. For early owner adopters, the entries in Columns 2 and 4 represent immediate, first-year

i cost savings of approximately $40.0 million.

; Thus, the entire fost year's investment (i.e., new-

, technology introduction costs) can be covered by

first-year cost savings captured by owners. Future

: owner cost savings due to reduced maintenance

ij and repair expenditures add another $15.5 million.

( Contractor cost savings are lower than owner cost

savings, but part of these lower savings are due to the more stringent values of incidence rates

jj associated with the CII safety data versus industry

1 incidence rates in calculating improved safety

I performance. Thus, it is likely that even if contractors bear a larger share of new-technology

introduction costs, they will find investment in FIAPP products and services to be highly cost

effective. These savings, coupled with the

|, likelihood that new-technology introduction costs

will decline over time, indicate that FIAPP

products and services are an emerging technology

whose time has come.

4. REFERENCES:

1. Chapman, Robert E. 2000. Benefits and

Costs of Research: A Case Study of

Construction Systems Integration and

Automation Technologies in Industrial

Facilities. NISTIR 6501. Gaithersburg,

MD: National Institute of Standards and

Technology.

2. Chapman, Robert E. 2001. Benefits and

Costs of Research: A Case Study of

Construction Systems Integration and

Automation Technologies in Commercial

Buildings. NiSTIR 6763. Gaithersburg,

MD: National Institute of Standards and

Technology.

3. Ehlen, Mark A., and Harold E. Marshall.

1996. The Economics of New-Technology

Materials: A Case Study of FRP Bridge

Decking. NISTIR 5864. Gaithersburg,

MD: National Institute of Standards and

Technology.

4. Thomas, Stephen R., Candace L. Macken,

and Sang-Hoon Lee. 2001. Impacts of

Design/Information Technology on

Building and Industrial Projects. NIST

GCR 01-828. Gaithersburg, MD: National

Institute of Standards and Technology.

5. American Society for Testing and

Materials (ASTM). Fourth Edition, 1999.

ASTM Standards on Building Economics.

West Conshohocken, PA: ASTM.

I

279
Table 1. Cost Savings by Category and in Total by Year: 2005-2017

Year

Annual Cost Savings in Millions of 1997 Dollars by Category Due to Total Cost Savings

by Year in Millions

oi iw/ uoiiars

IVCuUCllUlu Ul First Cost

Reduced

Maintenance

and Repair

RpHi IXCUUV.I'lvFlld K^lii^tic inUl Delivery Time

Higher

Contractor Net Income

Improved

Safety Performance

Col. (1) Col. (2) Col. (3) Col. (4) Col. (5) Col. (6) Col. (7) (2)+<3)-K4)+(5)+{6)

2005 20.6 15.5 19.7 15.1 0.7 71.6 2006 49.9 29.6 47.2 36.7 1.6 165.0 2007 79.9 40.5 74.5 58.7 2.4 256.0 2008 125.5 62.7 115.6 92.2 3.6 399.7 2009 192.1 94.5 174.7 141.1 5.2 607.6 2010 283.2 137.1 254.3 208.1 7.3 890.1 2011 397.6 189.6 352.6 292.1 9.7 1 241.7 2012 526.5 247.1 461.3 386.8 12.2 1 634.0 2013 655.5 299.3 567.4 481.6 14.4 2 018.2 2014 769.9 330.9 658.5 565.6 16.0 2 340.8 2015 861.0 323.1 727.7 632.5 17.0 2 561.3 2016 927.5 261.3 774.9 681.4 17.3 2 662.5 2017 973.2 146.8 803.6 715.0 17.2 2 655.8

Table 2. Present Value Cost Savings Nationwide by Year and in Total

Year

Total Cost

Savings in Millions

NewTechnology

Introduction Costs

Net Cost

Savings in Millions by

Year

Single Present Value Factor by

Year

Present Value of Net Cost Savings

Nationwide by

Year in Millions

Col. (1) Col. (2) Col. (3) Col. (4)

(2) -(3)

Col. (5) Col. (6) (4) X (5) 2005 71.6 24.0 47.6 0.582 27.7 2006 165.0 58.3 106.7 0.544 58.0 2007 256.0 93.3 162.7 0.508 82.7 2008 399.7 146.6 253.1 0.475 120.2 2009 607.6 224.4 383.3 0.444 170.2 2010 890.1 330.8 559.3 0.415 232.1 2011 1 241.7 464.4 777.3 0.388 301.5 2012 1 634.0 615.0 1 019.0 0.362 369.3 2013 2 018.2 765.6 1 252.6 0.339 424.3 2014 2 340.8 899.2 1 441.7 0.317 456.4 2015 2 561.3 1 005.6 1 555.7 0.296 460.3 2016 2 662.5 1 083.4 1 579.1 0.277 436.6 2017 2 655.8 1 136.7 1 519.1 0.258 392.6 TOTAL 3 531.9

280
A Micro Level Analysis Of The Relationship Between Changes In Equipment Technology And

Wages In The U.S. Construction Industry

by

Paul M. Goodrum ' and Manish Gangwar

ABSTRACT:

A shortage of skilled labor exists in the construction industry. Fortunately, advancement in construction

equipment and material technologies, along with modularized components and estimating and scheduling

strategies have offset the shortage of skilled construction labor. The construction industry has witnessed a drop in real wages since 1970. Decline in real wages may be attributed to a combination of

socioeconomic factors like migrant laborers, fringe benefits, safety procedures, union membership and

worker skills. Another factor that may be impacting construction real wages is technological changes over

the past couple of decades; including technological changes in construction equipment. There is a growing need to understand how changes in technology are affecting employment conditions in construction. If more could be known about how technology affects wages, the industry could formulate

better strategies for future workforce needs. This paper examines the relationship between changes in equipment technology and changes in construction wages with the help of five factors of equipment

technology change; control, energy, ergonomics, functionality and information processing. Furthermore,

data from the U.S. Bureau of Labor Statistics' Current Population Survey (CPS) is used to examine the

effects of computer usage on wages among hourly workers in construction.

KEYWORDS:

1. INTRODUCTION:

The U.S. construction industry

contributes significantly to the U.S. economy.

When one includes construction related business

involving design, equipment and materials

manufacturing, and supply, the construction

industry accounts for 13% of the GDP, making it the largest manufacturing industry in the U.S.

(BEA 2000).

The shortage of skilled workers is considered to be one of the greatest challenges

facing the U.S. construction industry. Not since

the early 1970s and post World War II has the

U.S. construction industry experienced such low

unemployment rates (BLS 2002). Advances in construction equipment and material

technologies, modularized components, and

estimating and scheduling strategies have offset the shortage of skilled construction labor. However, there is a perception among industry

leaders that the skilled worker shortage is getting worse. A survey of facility owners showed that 78% thought the skilled worker shortage had

increased during the past 3 years (Rosenbaum

2001).

Although real wages in general in the

U.S. began to outpace inflation in the late 1990' s, there has been a long-term decline in construction real wages since the 1970's

(Allmon, et al. 2000 and Oppedahl 2000). Other

industries, such as manufacturing, have also

experienced declines in real wages; however, the

declines have typically been greater in construction. This greater decline may be due to a combination of socioeconomic factors including an increase in migrant laborers in construction, fringe benefits, and construction

safety, and a decrease in union membership and

worker skills (Oppedahl 2000, Goodrum 2002).

Another factor that may be impacting

construction real wages is technology. Over the

past couple of decades, there has been a wide

array of technological changes in construcdon

equipment and material technology.

Construction equipment has become more

powerful, automated, more precise, safer, and more functional, allowing workers to be more

productive in construction activities. In many

instances, technology has made construction

equipment easier to use. One example is heavy

machinery. Advancements in hydraulic controls

1. Assistant Professor, Department of Civil Engineering. 151C Raymond Bldg., University of Kentucky, Lexington, KY 40506-0281

email: pgoodrum@engr.uky.edu

2. Graduate Research Assistant. Department of Civil Engineering, 151D Raymond Bldg., University of Kentucky, Lexington. KY

40506-0281 281
and microprocessors have automated and

simplified the operation of earthmoving

machinery. There have also been advancements

in construction equipment that have introduced new technologies that require skill sets normally

outside those traditionally required for

construction. For example, the use of Global

Positioning Systems onboard earthmoving

equipment now require equipment operators to be proficient in the use of computers.

2. METHODOLOGY

This paper examines the effect of

equipment technology on construction wages in two parts. First, the effects of changes in equipment technology on real wages from 1976

to 1998 are examined. This involves examining

the changes in five technology factors (Amplification of Human Energy, Level of

Control, Functional Range, Ergonomics, and

Information Processing) and the change in the

average wage of workers in crews for 100

construction activities. Second, the effects of

computer usage on construction wages are examined for 470 individual hourly construction

workers.

2.1. Equipment Technology Defined

This research examines the effect of

changes in equipment technology on

construction wages, specifically the equipment

technologies of hand tools, machinery, and

computers. Hand tools include pneumatic nail guns, electric drills, circular saws, and similar

types of tools. Machinery includes cranes, grout

pumps, bulldozers, and similar types of

implements.

2.2. Technology Factors To examine how different mechanisms

of equipment technology change have

influenced construction wages, five factors were

identified (defined below and examples

discussed later) to characterize changes in technology.

Amplification of Human Energy: technology designed to make an activity easier

to perform physically. In its simplest terms, it can be regarded as the shift in energy from

human to machine bringing an increase in energy output.

Level of Control: advances in machinery

and hand tools that transfer control from human

to machine.

Functional Range: changes that expand

a tool or machine's range of capabilities.

Ergonomics : technology that alleviates

physical stresses imposed on a worker and helps

the worker cope with the work environment

Information Processing: over time,

construction equipment has been designed to provide greater and more accurate information

regarding internal and external processes. This

factor includes the incorporation of computers

into the work processes.

3. DATA SOURCES

3.1. Estimation Manual

The data for the research came from the

estimation handbook Means Building

Construction Cost Data (Means) and the

Computer and Internet Use Supplement, data

files for 2001 from the U.S. Bureau of Labor

Statistics* Current Population Survey. Wage

data from the 1976 and 1998 Means estimation

handbooks on 100 activities was collected to examine the effects of changes in equipment

technology (as defined by the technology

factors) on construction wages. Data from the

CPS was used specifically to examine the effects of the use of computers on construction wages.

These estimation handbooks provide

wage data, unit labor costs, unit equipment

costs, physical output data, and work-hour

requirements for construction activities. While

the handbooks are a valuable source of

information about construction cost and

productivity across time, there are some

limitations to the data. The contractors who

provide the figures for the manuals are not required to build a project using their estimations; this leads some contractors to submit inflated estimates of construction costs (Pieper 1989).

Three criteria were used to select

activities for inclusion in the study. The first criterion was that the same activity be found in

282
both the 1998 and 1976 estimation manuals.

Due to changes in methodology, materials, or

lack of use in construction, a number of

activities included in the 1976 manual were not included in the 1998 manual. Likewise, a number of new activities were included in the

1998 manual due to new methodology or

materials. Second, activities from a diverse

range of technological changes were selected. Third, activities were selected to represent a wide range of activity types from different

divisions of the Construction Specification

Institute (CSI) master format.

3.2. CPS September 2001 Computer and Internet Use Supplement

To further examine the effects of

computer usage on construction wages, data was

collected from the September 2001 Computer

and Internet Use Supplement from the U.S.

Bureau of Labor Statistic's (BLS) Current

Population Survey (CPS). The CPS is a monthly survey of approximately 50,000

households conducted by the U.S. Census

Bureau for the U.S. Department of Labor. With

the survey being conducted for more than 50

years, CPS data provides information on economic indicators, which influence U.S.

governmental policy. Data from the CPS is available to the public via their website.

(http://www.bls.census.gov/cps/cpsmain.htm).

Each month, the CPS randomly selects 59,000 housing units (e.g. single family homes,

townhouses, condominiums, apartment units,

and mobile homes) for the sample, and

approximately 50,000 are occupied and eligible for the survey. The other units are found

ineligible because they have been destroyed,

vacant, converted to nonresidential use, or contain persons whose usual place of residence

is elsewhere. Respondents are asked questions

about the employment information and

demographic characteristics of each member of

the household over 14 years of age. In September 2001, the Computer and Internet usage survey was added as a supplement to that month's CPS. In addition to the demographic

data collected each month, the Computer and

Internet Supplement contained questions about

the respondent's use of computers, including the

use of computers at work, which was used in the

research's analysis.

A number of criteria were used to select cases (each case representing an individual

respondent) from the September 2001 CPS

Computer Supplement data. First, only

individuals listing their primary industry of

employment as constmction were selected. Next, each case had to meet the following series

of additional selection criteria:

1. Full-time hourly workers;

2. Male construction workers;

3. Non-supervisory construction workers;

4. Hourly wage greater than or equal to the

U.S. minimum wage of $5.15/hour.

The use of these selection criteria resulted in 470

cases.

4. ANALYSIS

4. 1 . Effects of Changes in Equipment

Technology on Real Wages from 1976 to 1998

4.1.1. Measured Change in Equipment

Technology

The authors identified and examined 43

types of hand tools and 3 1 types of machinery in the 100 construction activities. Obviously,

many hand tools and machinery were used in several activities. Equipment technology

changes were identified using equipment

catalogs, handbooks and specifications. Figure 1 shows the number of activities that experienced

a change in equipment technology in at least one

tool or item of machinery for each of the

technology factors. As shown in Figure 1, more than 70% of

the activities experienced an increase in energy

output. Prior related research indicates that the

metals, wood and plastic, and site-work

divisions experienced the greatest amount of

change in tool and machinery energy output

(Goodrum and Haas 2002). One example of

change in energy output in the metals division

involves welding machines, which offer

increased wattage output. The powder actuated

systems in the metals divisions used in metal

decking offer greater depth penetration for

installed studs. In addition, by 1998 cranes

283
offered more lifting capacity than available in 1976. In the wood and plastic division, circular saws operated at higher RPMs, and the

pneumatic nail gun required less human energy

than a hand held hammer. Most site work

machinery increased in horsepower output

including front-end loaders, dump trucks,

backhoes, bulldozers, graders, asphalt pavers, and scrapers. As seen in Figure 1, almost half of

construction activities experienced a change in the amount of human control needed from 1976

to 1998. Welding machines in the metals

division, for instance, are now equipped with

remote controlled amperage adjusters and

powder actuated systems have semi-automatic

loading capability. The pneumatic nail gun has

replaced the hand held hammer in the woods and

plastic division and in formwork installation in the concrete division. Also in the concrete

division, pump trucks are now equipped with

remote controlled booms, and concrete vibrators

automatically adjust the vibration frequency to match the concrete's slump.

Changes in functional range occurred in

slightly less than half of the activities (Figure 1). Through advancements in hydraulic controls and

microprocessors, site-work machinery now has

greater precision and a longer reach for booms

and buckets. Excavators and backhoes are capable of digging deeper.

Figure 1 shows that exactly half of the

construction activities experienced some change

in ergonomics. For example, by 1998 many

hand tools, such as circular saws, hand drills,

pneumatic nail guns, and caulking guns, were

lighter and operated with less noise and

vibration than their predecessors.

Almost all of the advances in information processing occurred in heavy

machinery (Goodrum and Haas 2002). This

finding explains why most construction

activities did not experience such an improvement in equipment technology. For

example, some heavy machinery now offer self- monitoring and self-diagnostic systems.

4.1.2. Measured Change in Real Wages

Daily crew wages as reported in Means

were divided by the number of crewmembers in

each activity to estimate individual worker's

daily wage. In order to measure real wages

(wages adjusted for inflation), the Census

Construction Cost Index was used to normalize

wages to 1990 levels. A description of the

Census Construction Cost Index can be found at the Department of Commerce website

(http://www.census.gov/prod/3/98pubs/c30-

9805.pdf).

The overall average change from 1976

to 1998 in a worker's daily real wage was - $19.97, with a 95% confidence interval of ±

$6.97. This confirms other findings that show a long-term decline in construction real wages

(AUmon, et al. 2000, Oppedahl 2000). Figure 2

illustrates the average changes in daily real wages for each division of the CSI Master

format.

On average, concrete activities experienced the largest decline in daily real wages, while masonry activities experienced

little change. Further research is needed to determine the reasons behind the various sector changes.

4.1.3. Relation Between Equipment Technology

and Partial Factor Productivity Change

Analysis of Variance (ANOVA) is used

to test whether two or more groups have

statistically significant different means. The

ANOVA test estimates the statistical significance of the difference between the means

(F-value), and it measures the amount of

variation in the dependent variable that is explained by the independent variable Eta

Square (e). The ANOVA analyses compared the

daily real wage changes from 1976 to 1998 for

(1) activities that experienced a change

according to the technology factor and (2)

activities that had not. Figure 3 shows the

ANOVA resuhs.

With the exception of energy and

ergonomics, the activities that observed a change

in equipment technology experienced a

statistically significant different decline in daily

real wages. Activities with an equipment

change in functional range and information

processing experienced over 60% less of a

decline in daily real wages compared to

activities without such changes. One possible

284
explanation for these differences is the added

skills required for workers to adopt these types

of equipment technology changes, which may

result in higher wages. Activities experiencing a change in level of control actually experienced

over 150% more of a decline in real wages

compared to activities without change. A

possible explanation for this added decline is that many changes in level of control serve to simplify the processes, which may result in lower wages. Further research in the area is needed to examine other reasons.

4.2. Effects of Computer Usage on Construction

Wages

One result of the previous set of

analyses was that information processing has a

substantial and significant relation with activities that saw less of a decline in daily real wages

compared to activities that did not experience

such a change. Because this phase of the study was limited to examining changes in equipment

technology that were widely diffused in construction, most of the changes in information

processing were found only in heavy machinery.

To further examine how changes in information

processing affect construction wages, data from

the CPS September 2001 Computer Supplement was analyzed.

4.2.1 Measured Computer Usage Among NonSupervisory Construction Workers

Of the 470 cases analyzed in the CPS

September 2001 Computer Supplement, 49

(10.4%) indicated they used a computer at work.

The top three occupations that used computers

were: (1) electricians, (2) electrical power

installer and repairers, and (3) plumbers.

Occupations in which there were no respondents

indicating they used computers as work

included: roofers, concrete and terrazzo

finishers, electrician apprentices, hard and soft

tile setter's, insulation workers and sheet metal

duct installers. Unfortunately, the Computer

Supplement data did not measure how the

computers were used at work.

4.2.2. Relation Between Computer Usage and

Wages in Construction

Data was analyzed from the CPS

September 2001 Computer Supplement to examine the effects of computer usages on

construction wages by comparing hourly wages

between construction workers who use a computer at work and those who do not use computer at work (Figure 4). The difference in education, work experience, and age was also

examined between those who do and do not use

a computer at work.

Information from the CPS is used to create more than 350 variables. The CPS,

however, does not ask respondents about their work experience, an important consideration in a study on wage differentials. One method for estimating work experience, used by the BLS, is to use CPS data to calculate potential experience

using the following equation (1) (U.S.

Department of Labor. (1993)). The units of

potential experience are given in years.

Potential Experience = Age - 6 - Years of School ( 1

)

Variable for education was recoded by

the researchers to represent number of years of

education completed at school. Women's work

experience is found to be substantially

influenced by being married and having

children. To avoid these influences, this study

focused on men.

These analyses show that nonsupervisory construction workers who use computers at work are significantly paid more

than workers who do not use computers at work

(the average hourly wage among workers who

use computers was $18.43 compared to $15.56

for those who did not). At the same time,

workers who use computers at work are

statistically significantly more experienced

(workers who used computers had on average 22

years of experience compared to 18 years of

experience for those who did not); more

educated (workers who used computers had on

average 12.8 years of education compared to 11.6 for those who did not); and older (workers

who used computers were on average 40.8 years

old compared to 35.7 years old for those who

did not). Although this analysis indicates a

relation between higher wages and the use of

285
computers for non-supervisory construction

workers, it is not clear whether the increase in average hourly wage is due to usage of computer

or merely a reflection of already established

relations with experience, education and age.

5. CONCLUSIONS:

The findings reported here indicate that:

1. The decline in real wages exists

throughout all sectors and divisons in construction.

2. Activities that experienced a change in

Functional Range and Information

Processing experienced less of a decline

in real wages compared to activities that did not.

3. Not all changes in equipment technology

are related to lessened declines in real wages. Activities that experienced a change in Level of Control actually

experienced greater declines in real wages.

4. Non-supervisory construction workers

who use computers at work earn higher

hourly wages, although further research is needed to account for the effects of

experience, education, and age.

6. REFERENCES:

1. Allmon, E., Haas, C, Borcherding, J., Goodrum, P. (2000). "US Construction Labor Productivity Trends, 1970-1998." J. Constr. Engrg. And Mgmt., ASCE.

126(2), 97-104

2. Bureau of Economic Analysis (BEA) Website (2000). http://www.bea.doc.gov Accessed April 2002

3. Bureau of Labor Statistics (BLS) 2002, Current Employment Statistics Survey, http://www.bls.gov/ces, accessed June 13, 2002.

4. Goodrum, P., and Haas, C. (2002). "Partial Factor

Productivity and Equipment Technology Change at the Activity Level in the U.S. Construction Industry." J. Constr. Engrg. And Mgmt., ASCE. (Forthcoming).

5. Means Company, Inc (19XX). Building Construction Cost Data. Philip Waier, Sr. Editor, Kingston, MA.

6. Oppedahl, D. (2000). "Understanding the (relative) rise and fall of construction Real Wages." Chicago Fed

Letter. (155): 1-4.2000 Jul

7. Pieper, P. (1989). "Construction Prices Statistics Revisted" in Jorgenson, D. and Landau, R. Technology

and Capital Formation

8. Rosenblum. (2001). "Craft Labor Shortage Provokes More Study of Pay and Safety." Engineering News

Read, McGraw Hill, August 20 2001. PI 1.

9. Slater, S.. ed. (1997). Business statistics of the United

States, Bema Press, Lanham, Md. U.S. Department of

Labor. (1993). labor Composition and U.S.

Productivity Growth, 1948-90. U.S. Government

Printing Office, Washington, D.C.

Control Functional &gonomic Information Range Processing

Figure 1 : Change in Equipment Technology by Tecnology Factors, 1 976 - ms

-$0.21 -SlO.Ql

I -IT5.57

-$36.88

Masonary

Sitework

Doors, Windows

Metals

Electrical Mechanical

Specialities Finishes Moisture-Thermal Wood & Plastic Concrete

-$50.0 -$40.0 -$30.0 -$20.0 -$10.0 $0.0

Figure 2: Change in Daily Real Wages (1990$) by Division

(Data SoufCC ! Means lOXX)

i E3 Activities with No Change Activities with Change

Energy

Functiona] Range I

$0 I S -$5

•H |-$10 -H « --$15 ag -$20 I

-$25 § -$30 ^ -$35 F=0.018 F=7.625* F=6.431* F=0.604 F=7.518*

e =0.000 e =0.069 e =0.062 e =0.006 e =0.071

Figure 3: A Comparison of Daily Real Wages Change froml976 to 1998 for Activities that Experienced a Change in Equipment Technology and Activities with nn rhanop *p -» 0 OS

^ Not using Computer at Work Using Computer at Work

o Wage in $ Edu in Yrs Exp in Yrs Age in Yrs ° F=7.16* F=15.02* F=4.81* F=8.78*

e =0.015 e =0.031 e =0.010 e =0.018

Figure 4: Difference in Average Wages, Average Education, Average

Experience and Average Age Between Non-Supervisory Construction Workers Who Use Computer at Work and Workers Who Do Not. *p > 0.05 (Data Source: CPS 2001 Supplement for Computer and Internet Usage)

286
Generating and Maintaining Activity-based Cost Estimates

with Feature-Based Product Models

by

Sheryl Staub-French' and Martin Fischer

ABSTRACT

Understanding how the building design influences construction costs is a challenging task for

estimators. Estimators must recognize the design conditions that affect construction costs and

customize the cost estimate accordingly. Estimators have different preferences for how and when to adjust a project's activities, resources, and resource productivity rates that form the basis of a cost

estimate. Current tools and methodologies lack ways to help estimators customize constmction cost information according to their preferences and maintain cost estimates as the design changes based on

those preferences. This paper describes the activity-based cost estimating process we formalized to help estimators customize a project's activities, resources, and resource productivity rates based on

their preferences and the particular features in a given product model. We implemented and tested the

process in a prototype called Activity-based Cost Estimating (ACE). ACE creates a set of projectspecific activities that know why they are needed in the cost estimate, what feature requires their execution, what resources are executing the activity and why, and what their labor and material costs

are. Our tests show that ACE helps estimators to generate and maintain cost estimates more

completely, consistently, and quickly than state-of-the-art cost estimating software.

KEYWORDS: Cost Estimating; Information Technology; Construction; Product Features

1. C^TTRODUCTION

It is the cost estimator's task to determine how

a building design influences construction costs. Estimators must determine what design

conditions are important (i.e., incur a cost),

when they are important, and how they affect construction costs when creating cost

estimates. Construction cost estimates are used to assist designers, owners, and builders

of facilities in resolving a variety of decisions,

such as evaluating the cost of different design

alternatives, budgeting construction costs, and

establishing the cost impact of design changes.

Consequently, it is critical that cost estimators

provide detailed and accurate cost estimates in a timely manner to support project teams in making these different decisions.

Estimators using state-of-the-art estimating

software can establish a relationship between a component in a product model and a cost item

in a cost-estimating database when creating a

cost estimate (Timberline 2001). These

relationships help estimators to take off

quantities automatically by representing the

component properties that affect construction

costs. However, this representation is incomplete because it does not represent the

estimator's rationale for how the component

properties affect specific cost information, and

it does not represent other design conditions

and their impact on a component's cost. Consequently, generating and maintaining cost estimates today is a largely manual, error- prone, and time-consuming process.

This paper describes the formalization of an

activity-based cost estimating process that leverages the rich representation of standard

product models to help estimators generate and

maintain construction cost estimates. This

research is based on a completed research

project and was motivated by our experiences

with state-of-the-art integrated estimating

software on real projects. This work addresses

' Assistant Professor, Department of Civil Engineering, University of British Columbia, 2324 Main Mall,

Vancouver, BC, Canada, V6T 1Z4. Voice: 604-827-5 118, Fax: 604-822-6901 . shervlsf@civil.ubc.ca.

" Associate Professor, Department of Civil and Environmental Engineering and (by Courtesy) Computer

Science, Director, Center for Integrated Facility Engineering, Terman Engineering Center, Room 292, Stanford

University, Stanford, CA 94305-4020. Voice: 650-725-4649, Fax: 650-725-6014, fischer@stanfoi-d.edu.

287
conference themes related to computer

integrated building processes and construction

process modeling and simulation.

2. CASE STUDY

This section describes a case study to illustrate the requirements for automated support of the cost estimating process. The case study is based on a drywall estimator's process for

estimating the labor costs for one of the rooms

in an office project shown in Figure 1. Figure

2 shows an estimator's rationale for adjusting

the activities, resources, and resource

productivity rates to account for the cost impacts of specific design conditions.

The case study demonstrates that there are

different types of design conditions that affect construction costs. Design conditions can be

based on properties of components (e.g., the

'curvature' of the wall), intersections of

components (e.g., the 'structural penetration'

resulting from the intersection of the wall and

beam), and groupings of components (e.g., the

'grouping of walls' based on component

similarity). The case study also demonstrates

that design conditions can affect construction

costs in different ways. Design conditions can

affect the requirement for activities (e.g., the

'structural penetration' requires the activity

Apply Caulk), design conditions can affect when a resource is appropriate in an activity

(e.g., the height of the wall affects the need for

Rolling Scaffolding), and design conditions can affect a resource's ability to execute an

activity effectively (e.g., the similarity of the

walls leads to an increase in crew

productivity).

Estimators using state-of-the-art cost estimating software cannot represent many of

the design conditions that affect construction

costs (e.g., structural penetrations and

component similarity). Furthermore,

estimators using state-of-the-art cost estimating software cannot explicitly represent

the specific cost information affected and the

way it is affected by different design

conditions (e.g., resource use or execution).

Consequently, estimators have to manually

identify most design conditions and manually

adjust the project's activities and resources

accordingly. For a large project, it is typically too time-consuming to make these projectspecific adjustments manually for all the

different design conditions in a given product

model. Consequently, estimators often employ

ad hoc methods (e.g., adjusting the crew

productivity rates of all the "Install Metal

Studs" activities to account for one wall's

curvature) and overlook the cost impact of

different design conditions (e.g., overlook cost impacts resulting from openings). Moreover,

estimators often do not have the time to provide specific feedback to designers on the cost implications of their design decisions

(e.g., the cost implications of a specific wall

height). The lack of a formal process and

automated support leads to inconsistencies and

inefficiencies in the cost estimating process

and resulting cost estimate, and limits the

ability of estimators to help designers develop

cost-effective designs.

3. GENERATING AND MAINTAINING

COST ESTIMATES USING ACE

The activity-based cost estimating process we

formalized helps estimators to generate and

maintain cost estimates quickly and

consistently based on the design conditions in a given product model. We implemented and

tested this process in a prototype called

Activity-based Cost Estimating (ACE). The

main challenges associated with providing

automated support of the cost estimating

process are that different design conditions

exist in any given product model, that different

design conditions affect construction costs in different ways, and that estimators have

different preferences for how and when to adjust construction costs to account for different design conditions.

We developed the activity-based cost estimating process by abstracting the design

conditions estimators consider and the

different ways estimators adjust activities and

resources to account for different design

conditions. We use features to describe the

specific part of the design that estimators care

about, design conditions to describe when

features are important to estimators, and

activities to describe how features impact

production and hence, construction cost. By

leveraging the activity-based cost estimating

process, ACE allows estimators to represent

their rationale for relating features of a building product model with construction

288
activities to enable automated support of the

cost estimating process.

Figure 3 shows the three different modules of

the activity-based cost estimating process:

(1) Instantiate Features: Identify the relevant

cost-driving features in the input product

model and instantiate the features to create an

estimator-focused feature-based product

model.

(2) Customize Activities and Resources:

Customize the activities and resources for each

component being estimated based on the

estimator's rationale and the particular features

in the estimator-focused feature-based product

model.

(3) Generate and Maintain Construction

Costs: Calculate each activity's quantities and

duration to determine the activity's cost. If the

estimate is based on a revised design, identify

the cost information affected and reconcile the

activities and resources so that the design and

estimate remain in balance. The output of this process is a set of resource-loaded and cost- loaded activities that are explicitly related to the features in the input product model.

3.1 Ml: Instantiate Features

The motivating case shows that different types

of design conditions affect construction costs. Estimators consider properties of components,

intersections of components, and groupings of

components when creating cost estimates. The

purpose of the first module is to transform

designer-focused product models into feature- based product models that support cost estimating. The input product model is represented using the industry standard

Industry Foundation Classes (IFC) (lAI 2001).

ACE identifies the cost-driving features in the

input IFC-based product model to create an

estimator-focused feature-based product

model.

The IFC's explicitly represent components,

attributes of components, and relationships

between components in building product

models (lAI 2001). However, they do not

explicitly represent many of the design

conditions that affect construction costs, such

as penetrations and component similarity. We

use features to represent the design conditions

that are important to cost estimators of

building constmction. Product features are

used extensively in manufacturing to describe

the geometric forms or entities in a product

model that are important in some aspect of the

manufacturing process (Cunningham and

Dixon 1988). However, the feature

representations developed in the

manufacturing industry do not fully support

the representation of building product models.

Specifically, building product models contain

different features and different types of

products. Our research applies the

manufacturing concept of features to building

construction and extends it to represent the

features that are useful to cost estimators.

We modeled three different types of features in

this research: (1) component features (e.g.,

'walls'), (2) intersection features (e.g., 'structural penetrations'), and (3) macro

features (e.g., 'groupings of components based on similarity'). We formalized a feature

ontology that represents the different attributes of each feature type and enables estimators to represent feature instances according to their

preferences (Staub-French 2002). The feature

ontology provides the map to relate an IFCbased product model to an estimator-focused

product model. We represent features in a project-independent way so that they can be

reused from project to project to identify the

relevant features given an IFC-based product

model.

ACE leverages the feature ontology to provide

a framework for estimators to represent their

preferences for naming features, specifying

relevant component intersections, defining

component similarity, and specifying the

features that affect a specific component's

construction costs. For example, the estimator

from the motivating case can represent the

"structural penetration" as a feature that results from the intersection of 'walls' and 'beams,'

and specify that this feature is important for

constructing 'walls.' ACE analyzes the

geometry and topological relationships

between the components in the input IFCbased product model to identify the cost- driving features specified by the estimator.

Hence, ACE enriches current standard building

product models by representing the features of

building product models that affect construction costs.

289
3.2 M2: Customize Activities and Resources

The case study shows that estimators adjust the

project's activities, resources, and resource

productivity rates to account for the cost impact of different features. The purpose of

the second module is to help estimators

customize the activities and resources in a cost estimate according to their preferences based on the specific features in a given product

model.

Prior research efforts demonstrate that cost estimates can be generated directly from 3D

models (Laitinen 1998; Aouad et al. 1994;

Aouad et al. 1997, Staub-French and Fischer

2001). However, these research efforts do not customize construction cost information for

specific design conditions in a given product

model, and they do not account for different

estimator preferences. Other research efforts recognize design conditions that affect construction costs and customize the activity's resources and resource productivity rates accordingly (Fischer 1991; Thomas and

Zavrski 2000; Hanna et al. 1992). However,

these research efforts do not represent and

account for different estimator preferences

when customizing the project's resources and

resource productivity rates to the design

conditions in a particular product model.

We abstracted the common attributes of

estimators' rationale for how and when

different design conditions affect construction

costs and developed templates to capture this estimating knowledge from estimators (StaubFrench 2002). The templates allow estimators

to specify the features that affect activities (Activity Specification templates) and the

features that affect resources (Resource

Specification templates). The templates

provide a structured way for estimators to represent the specific impact different features

have on a project's activities and resources. Estimators input their rationale once in the

Activity and Resource Specification templates

and ACE reuses this knowledge from project

to project when generating and maintaining

cost estimates.

In ACE, we implemented a formal process that automatically customizes activities and

resources when generating and maintaining

cost estimates for estimator-focused featurebased product models (Staub-French 2002).

For each feature in the input product model,

ACE identifies the relevant Activity

Specifications and adds the specified activity

to the estimate. Then, ACE assigns resources

to the activities and adjusts the resources' productivity rates according to the estimator's

preferences in Resource Specifications and

based on the specific features in the feature- based product model. The output of the

second module is a set of project-specific

resource-loaded activities that are explicitly related to the estimator-focused feature-based

product model and the estimator's rationale.

3.3 M3: Generate and Maintain

Construction Costs

The purpose of the third module is to generate

and maintain construction costs given the input

resource-loaded activities and related features. Calculating the construction costs for resource- loaded activities is a straightforward process. However, the explicit relationships between

features, activities, resources, costs, and the

estimator's rationale in Activity and Resource

Specifications enable the maintenance of cost estimates if the design changes.

Many research efforts have developed

computer tools that automatically generate the

project-specific relationships between

components, activities, resources, and costs (Laitinen 1998; Aouad et al. 1994; Aouad et al. 1997; Froese 1992). However, they do not

represent why components, activities, resources, and costs are related and when the

relationships are needed.

Our research extends existing formalisms of

construction processes that define activities as objects <0>, actions <A>, and resources <R>

(Darwiche et al. 1988; Aalami 1998). Our

research extends this formalism by generating

activities that also know what feature <F>

requires the activity's execution and how much

the activity costs <C> to create an integrated

<FOARC> model consisting of activities that explicitly relate features, objects, actions, resources, and costs.

Each activity generated by ACE knows what

feature requires its execution, the material and

resource cost implications of the activity, the

estimator's rationale for adding the activity.

290
what resources are executing the activity and

why, and how particular features affect the resources" productivity rate. Consequently,

ACE can help estimators to identify the cost information affected by design changes and

calculate the corresponding cost impact of

design changes. Our tests show that the cost estimating process implemented in ACE and

the resulting integrated <FOARC> model

enables estimators to generate and maintain

construction cost estimates from feature-based

product models more completely (i.e., less ad

hoc and with fewer omissions), consistently,

and quickly (Staub-French 2002).

4. CONCLUSIONS

This paper described an activity-based cost estimating process that creates an integrated

model consisting of activities that explicitly

relate features, objects, actions, resources, and

costs, and the estimator's rationale for relating

this information. This process helps estimators

to generate and maintain construction cost estimates and avoid ad hoc and error-prone

methods that lead to inconsistencies and

inefficiencies in the cost estimating process.

The formalisms developed and implemented in ACE take an essential step toward creating

software tools that can help project teams to maintain integrated models of a project's scope, schedule, and cost. Understanding the

relationships between this information is critical to managing the design and

construction process. Future research

directions should address other types of

features and factors exogenous to product

design, such as site characteristics and resource

skill and availabihty.

5. REFERENCES

Aalami, F. (1998). "Using Method Models to Generate 4D Production Models," PhD Thesis,

Stanford University, Stanford.

Aouad, G., Belts, M., Brandon, P., Brown, F., Child, T., Cooper, G., Ford, S., Kirkham, J., Oxma, R., Sarshar, M., and Young, B. (1994).

"ICON: Integration of Construction

Information." Department of Surveying and

Information Technology Institute, University

of Salford, Salford.

Aouad, G., Child, T., Marir, F., and Brandon,

P. (1997). "Open Systems for Construction

(OSCON), draft industry report." Department

of Surveying, University of Salford, Salford.

Cunningham, J.J. and Dixon, J.R. (1988).

"Designing with Features: The Origin of

Features," ASME Computers in Engineering

Conference, San Francisco, CA, Aug. 1988,

237-243.

Darwiche, A., Levitt, R., and Hayes-Roth, B.

(1989). "OARPLAN: Generating Project

Plans by Reasoning about Objects, Actions and

Resources." AI EDAM, 2(3), 169-181.

Fischer, M. (1991). "Constructibility Input to Preliminary Design of Reinforced Concrete

Structures." Technical Report 64, Center for

Integrated Facility Engineering, Stanford.

Froese, T. M. (1992). "Integrated ComputerAided Project Management Through Standard

Object-Oriented Models." PhD Thesis,

Stanford University, Stanford.

Hanna, A. S., Willenbrock, J.H., and Sanvido,

V. E. (1992). "Knowledge Acquisition and

Development for Formwork Selection

System." Journal of Construction Engineering

and Management, ASCE, 118(1), 179-198.

International Alliance of Interoperability (lAI)

(2001). "IFC 2x Extension Modeling Guide",

Available from http://www.iai.org.uk.

Laitinen, J. (1998). "Model Based

Construction Process Management." PhD

Thesis, Royal Institute of Technology.

Stockholm, Sweden.

Staub-French, S., and Fischer, M. (2001).

"Industrial Case Study of Electronic Design,

Cost, and Schedule Integration." Technical

Report 122, Center for Integrated Facility

Engineering, Stanford.

Staub-French, Sheryl (2002) "Feature-Driven

Activity-based Cost Estimating." PhD Thesis,

Stanford University, Stanford.

Thomas, H.R. and Zavrski, I. (1999).

"Construction Baseline Productivity: Theory

and Practice." Journal of Construction

291
Engineering and Management, American

Society of Civil Engineers, 125(5), 295-303.

Timberline Software Company (2001).

Precision Estimating Extended and CAD

Integrator, Users Documentation, Beaverton,

Oregon.

Co\urr\n^Exist^ Beam (Existing)

\Wal Door and Window

Figure 1. Building

project case study.

components in the office

Relevant Design Conditions Estimator's Rationale

^Curved Wall

Reduces the crew

productivity rate for all the

"Install Metal Studs"

activities.

rl ' . V\Wall Height

Uses Rolling Scaffolding and

reduces crew productiivty in the "Install Metal Studs"

activity if the wall height is between 9' - 13'.

Structural Penetration Adds activity "Frame

Penetration" to account for the additional labor costs for the unusual framing

condition. Adds activity "Apply Caulk" If the

intersected wall is fire-rated.

Component Similarity

If most of the walls have the same height, increases the crew productivity for the

"Install Metal Studs" activity

L, , 000/ by 20%.

Figure 2. Estimators' rationale for adjusting the

activities, resources, and resources' productivity

rates to reflect the cost impact of specific design

conditions in the cost estimate.

Features

IFC-Based _

Product Model

Estimator-focused Feature-based Product Model

Identify Features!

Instantiate Features!

Activity and Resource

Specifications

Customize

Activities and

Resources

IVI2 Resource-loaded

Activities &

Related Features

Generic Project

Activities & Cost

Resources, Estimates

Analyze Activity Specifications!

Instantiate Activities! Analyze Resource Specifications! Assign Resources to Activities! Adjust Resource Productivity Rates!

Generate and

Maintain Construction Costs M3

Resource-loaded and Cost-loaded — Activities &

Related Features

Calculate Quantities and Resource Durations! Calculate Costs! Reconcile Costs (if design changes)! Figure 3. The three steps of the activity-based cost estimating process to (1) create an estimatorfocused feature-based product model, (2) customize the activities and resources based on the

estimator's rationale in Activity and Resource Specifications, and (3) create resource-loaded and cost- loaded activities that are related to the features in the estimator-focused feature-based product model.

292
Construction Zone Generation Mechanisms and Applications

RagipAkbas Martin Fischer

Stanford University Stanford University

Centerfor Integrated Facility Engineering Construction Engineering and Management Program,

M:4020, Stanford, CA, USA 94305-4020 Terman Engineering Center, Room 292

Stanford, CA, USA 94305-4020

rakbas@stanford.edu fischer@stanford.edu

Abstract. Construction zones are geometric units of work in the construction planning process. Using construction

parameters and geometric properties, construction zone generation mechanisms change the level of detail of the 3D

geometry and corresponding activities of the planned project. We have defined and implemented a set of

mechanisms for construction zone generation. Decomposition provides various ways to generate detailed zones, while aggregation generates combined zones. To support these mechanisms, we have formalized a geometric

representation based on triangular meshes that can represent the activity workflow, project spatial hierarchy, local variations in productivity, and activity state information on a component at any given time. This paper summarizes

the mechanisms and describes various planning/scheduhng appUcations of these mechanisms, such as rapid plan

evaluation, resource and workflow balancing in 3D, and association of schedules at multiple levels of detail. Our

contributions are the formahzation of these zoning mechanisms, representation and algorithms to support these mechanisms, and planning/balancing methods utiUzing the mechanisms.

Keywords: construction planning; geometric algorithms; construction zones; line-of-balance techniques

1. INTRODUCTION

Today, it is difficult for construction superintendents

and schedulers to consider and communicate

alternative plans even with the existence of 3D

models. There is also a gap between the techniques

for high-level planning/scheduling and detailed

operations level planning from research and practical

perspectives. We designed construction zone

generation mechanisms to address these problems.

Where and when an activity is ongoing is crucial

knowledge that relates different sources of

information. Scheduling at a more detailed level can

decrease activity duration and increase the reliability

in the construction schedules. Relating high-level

and detailed schedules can prevent common

inconsistencies between schedules at different

granularity.

One of our goals is to make effective use of

geometric models, extending existing techniques in computer graphics to build a general computational

structure for construction planning. We want to make the geometry details transparent to the planner,

capturing the reasons for planning as parameters in zoning mechanisms. Then, changing these

parameters, planners can easily try different

scenarios with different crews and methods and

different workflow parameters.

1.1 Previous Work

We define construction zones as the geometric units

of work in the construction planning process. A

construction zone can be a part of a component, a component, a group of components or a volume.

We refer to the process of changing the level of

detail of the building geometry and activities as zone

generation. Previous zone generation approaches are mostly for automated planning and use user-defined

volumetric elements. Their purpose is to simplify the

automated planning process by creating subnetworks of activities and constraints within zones and combining them to generate the final plan.

293
Thabet and Beliveau [5] define zones for

aggregating components using a hierarchy of boxes.

The ZonePlanner research [6] uses volumetric grids

to search for an optimal zoning plan. These systems

do not address crucial knowledge of planners related

to workflow, arrangement of work areas, and

changes in production rates due to various factors. None of these systems analyze and make use of

complex geometry. They suffer from the necessity to define building blocks for each case a priori and

from the combinatorial complexity to try all possible

merging alternatives.

Riley and Sanvido [3], in their research for space

planning in multistory buildings, define work-area

patterns to describe the directions for and locations

of units of work completed for different activities and materials. However, they don't represent the

patterns computationally. We provide a computational method for supporting similar

patterns of construction on 3D models.

4D CAD, in its simplest form, is the ability to visualize the state of construction at any given

project time. It uses the association of the building

elements with the activities required to construct them. Therefore, every component has time

attributes. We extend that to every polygon on the

geometry. Therefore, every location on the geometry

can support different time parameters.

1.2 Terminology

We represent a building element by association of

semantic product information with geometry, similar

to many product modeling approaches [1]. We use

the term building element synonymously with an

assembly, e.g., a stud wall, concrete slab, roof. Building elements or assemblies are organized in a

spatial or organizational hierarchy, a tree, where

only the leaf nodes can contain the actual

components (Figure 1). An assembly is composed of one or more of its components or constituents. For

example, components for a stud wall assembly are

studs, dry wall, insulation, etc. Each component can have different partitions representing zones, the

smallest possible partition being the unit size of that component. Each assembly has a type, e.g., floor

slab. By the same token, each activity has an activity

type, e.g., pour concrete.

There is no single correct spatial level of detail for

building elements. For example, either the whole

floor slab or part of this slab enclosed by a room can

be a building element with different granularity.

Similarly, the activity required to construct it can be

for the whole slab or the slab bounded by the room. We distinguish between three main component

categories for zone generation purposes:

prefabricated, fixed size site-assembly and

continuous site-assembly. Prefabricated components

are installed as a single step. Therefore, the

component and the assembly are the same, and they

cannot be partitioned. Fixed-size site-assembly

components require on-site installation, are formed

of well-defined units of work, and one or more

different activities are necessary for their construction, e.g. stud walls or roofing. Continuous

site-assembly components are either not formed of

unit size elements or the elements are negligible in

size, such as reinforced-concrete components.

In the rest of the paper we will first explain the

zoning mechanisms and the required geometric

representation for them. Then, we will focus on

different applications using these mechanisms in areas where traditional planning and scheduling

techniques are limited.

2. ZONE GENERATION APPROACH

2. 1 Mechanisms

We have abstracted the common level of detail changes during the construction planning/scheduling

process using a well-defined set of zoning

mechanisms, which act on components and

activities. Zoning mechanisms essentially describe

planning and geometric parameters for how

activities are installed. They are powerful in replicating the construction planner/scheduler's

intent and support what-if analyses and

visualization. They are also designed to be general

and extensible. We have two main categories of

mechanisms for zone generation: decomposition and

aggregation. An intuitive way to think about these

mechanisms is: decomposition creates and maintains zones formed by a part of a component, aggregation

creates and maintains zones consisting of a group of

components.

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2.1.1 Decomposition

This mechanism generates detailed construction zones on components and detailed activities for the zones, thereby increasing the level of detail of the

existing models. The operation for decomposition is Decompose(c, a, t, D, F), where

c: component to be decomposed,

a: activity to be decomposed,

f: type of decomposition, one of (grid, production), D: direction set, which contains, in the case of grid

decomposition, a direction vector and amount of

decomposition in each direction. For productionbased decomposition, the direction set is the starting

location and a set of unit direction vectors at specified locations,

F: factor set, which contains the shape factor

functions and parameters and time-space functions

as explained in section 2.3.

After the decomposition, the application generates a

set of subcomponents and subactivities and links

them to each other. The geometric representation for each subcomponent is a partition of the geometry for

the original component. Each subactivity is a result of splitting the original activity.

2.1.2 Aggregation

This mechanism groups components and sets the

start and finish dates by associating detailed

activities with the new group of components. Its types range from organizing the components within

a region to ordering the activities necessary for their

construction. It supports, for example, ordering of

exterior walls given the starting location and

direction.

The operation is Aggregateinode, a, t, D, F), where

node is a node in the product hierarchy, t is the type

of aggregation, D is the direction set, and F is the

factor set. Note that Aggregate is different from the

Union operator from solid modeling, in that its purpose is not to combine the geometry of individual

components. Furthermore, Aggregate is not the

inverse operator of Decompose.

2.2 Geometric representation for the mechanisms

Since the zoning mechanisms act on the geometry,

geometric representation and algorithms are an

important part of this research. We use triangle

meshes for the geometric representation.

Geometrically, a triangle mesh is a surface

consisting of triangular faces pasted together along

their edges. The mesh geometry can be denoted by a

tuple M = (K, V), where K specifies the connectivity

of the mesh (the adjacency of the vertices, edges,

and faces) and V is the set of vertex locations

defining the shape of the mesh in R\ The vertex

locations and the connectivity for the mesh can be

acquired from any 3D CAD or modeling application.

We can also build the connectivity for the faces

using common computer graphics techniques.

Triangle mesh is a common and well-researched

representation. However, as it is, it lacks the

construction domain information needed to support

the zoning mechanisms. We have extended the mesh

representation to a tuple M = (K, V, D, S), where D

is local direction of workflow and production

modifier at any location on a component, and S is the state of the component location as a function of

time. D is associated with a (vertex, activity) pair,

while the state S is associated with the faces (Figure

2c). These main extensions are as follows:

• Every vertex on the mesh contains a unit

direction vector for each related activity to describe the local direction of workflow at that location.

• Every vertex on the mesh contains a productivity

modifier for all related activities, Pk €[0,1].

Originally, modifiers on all vertices are 1, meaning the activity production rate at the given

location is equal to the production capacity.

• Every triangle contains a local activity state to represent the installation status at any given

time. We created an activity state machine to unambiguously calculate the local activity states as a result of the zone generation mechanisms.

2.3 Production Rate Modifiers

The production rate is not always constant for

activities anywhere on a component. We support

variable local production rates using the productivity

modifiers using the parameters stored with the

geometry. The modifier can be a combination of the

effects of the component's shape on the production

rate (shape factors), effects of other ongoing

activities [time-space factors), or other effects that

295
we did not consider so far in our research (learning curve, availability of resources, etc.).

The application calculates the production rate value

using the user-supplied functions and the shape

representation. Shape functions are dependent on

geometric parameters including height, distance to edge, and slope. Schedulers declare how production

rates are affected by these parameters so that the

software can calculate the local production rates. Time-space factors can decrease the production rate

if two close activities are installed at the same time

in the schedule. They can also stop an activity if a

prerequisite component is not ready.

2.4 Spatial Structures We use various spatial structures to aid the

mechanisms. A region is a bounded volume, which

encloses all the components that fall into it. Examples of regions for construction projects are a

floor, a room, or a quadrant. We support a

hierarchical region structure that is user defined and

unique for a project. Other spatial structures we use

are octrees for spatial search and grids for

arrangements of some mechanisms.

3. APPLICATIONS

We now will use the defined mechanisms together

with the geometric representation to show

approaches to common construction planningscheduling problems. Starting with plan evaluation on the simplest, single building element case, we

will extend the application to multiple building

elements at variable levels of detail. Building on the

common line-of-balance convention of continuous

utilization of resources, we will describe a

hierarchical 3D scheduling approach using the

zoning mechanisms. Then, we will consider

extensions to the architecture, such as keeping an

operational schedule synchronized with the master

schedule, and defining construction method-specific zones using the mechanisms.

3.1 Rapid plan evaluation

This application is a direct consequence of the

described mechanisms and the representation. Users can consider planning alternatives quickly by

changing the direction of workflow, starting

location, production rate and the sequence for the

activities. The application uses the parameters in the

mechanisms to traverse the geometry and generate

the states for any location at any time.

We have a prototype application that allows the user

to enter the parameters for the mechanisms, which

become input for the actual mechanisms. Let's say

the user wants to plan the pour for the slab in Figure

1. The user interactively defines how it will be

constructed in the application, in this case specifying

the direction of flow vector and amount (Figure 2a),

which in turn generates the following mechanism:

Decom;?05e(Floor2slab,Pour_noor2slab, grid, D, F)

Note that if the user changes the direction of the

activity or the amount of decomposition, only the

directional information, D, changes from the initial parameters. The user can immediately visualize the

effect of this change. If the user wanted to perform

this plan evaluation manually, he would need to (1)

modify the 3D model to split the geometry, (2) split

the construction activities into subactivities, and (3)

re-link them. Any other change requires the

repetition of this tedious process.

For the columns over the slabs, the zones are groups

of columns (Figure 2b). The mechanism is:

Aggregate{¥2Co\uvan%, Rebar_F2Columns, production,

(A-1,(-1,0,0)),F)

Obviously, construction projects are composed of

many activities and components, and considering

activities in isolation is not very valuable. The user can also decompose the same slab for the other

associated activities, such as rebar and form by

applying decompose mechanisms for each. In that case, different activities on the same component

should follow each other without interference. The

activity state machine guarantees that the activities do not violate their predefined ordering, i.e., the

prerequisite activity is always installed before, and

there are no two activities installed at the same

location at the same time. The mechanisms are also

applicable to more complex structures. Figure 3

shows production-based decomposition applied to an

exterior enclosure element. The user specifies the

starting location, direction of workflow, and effect of shape on production rate for different activity

types required to construct the enclosure.

296
The following application focuses on the interactions

of multiple activities on multiple building elements

considering resources, providing an alternative

scheduling approach when 3D models are available.

3.2 3D schedule balancing

Traditionally, line-of-balance (LOB) or linear

scheduling techniques are used for activities following each other for linear or repetitive work,

allowing planners to balance workflow by adjusting

the production rates and start dates for activities [4]. They help plan for continuous utilization of

resources. However, these methods are limited to fixed single level work areas corresponding to the

flow. Activities in linear scheduling techniques

should either be repetitive units or proceed linearly

in a single axis-aligned direction - horizontal or

vertical. To plan using LOB, the project is divided

into planning units usually as large work areas. Although multiple activities can concurrently act on

the same work area, LOB conservatively limits a

single activity in the same work area at a time.

Our application extends these valuable techniques to many types of construction activities using the

spatial and planning information and benefiting from

the same zoning mechanisms explained in the

previous application. It adds the ability to schedule

at multiple levels and supports multiple activities on

a component and complex shapes. The balancing

process can range from single element/single region

i to hierarchical/multiple regions.

3.3 Maintaining master and operational schedules

synchronously

The previous application examples ignored

maintaining the level-of-detail relationships with the

activities in the existing master schedule. Master

schedules are the means for tracking resources and

activities for construction projects. Detailed planning

with zoning mechanisms and actual detailed site data

adds valuable input to the schedule. Project

scheduling software [2] provide hammock or summary activity types to summarize a group of

activities. However, this relationship is error-prone

and limited.

We associate the original activities with the

activities resulting from the zoning mechanisms

through the associated project locations. Whenever

the activity date and duration are modified at a more

detailed level, the activities in the master schedule can be updated. Similarly, users can propagate the

effect of changes in the master schedule to the

detailed schedules. This also allows the construction

process visualization at two levels of detail.

3.4 Method changes on component

In all of the previous examples, the generated zones

correspond to some planning units of work. Zones

can also support changes in construction methods on

a single component. Construction methods can vary

because of geometric factors such as height and

slope or existence of nearby components, such as scaffolding. We support ways to generate separate zones on building elements in such cases.

4. CONCLUSIONS

In this paper, we have briefly described construction

zoning mechanisms and explained interactive

planning/scheduling applications. We are validating

the research by replicating the manual operation

plans on several projects via the zoning mechanisms.

The tested activity types include concrete pour

schedules, exterior enclosure and roofing.

Zoning mechanisms assume an activity proceeds in a connected way and make a surface approximation

for component geometry. Additionally, we use linear

shape and time-space functions.

These mechanisms provide the possibility of many

other types of visualization, analysis and

optimization. Another important use is data

collection by reverse-engineering the actual

construction dates to infer the planning parameters.

A space planning methodology can be adopted for

the 3D balancing application to check for other types

of spatial conflicts. Furthermore, functions to generate the temporary structures such as laydown,

scaffolding and formwork on the fly can increase the

value of this research.

5. REFERENCES:

1. lAI. 2001. Industry Foundation Classes - Release 2.x Specifications.

297
2. Primavera. 2000. Primavera Project Planner.

Primavera Systems, Inc., Bala Cynwyd, PA.

3. Riley, D. R. and Sanvido, V. E. 1995. 'Patterns of Construction-Space in Multistory Buildings',

Journal of Construction Engineering and

Management, Vol. 121, no. 4, pp. 464-473.

4. Stradal, O. and Cacha, J. 1982. 'Time Space

Scheduling Method.' Journal ofConstruction

Division, Vol. 108, no. 3, pp. 445-457.

5. Thabet, W. Y. and Beliveau, Y. J. 1997.

'SCaRC: Space-Constrained ResourceConstrained scheduling system', Journal of

Computing in Civil Engineering, Vol. 2, no. 1, pp. 48-59.

6. Winstanley, G. and Hoshi, K. 1993. 'Activity

Aggregation in Model-Based AI Plannmg

Systems', /. Journal of Artificial Intelligence in Engineering Design, Analysis and Manufacture

(AI EDAM), Vol. 7, No.3, pp 209-228.

^gj I Building

Floor!

-| Columns |

-| ColumnA-1

'—1 CoIumnA-2

H Slabs 1

Figure 1. Representation basics for the sample model, (a) Partial product composition hierarchy, (b) Partial 3D

isometric view, (c) Triangle mesh representation for the slab including the extensions.

Decompose

(b)

Aggregate

'I

Pour Slab Pour Slab_1 ^ Pour Slab_2

I 1 Pour Slab_3 C=3 Pour Slab 4

RebarCoiumnA-1

Rebar ColumnA-1_1 =1 Rebar ColumnA-1_2

I 1 Rebar ColumnA-1 3

Figure 2. Examples of mechanisms. Decomposition splits the geometric representation to correspond to the

units of work for pour_slab. Aggregation groups the concrete columns for install_rebar in this example.

Figure 3. Zoning mechanisms applied to a complex exterior enclosure surface, (a) Original model, (b) Direction

of workflow interpolated over the surface visualized by arrows and colors, (c) Height factor calculated on the

surface, (d) Snapshot of 4D model after the mechanism is applied.

298
ASSEMBLY + DISASSEMBLY OF INTERIOR WALL

by

Dipl-Eng. Albrecht Hanser

Technical University Munich, chair of building realization + -informatics,

Prof. T. Bock Arcisstrasse 21, D 80333 Miinchen,

albrecht.hanser@bri.ar.tum.de

Abstract: Flexible extension walls - watched on a long-term-use - have lower costs and are more economical and especially more variable compared to convenient post-and- beamstructures. Because room requirements - mainly in office and administration building -

change faster and faster, an extensive potential on future markets for these technologies exists

Keywords: Flexibility, Economic Efficiency, Non-supporting removable wall-unity, Mediaand electric wiring, Put-and-sUde-technology, Relocate systems. Cost, Different Elements,

1 INTRODUCTION

Flexibility

A higher and higher flexibility of the floor

plan is expected in office- and commercial

building as in house building. The change of

users or function often results in the wish

redesigning the existing spatial pattern. A

basic floor plan flexibility often is possible and

practiced by dividing the load-bearing building

surface from non-structural separation walls

and ceilings. A well known system of this type

of walls is a wooden or metal post-and-beamstructure with mineral fibre filling and

plasterboard panelling.

By using this building system it is difficult to realize variations of different room structures and subdivisions by self building. In fact they

are cheap to produce and to install but in the

end they are much fuss in redesigning, few

flexible and actually not reusable. In addition

there are already reusable, demountable

partition systems available. However they

usually are to expensive and to much fuss to

con.struct.

Economic Efficiency

All partners in construction business know

exactly what construction cost mean. Very

often we think and act only in this kind of

category.

The reason for this understanding is the

existence of two different budgets; one for

construction and a second for consequential

costs during life cycle, which are even managed by two teams. Feedback between the

two will almost not occur. So at the end in a

life cycle of a building, nobody is able to find out the real cost situation which has been

followed after construction time, of a product

incorporated in the building. Even what the

savings could have been, we cannot find out,

in case we would have constructed in prefabricated and modular systems.

Indeed thinking in a complex overall view, we

are realizing where the advantages are for

prefabricated and relocate-partitions:

Connections with its components,

separations in floor- and ceiling-areas are

close in cost of these construction types.

The finishes of partition-walls, out of

gypsum board, assembled on site, have not

this standard of quality as industrial

prefabricated partitions. Prefabricated

partitions need no new coatings for 30

years, as conventional gypsum boards

need it all 5 years.

299
brick-wall

cost of relocation

Figure 1: interior walls: cost of investment and

relocation (1)

In case prefabricated partitions get

relocated, the difference in investment cost becomes obvious. A prefabricated partition occurs 40% of its former construction cost, while a conventional partition, which has

to be demolished and reconstructed almost

completely new, occurs 220% fit. It is beyond any doubt, the payout-return

depends on construction type of

prefabrication and the amount of

relocations.

Recovery and cleaning up belong to an

ecological and oeconomical overview; in

this context relocate systems offer

advantages. Savings of material and

avoidance of waste have no exceeding

fees for supervised dumps. These cost have been augmented constantly the last years.

2 AIM OF THE PROJECT

It was valid to develop a non-supporting

removable wall-unity, which allows adaptable,

fast and disassembling room-splitting.

Next to the standard components we have to develop elements for the connection at the

existing support structure, elements for

passages and doors, for windows on the inside

and other glazing structures.

Figure 2: First sketch (4)

Media- and electric wiring are components of

the removable wall-unity. The elements are delivered prefabricated and manageable on the

construction site. The connection to the available

supportstructure is created with a streching

mechanism (Justix); the coupling of the

elements and also the management of mediaand electric among each other works with a

put-and-slide-technology.

3 DEVELOPMENT

Demands to the system

"More than a wall", which means

integrated media, such as TV, phone, flat screen, switches, bus, safe, mini-bar,

shelf-systems, cupboards, etc completely

connected up;

Demountable and reusable and without

damaging the existing solid construction;

With finish-surface on both sides, in

complete lightweight construction;

For two persons to handle and to install Simple construction and long-term use

300
Located in price between the plaster board/

post-and-beam-structnres and the conventional wall systems.

"More than a wall"; beside separating for

offices, administration or housing the wall unit

is supposed to serve as room divider semi high

screen wall or fair stand. Put on wheels it can even become a mobile

office wall.

One of our aims is to see the wall not only as a separating element between two areas, but to include additional functions such as screens

lights, mini-bars, shelf-boards, integrated air- condition, etc; even PC or printer can be

hidden in the wall;

4 ELEMENTS

Surface finished, easy-to-handle modules are basic for interior wall surfaces. Elements are: Room-high elements (size depending on

height of the ceiling, standard sizes)

Door high elements ( height 210 cm)

End elements above door high elements

(size depending on height of the ceiling)

Elements for easy zoning, separating areas

(height 105 cm)

Special elements

5 CONSTRUCTION

The substructure for the single module is supposed to be a circulating frame. Panel

materials for wall surfaces like wooden

panels, plasterboards, glass etc. serve as frame

bracing.

Wooden profiles but also special formed plates can be the frame material.

The connection to the load bearing wall

construction and to the ceiling is designed as edging board.

The gap between the bottom of the wall an the

floor is covered by a clipped baseboard. A

dovetail-similar joint with integrated plugs for power and data supply connects the single

elements among one another and to the load

bearing walls. The single modules therefore are coupled by

Figure 3: Simulation of the elements (4)

fitting an pushing the connecting elements

301
The single modules therefore are coupledby

fitting an pushing the connecting elements

together. The stack design is variable.

Door high elements and end elements are connected in the same way. A special

processing of the frame profiles makes it possible to carry the prefabricated electronic

wires through the element.

The contact from element to element gets

possible through the just mentioned

connecting modules. The necessary fitting in to surround construction could be succeeded

by vertical adjustable foot construction. There

are two for each wall panel. After connecting

the elements the foot construction is screwed

up and pressed against a connecting profile.

The rising gap at the bottom of the wall can be

used for supplementary wires - especially for

wire systems, that can only be added

restrictively (phone, networks). A clipping

profile as baseboard covers the open bottom

area. There must be sound and fire technical measures on the surface, in the stack area as in

the base and ceiling area.

6 FABRICATING PROTOTYPES

There are running parallel extensive tests with

prototype wall modules to transfer the gained

knowledge practical.

supportconstruction

connector

electric wiring

f.e. gyp-board

[-

2 2A

1 ^--4 ^-4 ^-4

Figure 4: The elements; dimension: 90cm

wide, 300cm, 210cm, 90cm high; the

connecting system (4)

7 CONCLUSION

The system shown in this paper will find

place between the low cost but not

reusable gypsum board partition-walls and

the industrial prefabricated partitions,

which are very expensive. The

combination between a prefabricated high

tech system, affordable and economical,

usable as flexible elements for different

tasks are the main advantages of the new

system.

REFERENCES

(1) Studiengemeinschaft Fertigbau (1987).

Trennwandsysteme

(2) Tichelmann / Pfau (2000).

Entwicklungswandel Wohnungsbau, Vieweg,

Wiesbaden

(3) Diverse Herstellerunterlagen: Lindner,

Knauf, Item, Dorma, Hafele, Strahle, Hettich,

u.a.

(4) all figures: Technical University Munich,

chair of building realization; exept figure 1 which belongs to reference (1)

302
SESSION 6

FIELD SENSOR DATA AND

CONSTRUCTION PROCESS

INTEGRATION PROTOCOLS

303

STANDARDIZATION OF DATA FLOWS ON EARTHWORKS AND ROAD

PAVEMENT SITES USING INFORMATION SYSTEMS

by

Francois Peyret

ABSTRACT: The work described in this paper

is the follow-up of the first analysis presented

in the previous ISARC on the same theme. The

paper start by recalling the background with is the ISO TC-127 WG2 standardization initiative. Then he applies a basic logical model of site information system for civil-engineering sites to various existing or under development such

European systems (CIRC and OSYRIS) to identify and specify the main categories of

information flows that are worth to be

standardized. The paper ends with some

considerations about these categories and the

way to continue the work.

KEYWORDS: standardization, site information

systems, civil-engineering, computer integrated

construction, data flows.

1 INTRODUCTION

Still much time and money are lost all along

and between the various phases of construction,

due to the lack of information and the very poor

quality of the management of this information,

making very small use of the new available

Information Technology. Clearly, the new

challenge in the construction world is now the

information management.

Due to the presence, on more and more work

sites, of novel operator-aiding systems using

smart positioning and processing systems,

people have become aware of the value of all the relevant data that can be collected from such

systems, for instance for quality assessment and

relationships with the road owner. These data, that need to be exchanged between different

information and processing systems are really

valuable only if they are standardized

2 BACKGROUND

To address this issue, the ISO TC-127

standardization committee launched a new

working group, WG 2, focused on the scope of

Work site data controlled earth-moving

operation in October 2000. This group,

gathering experts from Japan, USA, France,

Germany, Sweden and Italy, already met 3

times, in Tokyo, Bologna and Denver and the

main decisions which came out from the

discussions are the followings:

to focus upon road construction works,

including earth moving operations and

pavement construction,

to start with the standardization of the

definition and content of the information

exchanged, then to study the format, then

the protocols,

to stay close to the site, and more precisely

to the machines itself, that is to say not to study, in a first step, the higher level exchange of information between road

authorities and the contractors. To structure its work, the WG decided to subdivide it into 3 projects: Terminology,

System Architecture and Data Dictionary, the

first two ones being under the responsibility of

Japanese experts, the third one of the French

experts, co-operating with the American ones. Terminology should set up the basis of common

understanding for all the work, System

Architecture should define how the data will be

handled in the various exchanges and Data

Dictionary should define what data should be

standardize and propose a common definition

and representation of them.

Site Robotics and Positioning Team, LCPC

(Laboratoire Central des Fonts et Chaussees),

Bouguenais, France, francois.peyret @Icpc. fr This paper presents mainly the work achieved

by LCPC, composing the French delegation,

about data identification and clustering for

305
preparing the work of establishing the relevant

data dictionary to be included in the tentative

standard.

3 THE LOGICAL MODEL

The paper presented at last ISARC in Warsaw

[1] already presented differences between

logical and physical modeling and explained

why we proposed to start the standardization

discussions at the logical level. This paper also

introduced the important concept of 'road

product model'. The core part of the paper was

the proposal of a logical model of a Site Information System which was based upon the

analysis of the functional design made for the

OSYRIS project [2]. A 'system' is a group of functions providing a

'service' (can be an action but generally a piece

of information) as answer to a 'demand' (always

a piece of information). Each system can be

decomposed into several sub-systems, thus

giving a fractal structure to the representation.

The logical model of our system is presented in Figure 1 , is composed of four main sub-systems

which play well-separated roles in the global

process: Temporary Data Storage, Data

Collection and Processing, Assist For

Operation and Work Execute systems.

missioi

Data CoHection and Processing (DCP)

Data collection lemporaryi

Data

Storage

., jC)pe2'ator

Work Executt

(WE)

Machine Tool management management

MotliOcatioK of tlse real world: aciioii of tise machiiie

Figure 1: The basic logical model

- The Site Information System (SIS) (formerly

called Data Operation System) means the

whole system itself which is managing

information to improve the quality of the work.

The SIS can be physically distributed at various

places, on the machines. It has generally one

'office' segment and one 'site' segment.

- The Work Execute (WE) sub-system is the part

of the SIS who is managing the machine and/or

the tool. It might not exist when the operator is steering manually.

- The Assist For Operation (AFO) sub-system,

which can also be called Execution

Management sub-system, is the sub-system

which is making the decisions for the execution

of the work, with or without the help of the

operator.

- The Temporary Data Storage (TDS) subsystem is in charge of storing all the temporary

data that important for the quality assessment,

before transmitting it to the external 'Permanent

Data Storage and Management System'.

- The Data Collection and Processing (DCP)

sub-system, is a composite and intermediate

system which is in charge of acquiring the

necessary data from the Real World or from the

TDS and in charge of processing them for the

other sub-systems. It also prepares the data for

visualization if necessary.

The human beings participating to the

execution, grouped into two classes: Manager

and Operator, are considered external to the

SIS, thus contributing essentially to the process. The machine itself, that is to say the piece of

equipment composed mainly of hardware but

also of software, under the form it is provided

by the manufacturer, is considered also external

to the SIS.

306
The data flows that are in the scope of the

standardization work are those exchanged

between: SIS and machinery. SIS and

measurement instruments , SIS and contractor or consuhant office .

4 DATA EXCHANGED BETWEEN THE

VARIOUS SUB-SYSTEMS.

4. 1 Analysis Of Existing Systems

To support our analysis, we studied carefully

the data flows existing in several SIS already

developed or under development. The SIS we

analyzed are dedicated to road pavement

construction, but we make the assumption that the results would be valid for earth moving sites too, with maybe some minor differences.

First, we considered the Computer Integrated

Road Construction [3] products, that is to say

the CIRCOM system, dedicated to the rollers,

and the CIRPAV system, dedicated to the pavers. CIRCOM

CIRCOM [4] is an operator-aiding system

which provides, through an accurate and

ergonomic display (colored map), to the

operator the position of its machines, its speed

and the already achieved number of passes. The

positioning component, called CIRCOM POS,

is a quite sophisticated one, using various

sensors, in particular a high-precision GPS. The

preparation of the mission and the transmission

of the design data are made on a computer

called CIRC GS (for Ground Station) and the

on-board processing is done by the CIRCOM

OB (for On-Board) computer.

The CIRCOM data flow analysis is presented on Figure 2.

Internal flows Real-time

Figure 2: The CIRCOM data flows

The first thing to remark about the CIRCOM

SIS is that the Work Execute sub-system (WE)

doesn't exist as the steering of the machine

remains manual, or can be considered as

external. The second point to notice is that the physical

'components' of the system are distributed

among the various logical sub-systems,

meaning that a physical component provides

generally different kind of services, from a

logical point of view (e.g. temporary storage,

intermediate data processing and display to the

operator for the on-board computer).

The data flows that are activated by the

operation of the system are of different kinds.

Some are 'internal', meaning that they should

remain proprietary and thus, are not to be

considered for standardization. Some are real- time and some are not. The important data

flows for standardization are those which are exchanged either between the SIS and external

systems or between sub-systems, when it is necessary. This has to be discussed case by

case.

1. Data exchanged between the SIS and external

systems :

307
design data (description of the road

geometry);

mission data (target number of passes and

target speed)

as-built data (compaction map showing the

actual achieve number of passes on the

road);

positioning data (plane position and speed),

from the positioning component, considered

external.

2. Data exchanged between sub-systems : we took into consideration what we called the

achieved surface data, that is to say the 'just

achieved' work of the roller that might be

interesting to transmit and to use in real-time.

This is justified for this kind of system because

these data have to be exchanged between the

different compactors and they might be

equipped with similar systems from different

manufacturers.

The achieved surface data are representing, in

the case of CIRCOM, the surface compacted by

the machine, to which is associated the speed

and the indication whether the roller is vibrating or not. More attributes about the compaction

energy of the machines can also be added:

amplitude, frequency, etc.

CIRPAV

CIRPAV [3] is a little more complicated since

it provides two main functions: assistance to the

driver for the steering of the machine, thanks to a color display similar to the CIRCOM's one, and automatic elevation control of the screed.

The positioning component, called CIRPAV

POS, can be based upon different technologies,

but has to provide both position and attitude of

the screed. The preparation of the mission and

the transmission of the design data are still made on the CIRC GS and the on-board

processing is done by the CIRPAV OB.

The CIRPAV data flow analysis is presented on

Figure 3.

Data collection

Data processing

Inform about work progress

Decision Create

, Tow points deviations Deviations of the left an<

IRFAV OU

MM-interface |

Pgeraior

command'r-j

Figure 3: The CIRPAV data flows

Most of the data flows are similar to the

CIRCOM's ones, albeit with a different content: design, as-built, mission, position, and achieved

surface data. The main difference is in a new data flow that is exchanged between AFO and WE (which exists

this time due to the automatic control ensured

by the CIRPAV SIS): the deviations between

the actual tool position and the target tool position.

This data flow category we can call: deviations

for machine control.

OSYRIS

OSYRIS [2] is an even more complex system

where more data flows are addressed, as it includes work execution functions and quality

documentation functions. It is a system also

where there are several data exchanges between

different kind of machines (paver to rollers).

OSYRIS system is mainly designed for

standard asphalt pavement sites, executed with

1 paver and 2 compactors. A basic

configuration is proposed, with additional

308
options for on-board functions and office

functions.

- The TDS sub-system functions are executed

by several pieces of software that are physically

located in office computers or in on-board

computers, depending of the version of the

product.

hi the 'full' version of OSYRIS, the whole

package includes the office Design and

Documentation piece of software that allow a

full mission description and a full documentation of the achieved work consistent

with the geographical data base (OSYRIS

Product Model).

These pieces of software can also be located at the level of the Permanent Data Storage and

Management system which is outside of our

SIS, since they are also designed to manage the

permanent information after the execution of

the work.

- The DCP functions are executed mainly by

the on-board computers, located on the paver

{Paver OB) and on the rollers (Roller OB). This means that wireless exchanges are addressed,

for instance for temperature data, position data,

etc. The visualization of the progress of the

work is ensured by the office Work

Documentation software component (WD) and

by the Work Site Web (WW) service.

Many on-board sensors are also concerned in OSYRIS, as inputs to the DCP and these data

flows are necessary to be standardized . As far as AFO and WE are concerned, the

functions are quite closed from those of CIRC

system.

The OSYRIS data flow analysis is presented on

Figure 4.

Figure 4: The OSYRIS data flows

The new data flows that are involved in this kind of SIS are material-related measurements

that are carried out on the machines, for documentation, operation or transmission to other machines purposes, like: temperature,

thickness, width and volume of the layer,

environment parameters. Let us call this new category: machine sensors

data.

5 SYNTHESIS ABOUT THE DATA

FLOWS TO STANDARDIZE

Our analysis, from road construction SIS, has

yielded the following 6 main data flows

categories:

1. Design data,

2. Mission data,

3. Real-time Position and speed data,

4. Real-time machine sensors (and

achieved surface) data,

5. Real-time deviations for machine

controls,

6. As-built and work documentation

data.

(As achieved surface data are obtained from

sensors on-board of the machine, they can be

309
grouped with machine sensors data. Position

and speed data are for the moment considered

apart, given their very specific importance).

These categories have different time scales:

1 and 6 have very long evolution periods

(from several days to several months),

2 has medium long evolution periods (from

several hours to several days),

3, 4 and 5 have short evolution periods

(from some milliseconds to several

seconds).

Type 6 is the counter part of types 1 and 2, asbuilt corresponding to design and work

documentation to mission. These 3 categories

are composed of static data. As far as format is concerned, XML seems to be an excellent

candidate given its universality and flexibility. In this respect, the new LandXML standard

under development [5], proposing both data

model and data format should be considered,

although non addressing documentation data so

far. Raster formats are also to be considered for

presenting synthetic documentation maps.

Categories 3 to 5 are real-time data, attached to the machine itself. An important remark is that these data have necessarily to be processed with

respect to the position of the machine (this is obvious for category 3). An interesting way of

representing these data is to use the Ribbon data

base structure which has already been used in both CIRC and OSYRIS projects and is described in [6] and [7]. Ribbons allow the

description of geometry, this way they can be

used also for design and as-built data, but they can also store parameters with respect to the

position of the machine. These parameters can

be either machine sensors data or deviations for

tool control. Ribbons are generated by a generator moving along an oriented polyline

and allow parameter interpolation as wall as curvilinear transformation. They are timetagged and each machine is generating its own

ribbon. All the different ribbons can be merged

to output the synthetic maps for as-built

documentation.

6 CONCLUSION AND PERSPECTIVES

Our analysis has brought to the fore several data

flows categories that must be considered

separately since they play different roles in the process. Still these different categories need to be described more precisely to continue the

work, but experience from European projects

such as CIRC or OSYRIS already tells us that the Ribbon structure can be considered as a

universal digital model for real-time data. As

far as static pre-execution and post-execution

data are concerned, existing standards as LandXML or raster format must be used.

7 REFERENCES

[1] Peyret F. Miyatake H., "Standardization of

information systems for civil engineering

rh sites", Proc. 18 International Symposium on

Automation and Robotics for Construction,

Krakow (2001), 235-240

[2] Ligier A., Fliedner J., Kajanen J., Peyret F., "Open system for road information support",

th Proc. 18 International Symposium on

Automation and Robotics for Construction,

Krakow (2001), 117-182

[3] Peyret F. , Jurasz J., Carrel A., Zekri E., Gorham, B., "The Computer Integrated Road

Construction project". Int. journal Automation

in Construction , vol. 9 (2000), 447-461

[4] Pampagnin L.H., Peyret F., Garcia G.,

"Architecture of a GPS-based guiding system

for road compaction", Proc. IEEE

International Conference on Robotics and

Automation (ICRA), Liege (1998)

[5] http://www.landxml.org/

[6] Jurasz J., "Universal digital environment

model for computer integrated road

construction", Proc. 18 International

Symposium on Automation and Robotics for

Construction, Krakow (2001), 37-42

[7] Jurasz J., Ligier, A., Horn A.., "On-board

data management structure for advanced

construction machine support", to be

published in Proc. 19 International

Symposium on Automation and Robotics for

Construction, Washington DC (2002)

310
PARTS AND PACKETS UNIFICATION

FOR CONSTRUCTION AUTOMATION AND ROBOTS

Tomohiro UMETANI*, Tatsuo ARAI*, Yasushi MAE*, Kenji INOUE*, and Jun-ichiro MAEDA**

Graduate School of Engineering Science, Osaka University

1-3 Machikaneyama, Toyonaka, Osaka, 560-853 1

, JAPAN

**Shimizu Co.

umetani@arai-lab.sys.es.osaka-u.ac.jp

+8 1 -6-6850-6368, +8 1-6-6850-634 1 (FAX)

ABSTRACT: This paper proposes a method of configuration of database system for parts oriented

construction. In parts oriented construction, robots acquire information related to the tasks from the server through ID attached to the construction components. This system aims (1) simplification in motion planning of the construction robots using information attached to components, (2) reconfiguration

of data structure for process of construction tasks. The robot performs the tasks according to local planning based on the local information. The operation server reconfigure parts information based on

task result by robots so that the next robot can obtain the required information from the composed

components in the next phase. We call the parts integrated information "packets", and call our idea

"parts and packets unification." The feasibility of our proposed method is also shown in the prelimi- nary experiments where an RPID tag attached to a component is applied for data exchange.

KEY WORDS: Automatic Construction, Information Integrated Components, Data Collection System and Labeling, Automatic Reconfiguration of Parts Information, RFID Tags

1. INTRODUCTION

The recent advancement of information

and communication technologies has brought

feasibility of efficient construction automation

[1][2][3]. However hard problems of construction automation still exist. In construction site, workspace changes according to a progress of

construction works and works are performed in

parallel. And a building is one-article production. Therefore, it is difficult to make a global

and perfect plan of the construction robots beforehand.

It is reasonable that the parts-oriented construction, where a robot makes a plan using

information of parts on site, is applied to the construction automation. For the parts-oriented

construction, the server manages a relation between construction components and their information. And the server has to manage the information of working robots. By managing

the relationship between the parts and their

information, the robot can check the assembled

parts and can correct errors caused by distur- bances. Therefore, it is expected that the work

may not be repeated to cancel the errors and

the efficiency may be improved of the work.

In the construction tasks, new components

are generated in the progress of construction. We call this newly composed component a "module," since it is used as a part of the

building. A module is used as a component in the next phase. Attributes of a module (form,

weight, center of gravity, etc.) will change as components are composed to a new module. It

is difficult that a robot obtains required infor- mation of each component composed in a module. Then parts information about the module should be reconfigured. In order to reconfigure the parts information automatically,

it is necessary to match a component (parts)

with its accompanying information (packets).

We call this state "parts and packets unified

state." We propose a parts oriented construc311
Fig. 1 Change of components in construction

tion system using the concept of "parts and

packets unification."

In this study we consider parts and packets

unification, where every object, part, module,

and structure carries its related information on

itself with data carrier such as RFID tags [4] [5], bar codes [6], and so on. We are also interested

in its effective usage of the construction auto- mation and robots. In the following we will discuss what a feasible database will be, how

attributes will be dealt with as construction

objects are processed, and what physical and

information interactions between objects and

robots will be, by citing some example tasks.

2. PARTS ORIENTED

CONSTRUCTION

2.1. Unification of Parts and Their Information

We show a construction process of a building in Fig. 1. In the construction tasks, information and attributes of each component

and those of the completed building are known.

And the work procedure is also known. A new

module is generated by composing the components. Attributes of a module (form, weight,

center of gravity, etc.) will change as the module is composed. But their information is un- known. In a process of construction, attributes of a module should be clear for local planning

of the construction robots. We propose a method to clarify the attribute of the module

using an ID attached to each component.

Component ID Operation Result

Component Data Rough Planning Operation Server Data Operation I f Perfect Operation I I Component ID & Management I i Matching

mmm

Information Integrated Components Component Database

Fig. 2 Diagram of parts oriented

construction

2.2. Parts Oriented Construction

We consider a method of realization of the

parts oriented construction system using in- formation-integrated components. In Fig. 2, we

show a relation between construction robots,

components, and their information. A Robot

acquires the parts information via ID attached

to the components, and operates the components. The robot sends the components ID and

the task results to the operating server while

achieving the tasks. The server sends the parts

information to the robot by the components ID. There are several methods to obtain the components ID in this system, for example, RFID

tags, bar code, and so on. And there are several ways to communicate between the robots and

the server, for example, a private network,

LAN, and so on. A method of informational operation by

the server and acquisition of the parts information by the robots are serious problems to the

settle of the construction system. Thus we dis- cuss the method of the informational operation

and management of the parts information in section 3. And in section 4, we carry out ex- periments of the acquisition of the parts infor- mation using RFID tags. We discuss the problem in the parts oriented construction system.

312
Ran

Goal

component ^^^p

Stored Information

Module Assembly

Data Flow

1 Integration of Information &

\^ Actual Objects

Fig. 3 Example of parts and packets

unification

component A TaglDxxxx

Data ID aaaa

module C: Data ID cccc \

/

component B: Tag ID yyyy component D: Tag ID y??? Data ID bbbb Data ID dddd Data Structu re

Data Table Data Table Data

module E: Data ID eeee

Data Table Dala

component B

componeni D

lag zzzz

3. MANAGEMENT OF STRUCTURE

OF PARTS INFORMATION

3.1. Autonomous Data Acquisition

Fig. 3 shows a concept of autonomous

composition of parts information. Robots

achieve a construction task based on the task

plan. The parts information is also composed

from the task results. Thus the parts information of the modules is also composed. Fig. 3 shows an example of how a module and its attributes are reconfigured through an assembly task. The attributes of a real module and

those stored as parts information of the module

in the server are matched by autonomous re- configuration of the parts information. Thus,

the robot can determine the detail motion plan

using the rough motion plan and the stored information of the modules.

We show the merits of the autonomous

data reconfiguration. If the attributes of modules are stored as the accompanied parts in- formation, the robot can obtain the information

of the modules easily by local information ac- quisition through the ID.

3.2. Properties of Parts Information

Attributes of a module, for example,

weight, center of the gravity, posture, and so

on, change in robots and machine acting on a module. It is expected that recognition of the stored attribute utilizing the task result of ro- bots lead to consumption of lower energy and

safety of the construction site for workers,

machine, and robots.

In this section, we describe the property of

Fig. 4 Autonomous data renewal process

in module assembly

the attributes of modules. The attributes of

modules change in a progress of tasks. Some

attributes inherit the former attributes before

the change (dependent), and others do not in- herit the former attributes (independent). For

example, form, moment, and the properties of

a module depend on those of a former module.

On the other hand, appearance and accuracy of

a module do not depend on those of a former

module. Accuracy of attachment and processing of modules are different since abilities of

workers or robots are different. And new at- tributes are added when a module is processed,

i.e. welding and cutting.

The attributes of each module should be

reconfigured during construction. A large

module consists of many modules.

3.3. Reconfiguration of Parts Information

Fig. 4 shows the change of the parts in- formation stored in the database in the process of module assembly. The top of the figure

shows an example of the process and how each

component is composed is shown. The bottom

of the figure shows the parts information of the composed module. In this figure, module C is composed from component A and B. And

module E is composed from module C and

element D. The code "xxxx" indicates the ID

code of each tag or information. In this example, the module is composed so that the parts

information is also reconfigured. It is desired

that the database should be set up in order that the robot can refer the same information of the

313
module via each tag attached to the module.

We will discuss the structure of the parts in- formation and the method of reconfiguration of

reference of the parts information.

We show the method of the configuration

of the parts information in the following. It is supposed that a tag is attached to component A,

B, and D. The parts information referred to each tag is stored in the server. When the robot composes component A and B, the robot ac- quires the parts information using the reference from the tag xxxx attached to component A

and tag yyyy attached to component B, and the robot achieves the task. Then both attributes of

component A and B change so that the newly

reconfigured information of module C is generated. And the attribute of module C is re- ferred to the tags attached to component A and

B. Therefore the robot c£in acquire the infor- mation of the module via any tags attached.

Fig. 5 shows the reconfiguration of data reference from tag xxxx, yyyy in the composition process. The left side of Fig. 5 shows the ranking of the parts information references. For the first time, the reference of parts infor- mation about each element is stored in the reference map. In the process of the module

composition, the ranking of the reference changes in order that the robot refers to the information of the composed module via each

tag attached to the module. Through the data

operation, the robot can refer to the present

information of the module via any tags at- tached to the module. On the other hand, the robot reaches the information of each element

using the list of the reference map for each tag. We make a simple program of reconfiguration of the database, so that the robot can re- configure the parts information of the module.

4. EXPERIMENT OF ACQUISITION

OF PARTS INFORMATION

4. 1 . Acquisition of Parts Information by Robot

We describe a method of acquiring parts

information by a robot. To obtain the information attached to the parts, a robot recognizes

letters or markers printed on the parts in a

Top

2nd

3rcJ

Top

2nd

3rd

tag xxxx 1^tag xxxx

cccc aaaa

bbbb

tag yyyy bbbbtag yyyy

cccc "bbbb"

Reference Map Data Map

Fig. 5 Reconfiguration of data reference

in module assembly

Fig. 6 Prototype of hybrid arm

method [7]. But a vision sensing has a diffi- culty to acquire the information, since a vision sensor is strongly influenced by conditions, the surface status of parts and a light source. We adopt an RFID tag as a medium for acquisition of the information. An RPID tag is robust against a change of environmental conditions, e.g. temperature and light sources. However it is influenced by a metal that is fi-equently used as parts in construction site, since they are communicated by radio signal.

Here we try to carry out experiments of ac- quiring parts information using RFID tags to ascertain the feasibility. Through the experiment, we discuss possibility of autonomous

construction using RFID tags. The experiment setup includes using an

antenna, RFID tags, parts models, and the prototype hybrid parallel arm for autonomous

construction (see Fig. 6). We consider the conditions about a robot that acquire parts in314
Antenna Component Table 1 Communicable distance between

antenna an RFID tags

Non

Conductive

Material

Fig. 7 Experimental environment

formation from the parts by RFID tags, and

also discuss how the tags should be attached.

4.2. Experimental Setup

The experimental setup is shown in Fig. 7. The center of the antenna is set at the same

level, h, as the RfID tag, and the distance be- tween the antenna and the RFID tag is d. and

the distance between the RFID tag and the component is t. The RFID tag is OMRON

V700-D13P21. The antenna is OMRON

V700-H01. In this setup, the height h is 215[mm]. The component is 60[mm] by

60[mm] by 130[mm], and it is made of iron. There are two pins on a pair of the parallel sur- face. The length of each pin is 15 [mm]. The

floor is made of metal. We examine what the maximum distance

between the antenna and the RFID tag attached

to the component where no antenna can communicate with the tag. And we measure the thickness between the RFID tag and the component to obtain the reasonable communicable

distance. A nonconductive material is intro- duced to cancel the metal influence on radio

signal. Its thickness will be varied. To compare

the ability of the communicable distance, we

measure the communicable distance between

the antenna and the RFID tag attached to the nonconductive object.

4.3. Measurement Results We measure the commimicable distance by changes of the distance d between the RFID

tag and the antenna. We wrote small-size data

to the RFID tag, and read the data from the tag

using the antenna. We regard that the trial suc- ceeds if both writing and reading tests are suet [mm] 0 3 6 9

Maximum

Distance [mm]

Failure 90 125 130

(a) Pillar (b) Beam

Fig. 8 Information integrated components

handled by the hybrid arm

ceeded. For each distance d, \0 trials zire car- ried out, and we set distance d by 5 [mm]. We

regard the distance that all trial at the distance succeeds as the commimicable distance. The

thickness of the nonconductive material t is set

0, 3, 6, and9[mm].

The communicable distance between the antenna and the RFID tag is shown in Table 1. The table shows, a reasonable communicable

distance can be defined if the RFID tag is at- tached to the component with the nonconductive material, but not directly. In the comparison, the commimicable distance in the case the

tag attached to the nonconductive material is 180[mm].

4.4. Acquisition of Parts Information in Manipulation

We examine acquisition of parts information while the hybrid arm shown in Fig. 8. The

hybrid arm manipulates the parts and the ex- perimental setups are carried out in the same

conditions as in section 4.2. The height h from

the ground to an RFID tag is set 190[mm] so

that the hook or the end-effector of the hybrid arm might not become obstructive on manipulating a component. We attach an RFID tag to

315
a beam component at 40[mm] shifted from the center since the end-effector has the hook at the center. In manipulating the beam component, the height h is set 230[mm]. We set the thickness between the component and the tag /

is set 6[mm] from the measurement results in section 4.3. Fig. 8 shows how the arm can

handle the component.

We tried the communication test with the distance 80[mm]. From this examination, the robot can acquire the parts information via the RPID tag attached to the component using the antenna. But, when we shift more 10[mm]

from the center of the arm or set the communicable distance d more 20[mm], the antenna cannot communicate with the RFID tag. Therefore, the distance should be carefiilly se- lected in the actual application.

5. CONCLUSIONS

This paper proposes a parts oriented construction system using the concept of "parts

and packets unification." We propose an autonomous data reconfiguration using the change of attributes of modules that a robot

acts. We discussed the data structure of the

parts database, reconfiguration of the parts in- formation changes on task procedures, and the property of parts information. And we showed

the autonomous data acquisition using RPID

tags attached to components. Through the ex- periment, we assured the feasibility of the proposed parts oriented construction system.

ACKNOWLEDGMENT

This work has been done in IMS international joint research program IF7-II. We appreciate the usefiil discussion with Mr. Jun-ichi Yagi, Shimizu Co. and other members of the program. REFERENCE

[1] T. Arai, K. Yuasa, et al: "A Hybrid Drive

Parallel Arm for Heavy Material Handling," IEEE Robotics and Automation

Magazine, Vol. 9, No. 1, pp. 45 - 54,

2002.

[2] "Study on innovative and intelligent field

factory domestic feasibility study for IMS," IMS Promotion Center, 1998.

[3] H. Osumi and T. Arai: "Cooperative Control between Two Position-controlled Manipulators," Proceedings of the IEEE In- ternational Conference on Robotics and

Automation, Vol. 3, pp. 1509 - 1514,

1994.

[4] K. M. Furlani and W. C. Stone: "Architecture for Discrete Construction Component Tracking," Proceedings of the 16th lAARC/IFAC/IEEE International Symposium on Automation and Robotics in Construction, pp. 289 - 294, 1999.

[5] K. M. Furlani and L. E. Pfeffer, "Auto- mated Tracking of Structural Steel Members at the Construction Site," Proceedings of the 17th lAARC/IFAC/IEEE In- ternational Symposium on Automation

and Robotics in Construction, pp. 1201 -

1206, 2000

[6] J. Ota, M. Yamamoto, et al: "Environmental Support Method for Mobile Robots Using Visual Marks with Memory

Storage," Proceedings of the 1999 IEEE

Intemational Conference on Robotics and

Automation, pp. 2976 - 2981, 1999.

[7] K. Sawa, W. Ohyama, et al.: "Recognition

of Degraded Character String on Steel

Plate," The Transactions of the lEE Japan,

Vol. 122-C, No. 1, pp. 84 - 89, 2002, (in

Japanese).

316
An UML-XML-RDB Model Mapping Solution for Facilitating

Information Standardization and Sharing in Construction Industry

I-Chen Wu^ and Shang-Hsien Hsieh^

Department of Civil Engineering, National Taiwan University

Taipei 10617, Taiwan, R.O.C.

kwu@caece.net' and shhsieh@ce.ntu.edu.tw^

Abstract: To facilitate information standardization and sharing in Construction Industry,

this paper presents a simple but effective approach that maps the UML (Unified Modeling

Language) object-oriented information model related to a construction project to an XML

schema, then to a Relational DataBase (RDB) schema. First of all, the mapping between

UML model and XML schema is discussed since UML has been a popular tool to model

the static structure and dynamic behaviors of the information and processes in a

construction project, while XML has become a de-facto standard for information sharing

and exchange. Then, a set of consistent rules for mapping from XML schema to RDB's

Entity-Relational (E-R) model are studied and estabUshed since RDB has been the most

popular choice for information management. The present study focuses on making the set of rules simple and easy-to-implement for most apphcations in construction industry.

Finally, a mapping tool for automatically generating RDB schemas from XML Schemas is developed.

Keywords: UML, XML Schema, RDB, Information Standardization and Sharing

Introduction

During the life cycle of a construction project,

voluminous data and information are usually

created along the delivery processes of

construction products. There is always a need

to share and exchange these engineering data

and information among related parties

involved in the project. However, because data

models defined in the information management

systems of various parties are usually different,

it is always difficult to directly map from one

data model to another for the purpose of

information sharing and exchange.

To address the aforementioned informationsharing problem among various parties,

standardization of the data model for a construction project is usually inevitable. Due

to the popularity of object-oriented modeling

approach in recent years, an object-oriented

information model is often constructed to represent the static structure and dynamic

behaviors of the information and processes in a

construction project and expressed by UML

(Unified Modeling Language) [1], a popular

tool for object-oriented modeling. Moreover,

Extensible Markup Language (XML) [2] has

become a de-facto standard for information

sharing and exchange in recent years. Therefore, there is a need to define an XML

schema based upon the UML object-oriented

information model to further facilitate information sharing.

Furthermore, due to the popular use of

Relational Database (RDB) technique for

information management, it is also important

to address the mapping between an XML

schema and an RDB model. However, the

mapping is not an easy one because the data

model of an XML document is fundamentally

different from that of a relational database.

Especially the structure of an XML document

is hierarchical and the XML elements may be

nested and repeated.

Although several RDB providers have

provided common data import/export tools to allow for data transformation between the

XML documents and the RDB tables, the

capabilities of these tools are still quite limited.

Recently some commercial software has also

provided tools for transforming information in XML documents into RDB. However, most of

them can only transform simple XML

documents. That is, if the XML documents

have a nested data structure and association,

317
most of these tools are still incapable of

making a complete transformation.

In addition, several XML-to-Relational

transformation algorithms and mapping tools have been proposed in the literature. For

example, Bourret et al. [3] introduced an XML-RDB mapping language to specify

transformation rules for generating an RDB

schema from an existing XML DTD

(Document Type Definition). They also

proposed a lightweight, DBMS- and platformindependent load/extract utility to facilitate the

data transfer between XML documents and

relational databases. Lee and Chu [4] proposes

a method where the hidden semantic

constraints in DTD are systematically found

and translated into relational data models.

However, most of them deal with XML DTD,

instead of XML Schema, which is more

flexible and offers more supports for data

types.

This paper presents an UML-XML-RDB

model mapping solution that maps the UML

object-oriented information model to an XML

schema, then to an RDB schema. First of all, the mapping between UML model and XML

schema is discussed. Then, a set of consistent

rules for mapping from XML schema to RDB's Entity-Relational (E-R) model is presented. In this work, the set of rules is made

simple and easy-to-implement for most

applications in construction industry. Finally, a mapping tool developed for automatically

generating RDB schemas from XML Schemas

is discussed.

Constructing XML Schema from UML

Data Model

This work adopts the concept of the XML

Metadata Interchange specification (XMI),

which defines a rigorous approach for

generating an XML DTD from a metamodel

definition, and slightly extends the approach of

XMI for mapping object-oriented data model

expressed by UML to XML Schema. The

transformation rules employed in the mapping

process are discussed as follows:

1. Mapping UML Classes to XML Elements

The UML Classes show the structural and

behavioral features in the object-oriented

Model. These features include attributes,

association, aggregation, and composition. On

the other hand, XML elements serve as a

container for attribute and child elements.

Thus, mapping UML classes to XML elements

are quite straightforward.

2. Mapping UML Attributes to XML Attributes or Elements

Basically, either a primitive data type or an enumeration of UML attributes may be

represented as an XML attribute. However,

XML parser removes all extra whitespace

characters, such as tabs, linefeeds, etc. That

makes XML attributes mainly appropriate for

simple datatypes of short string values. On the

other hand, one can map attributes of an UML

class to separate child elements of the

corresponding XML element of the class.

3. Flagging UML Object Relationships by an XML Attribute

The current version (Version 1.0) of XML

Schema does not yet have direct and full supports for expressing a complete objectoriented model, especially the distinction

between the delegation and aggregation

relationships that commonly exist in the

model. Therefore, this work employs a special

attribute named "relation" with a value of

either "delegation" or "aggregation" to flag the

relationship between the owning XML element

and its child elements. It will be shown later in

this paper how this special attribute is used to help mapping the XML object schema to a RDB table schema.

4. Constraints on Naming XML Elements

In general, the UML class name is directly

used as the XML tag name in the mapping

process. However, there are certain constraints

we must comply when naming the XML

elements:

• The tag name cannot have spaces in it, but

symbols like ".", "-", and "_" are allowed.

• The tag name should not start with the

string "XML".

Mapping XML Objects to Relational

Database Tables

318
XML provides many of the things found in databases, such as storage (e.g., XML

documents), schemas (e.g., DTDs, and XML

schemas), quer}' languages (e.g., XQuery,

XPath. XQL), programming interfaces (e.g.,

SAX, DOM, JDOM), and more. However,

XML lacks many important features that are supported by the real databases, such as

efficient storage, indexes, security, transactions

and data integrity, multi-user access, triggers,

queries across multiple documents, etc. [5] Therefore, databases are still the top choice for

managing information in a enterprise or government agency. Although several kinds of

database technologies are currently available in the market (e.g., object-oriented database,

object-relational database, etc.), RDB

technology remains the most popular one employed in the construction industry.

On the other hand, there is a trend for using

XML documents with a standardized schema

as a medium for information sharing and

exchange among different parties involved in a

construction project. In order to transfer data

from XML documents to an RDB for efficient management, it is necessary to map the XML

document schema (XML Schema) to the RDB

table schema.

Since an XML Element is mapped to an RDB

table, the attributes of the XML Element is naturally mapped to the columns of the

corresponding RDB table automatically (as

shown in Fig. 2).

Main Object

attributel attribute2

is napped to

A ttribute U apping

Columnl Column2

Fig. 2 Mapping attributes of an XML Element

to the columns of its corresponding RDB

table

3. Mapping XML Elements with Delegation or Aggregation Relationship to RDB tables

For mapping the delegation (or dependency)

relationship between XML Element objects,

the parent object and its child objects are mapped to separate RDB tables with a primary

key and a foreign key, respectively, for

associating them (as shown in Fig. 3).

Because the XML Schema can be viewed as a

tree of objects that is mapped from the object

model of its corresponding UML class diagrams (as already discussed in the previous

section), this work employs the following

object-relational mapping rules to map the XML schema to RDB tables [6]:

1. Mapping Elements to Tables

An XML Element object with attributes,

element content, or mixed content (i.e., a complex Element object) is mapped to a

separate RDB table as shown in Fig. 1

.

Main Object K

ClassUappisg

Single Table in RDB

attributel

attribute2

ia mapped to >

Columnl [/ Column2

Fig. 1 Mapping an XML Element to an RDB

table

2.Mapping Attributes to Columns

Object

attributel atbributeZ (Ref="DeDentent Object')

is mapped to

Dependent Object

attributes attibute4

is mapped to

D ependeiKy U apping

Single Table in RDB

Columnl

C olumn2(PrimaiyK ey)

Link to

D ependency U apping

Single Table in RDB

Column3(ForeignKey)

Colunni4

Fig. 3 Mapping XML Element objects with

delegation (or dependency) relation-ship

to RDB tables

For mapping the aggregation relationship

between XML Element objects, the parent

object and its child objects are mapped to a

319
single RDB table uniting attributes of all the

XML Element objects (as shown in Fig. 4).

Main Object

attributfil attributes

is mapped to

Aggregated Object

\ attributes attribute

is mapped

1

AggregalioDUappiiig

Single Table in RDB

attribute! attributes

atiribatel

Fig. 4 Mapping XML Element objects with

aggregation relationship to a RDB table

XML-RDB Mapping Tool

In this work, an XML-RDB mapping tool,

called Schema2RDB, has been developed to verify the mapping rules discussed in the

previous section and to automate and ease the

task of creating RDB tables based on an

existing XML schema. The tool is implemented using Java solutions mainly due

to its platform-independent capabilities. JDOM

API [7] is employed for an easy and efficient

reading, manipulation, and writing of an XML

document. JDOM itself is not a parser; instead,

it is a wrapper. Therefore, it requires the

presence of an underlying parser. In this work,

Xerces is used for the parser. Because JDOM

is used to handle all types of XML Data in this work, we can say that Schema2RDB is a 100%

pure Java application.

Figure 5 shows the interactions among the

user, Schema2RDB, and an RDB. First of all, the user assigns an XML Schema file and

executes Schema2RDB. Then, Schema2RDB

starts parsing the XML Schema file, applies

the mapping rules discussed in the previous

section, and generates SQL statements

automatically via JDBC [8] to create relational

database tables (in this work, Microsoft SQL

Server). Finally, the RDB responds with the

information about the created database tables and Schema2RDB forwards the information to the user.

W hen the action of

Creatiiig DB is done

,

Sending a message to notify the uSer

Fig. 5 Interactions among the user, Schema2RDB, and an RDB

The process of mapping an XML schema to RDB table schemas in Schema2RDB is discussed in more detail as follows:

1. As shown in Fig. 6, the structure of the

XML schema is first parsed by a XML

parser and converted into an XML DOM.

The parser provides a way to extract XML

schema information and can automatically

resolve names of elements and attributes.

XML Schema File

Fig. 6. Parsing the structure of XML schema

I. After the parser has resolved the names of

the elements and attributes, Schema2RDB

determines the names of the tables and

columns as well as relationships for

mapping to a relational schema.

Database

TableName

ColumnName

ReMonship

Fig. 7 Determination of the names of the tables

and columns as well as relationships for

RDB

3. Schema2RDB then composes the SQL

statements required to create the RDB

tables corresponding to the parsed XML

schema (as shown in Fig. 8). The template

of a SQL statement is first constructed

according to the variable, then the value of

320
the variable is used to complete the

composition process.

help facilitate information standardization and

sharing in construction industry

Database

TableName

ColumoNaine

Relatioitihip —

CREATE DATABASE

2. CREATE TABLE

3. ALTER TABLE

Fig. 8 Composing a SQL statement

4. Through the JDBC driver, Schema2RDB

creates a connection to the relational

database, executes the SQL statements,

and finally closes the database connection.

At this point, database tables are ready in the RDB for accepting data from the

corresponding XML documents.

1. CREATE DATABASE

2.CREATE TABLE

3j^LTER TABLE

Relational Database

Fig. 9 Process for creating RDB tables

In addition, Schema2RDB have been

successfully tested by several verification

examples. Although these examples are not considered sophisticated ones, the

effectiveness of Schema2RDB in mapping

XML Schema to RDB table schema has been

observed.

Conclusions

This paper has presented a simple solution for mapping UML object-oriented model to XML

Schema, and then to RDB table schema. The

framework and process of the mapping

approach have been discussed herein. A set of

simple, consistent, and easy-to-implement

mapping rules has been proposed. In addition, a mapping tool, called SchemalRDB, has been

developed to facilitate automatic generation of

RDB table schemas from XML Schemas. It is hope that the work presented in this paper can

REFERENCES

1. M. Fowler and K. Scott, UML Distilled,

2nd Edition, Addison Wesley, Boston,

2000.

2. W. J. Pardi, XML in Action, Microsoft

Press, Washington, 1999.

3. R. Bourret, C. Bomhovd, and A.

Buchmann, "A Generic Load/Extract

Utility for Data Transfer Between XML

Documents and Relational Databases,"

Proceedings of the Second International

Workshop on Advance Issues of ECommerce and Web-based Information

Systems (WECWIS 2000), San Jose,

California, U.S.A., June 8-9, 2000.

4. D. Lee and W. W. Chu, "CPI: ConstraintsPreserving Inlining Algorithm for Mapping

XML DTD to Relational Schema," Data

Knowledge Engineering, Vol. 39, No. 1, 2001, 3-25.

5. R. Bourret, "XML and Databases," from

web page at http://www.rpbourret.com/xmI/

XMLAndDatabases.htm, February, 2002.

6. I. C. Wu, "Information Sharing and

Exchange in Building Administration Using

XML Technology," M.S. Thesis,

Department of Civil Engineering, National

Taiwan University, Taipei, Taiwan, 2002.

7. J. Britt, "Interactive Java & JDOM online

tutorial," Commercially available from the

TopXML website at http://www.topxml.

com/, 2002.

G. Reese,

JDBC and

200 L

Database Programming with

Java, 2/e, O'Reilly, U.S.A.,

321

Using Customized Navigational Models to Deliver more Efficient Interaction with Mobile

Computing Devices on Construction Sites

Jan Reinhardt,

Research Assistant, Carnegie Mellon University, Dept. of Civil and Environmental Engineering,

janr@andrew.cmu.edu

Burcu Akinci,

Assistant Professor of Civil Engineering, Carnegie Mellon University,

bakinci @andrew. cmu.edu

James H. Garrett, Jr., Professor of Civil Engineering, Carnegie Mellon University,

garrett @cmu.edu

Abstract

Mobile computing devices have started to become useful tools on construction sites. These

devices can make large amounts of data available and support data collection tasks on a construction site. Even though battery life, computing power and data storage capacity have

greatly improved and will probably not be limiting factors for mobile computing solutions, it is

still difficult to interact with mobile computing devices efficiently. Some of the factors limiting

efficient interaction are the size of the screen of a mobile computing device, the deficiency of a keyboard and the limited accuracy of the pointing device. The approach we pursue is to limit the

interaction needed for specific tasks that are carried out using a mobile computing device. To do

this we are working on developing Navigational Models, which reduce navigation through large

data sets by grouping data entities closely together, according to the need to be accessed for a

specific task. Moreover, Navigational Models appear to be a useful construct to enter and access

data at the right level of detail, which they needed. In this paper, we discuss the need for more

efficient interaction with mobile computing devices on construction sites and introduce

Navigational Models.

KEYWORDS: Construction, Human Computer Interaction, Mobile Computing, Navigation

through Complex Data Structures, Product and Process Models

where they are needed, and bills of quantities

1 Introduction can amount to several hundred pages. As a Many documents available at a site office, result, site superintendents may not have the

e.g. drawings, specifications and schedules, data with them at the time when they need

are also needed on a construction site. the information. This deficiency leads to Currently, for the "last mile" of the flow of time-consuming document preparation

information from the site office to the job processes to make data available on a site,

site, computer-based documents do not work and additional data transition processes to very well. In a majority of the cases, the reintegrate data that has been acquired on a information stored within an electronic site into electronic documents,

document, or a product and process model,

needs to be printed out to access it on the In recent years, technologies that can bring

construction site. computing power to a construction site have

emerged. Mobile and wearable computers are Oftentimes, paper documents used on a powerful portable devices that can be used on

construction site are not in a format construction sites. Moreover, Personal Digital

appropriate for the environment in which Assistants (PDAs) and pocket computers

they need to be used. Drawings and schedules have become popular because of their may be too large to be carried to the locations portability. Information contained in

323
electronic documents becomes accessible

right on a construction site when these

devices are used. Observations that are made

on a construction site can be integrated into

electronic documents or models without

having to make notes and to enter the

information contained in the notes after being

back in the office. Current mobile computing

solutions for project management tasks in construction projects still have limitations.

These solutions limit the complexity of the

data with which the user is able to interact

efficiently. Unless mobile computing devices

for construction sites can bring all information to the construction site - both

complex and not so complex information -

and provide an environment within which a user can interact with the data efficiently,

problematic paper-based solutions will

continue to be used as the best available

approach.

2 Current solutions

Many vendors of established IT solutions for

construction processes, such as Primavera,

AutoDesk and Meridian, provide mobile

clients for their main product, e.g., Primavera

OnTrack. AutoDesk OnSite, Meridian Prolog

Pocket, respectively. The client applications

are equipped with functionalities needed on a

construction site in order to access and

collect data for a given application.

The information we acquired from site superintendents, who have been using a commercially available mobile project

management solution, suggests it has been

hard for them to enter textual data on the

construction site in an efficient way. For

example, the specification of the location of a problem requires cumbersome selections

from long lists of location descriptions. If the

list of possible locations was kept shorter

they were not able to specify the location at the desired level of detail. A similar selection

problem was identified for the input of the

problem description. Even though the

considered application handled relatively

simple data sets, the interaction with the

device and the application was challenging,

as the site superintendents had to trade off

between an accurate description of the

problem and efficient data input. Case

studies carried out by another research group

corroborate our observations that current mobile computing solutions fail to make

complex data sets available to the user

efficiently (Dogan et al 2001).

3 Related work

There appear to be three areas that are relevant for research addressing the problems

stated in the previous section: a) information

and data collection needs for knowledge

based tasks on construction sites, b) Human

Computer Interaction (HCI) methods for

interaction with large data sets and mobile

computing devices, and c) data models that provide the information needed on the

construction site.

Obviously, there are a number of knowledgebased tasks that are needed on construction

sites, which may vary among projects, but

trades also may vary within one project as the

project advances. The published literature does not provide much information that explicitly states knowledge-based processes

and data needs on construction sites. Nevertheless, there are a number of implicit statements that information is needed on

construction sites and office-based processes

require information, which needs to be

collected on the construction site (Dogan et al 2001, Pena-Mora, Park 2001; Mills 1999,

Tommelein 1998). These statements motivate our research to make the data needed

accessible in an efficient way.

For an efficient navigation through large data

sets, Furnas (1986) has identified that tree structures are especially beneficial, as they

allow the user to interact with the data on

different levels of detail and access detail and

context information at the same time. Chien

and Flemming (2002) propose tree data

structures for efficient navigation through

large design spaces in architectural design

and Bjoerk (1999) states that rich linkage

between semantically related entities in a

large data set enhances the efficiency of

information access (Bjoerk 1999; Chien and

324
Flemming 2002). These techniques for

efficient navigation through large data sets are relevant for our research as the sources of

data that may be needed on a construction

site can be large (construction projects may

have several hundred drawings and thousands

of pages of specifications).

Even though product and process modeling

originated from design rather than

construction problems, researchers have

shown the usefulness of product and process

models for the construction phase of

buildings. There have been proposed product

and process models that specifically address

processes in the construction phase of a

building (e.g., Stumpf 1996, Akinci 2000,

Froese et al 1999). These product and process

models appear to be the way of handling and

storing construction related data in the future

and should therefore be the model that contains the data that we want to make

available on a construction site.

4 Making data accessible on site In our research, we hypothesize that allowing

interaction with data presented to the user on

variable levels of detail (LoD) will enhance

the efficiency of user interaction. Moreover,

we hypothesize that linking semantically

related information and presenting the links

to the user minimizes navigation needs

during interaction with an integrated product

and process model that handles the

information needed on a construction site.

4.1 The level of detail problem

In a case study with a mobile computing

application, we experienced that the level of

detail at which data is presented to the user and in which the user enters data in a mobile

computing system has a significant effect on

the efficiency of the interaction. This

experience is consistent with another case

study that investigated the usefulness of an Augmented Reality (AR) System for

inspection tasks in Nuclear Power Plants

(Dutoh et al. 2001).

For construction projects, many information

access and data collection tasks can be seen

as problems related to the level of detail. We

identified punch list creation, punch list maintenance and construction progress

monitoring as knowledge-based tasks that are

carried out at construction sites and require

interaction with data at different levels of

detail. For example, the question about what

the punch list items of the project are needed

to be resolved in the following two weeks

may relate to the overall project, a section of

the project, a certain room, a trade or a

certain contractor. For progress monitoring,

the user needs to enter the observed

construction progress in a mobile computing

device. The observed construction progress

may need to be considered at different levels of detail, such as the building element level,

the activity level or a higher-level grouping

of activities.

Interaction with the computing device

becomes inefficient or ineffective if there is a mismatch between the level of detail, in which the user is interested or the user wants

to enter data, and the level of detail provided

by the application. For the progress

monitoring application we tested, (Reinhardt

2000), the level of detail for the construction

progress was the building element level (e.g,

"installation of wall 3 on the 3'^'' floor is 50%

complete"). This high level of detail was

appropriate for tracking closely the work of

subcontractors, who were constantly late, but

for other less problematic activities, the level of detail was too high. The site superintendent had to enter the construction

progress of all building elements of one

activity even though the actual information

she wanted to enter was that all other

activities of a certain trade were complete

(lower level of detail). The number of clicks on the touch screen of a mobile computer to enter the observed construction progress at the building element level rather than, for

instance, at the activity level was typically

around 3*n times higher, where n is the

number of building elements associated with an activity (it takes 3 clicks to update an

activity that is assigned to a building

element). In the case study, n was typically in a range of 3 to 4. For progress monitoring,

325
we could show that the level of detail in which the user interacts with a mobile

computing application has a significant effect on the cycles of interaction needed for a

particular task.

4.2 Minimizing navigation needs

Considering the objective to make all information needed on a construction site available through a mobile computing device,

it is obvious that large amounts of data are involved. We assume product and process

models to be the knowledge base for construction projects in the future. Even

though these models integrate information

and hence make the contained information

available to the user in a unified way, the

navigation across data domains can become

very extensive. For this reason, efficient

navigation through the data is crucial for

efficient interaction with the mobile

computing application. In order to reduce the

cycles of interaction needed for a particular

navigation task, it appears desirable to link

information items that are semantically

related. Product and process models may

already have a rich set of semantic links

between the information items included in the

model. In the personal organizer application

PowerView, researchers have linked

semantically related items and presented

these links as context information to the user (Bjoerk et al 2001). For our research, we

want to build on Bjoerk' s approach of linking

semantically related objects together and

investigate its usefulness for the computer

supported knowledge-based tasks on

construction sites.

5 Example envisioned interaction style

The task is to determine the degree of

completion of the installation of windows at the building element level. When the last update of the construction progress was done,

the windows on the east side were completed

30% and no windows were installed on the

other sides of the building. The current

situation on the project for this illustrative example is assumed to be as follows: on the

south side of the building, three windows

have been installed, whereas the east side is

already completed; the work on the two other

sides has not started yet.

In order to record the current progress

situation, the user needs to capture the

changes in construction progress since the

last site visit. The product model is organized

in a given decomposition hierarchy as it is depicted in Figure 1

.

Building

^Office 1.1 Office 1.2 Offices \ Office 1.3

West -.^Office 1.5 Offices^~- Office 1.6 ^Office 1.7 North Offices^

_--Wall 1

\wall 3

Window 1 Window 2

Figure 1, Representation of the data

contained in a product and process model

As the user performs update operations only on windows, he/she specifies that a tree structure needs to be derived that only

contains information related to windows (see

Figure 2). The user also specifies that he/she

wants to inspect the windows from outside

the building and hence needs, for instance, a

tree structure that groups windows at a higher

level by the direction of the facade.

Windows

Figure 2, Navigational Model, Nodes (in

circles) that need to be selected for the

progress update

In order to record the progress update for the

window installation, the user would select the

326
node East (higher level) and classify all building elements on the east-facade as

installed. For the south facade the user needs

to select the items Windowl, Window2,

Window3 (lower level) and classify the

windows as complete. For the south facade,

the information that needed to be entered was more detailed and hence the interaction with

the system was more detailed compared to the interaction needed to enter the

information related to the east facade. The

proposed interaction style allows capturing

data in a very detailed way, but requires less interaction with the data compared to solutions that present at a static level of

detail.

6 Customized Navigational Models

Considering the opportunities discussed in the previous sections, we propose a system

that supports efficient navigation through

large data sets contained in integrated product

and process models, which are presented on mobile computing devices. To achieve this,

we propose Navigational Models, which are constructs that fulfill the following three

conditions: a) establish links between

information items in product and process

models that need to be accessed on the

construction site, b) support interaction with

data sets on different levels of detail, and c)

do not contain information, but rather contain

references to information items in a product

and process model. Even though linkages

between entities may already exist in product

and process models, additional linkages or

direct linkages specific for a task may

become necessary. One representation of a Navigational Model is a tree structure, which

has leaf nodes that have references to data in a product and process model. The data at the

leaves of the tree structure have to have the highest granularity of information in which a user might possibly be interested. Higherlevel tree nodes are dynamic aggregations of

lower-level nodes and do not have their own

attributes other than references to parent or

child nodes. However, all data related to the

leaf nodes can be made available in non-leaf

nodes due to the child-parent associations

between the nodes.

One version of the Navigational Model

supports interaction with data at different

levels of detail, as higher-level tree nodes

represent data aggregations of lower level data and hence are less specialized. The user

is expected to interact with the tree nodes that represent the desired level of detail. In addition to the tree structure representation of a Navigational Model, these models should

be editable and changeable. The user of the

envisioned system should be able to change

the configuration of nodes in the model and

thus customize the proximity of nodes in the

model. The ability to customize a Navigational Model responds to the

requirement to link information that is semantically related.

The customization of a Navigational Model is a means to reduce the navigation space for a given task. In contrast to views of a model, a Navigational Model is a construct that specifically supports a task by providing

information needed for the task. Views are

rather isolated representations of data

contained in a model and may not support

tasks, as tasks may require efficient interaction with different views. A

Navigational Model is a task-centered

interaction scheme that provides the user with

information in representations that are appropriate for the task and the environment

of the user. Different from views

Navigational Models establish linkages

between information items contained on

product and process models. Navigational

Models should enhance both information

access and data collection on construction

sites.

6 Conclusion and future work

Mobile computing devices can support

knowledge-based processes in mobile

environments and have started to become

useful tools on construction sites. These

devices can make possible more efficient and

consistent data handling during the

construction phase. Computing power and

future network connectivity will not be

limiting factors to make all data needed on a construction site available on electronic

327
devices. Interaction with mobile computing

devices is a major limitation for a wider

usage of these devices.

Current interaction styles with mobile

computing devices and applications often do

not consider domain knowledge in order to enhance the efficiency of the interaction with

the device. For the domain of project

management during the construction phase,

we have shown that incorporation of domain

knowledge can enhance the interaction with

mobile computing devices. Based on these

considerations, we have proposed

Navigational Models that incorporate domain

knowledge of the task a user is doing on a

construction site. The proposed Navigational

Models are envisioned to enhance the

efficiency of mobile computing applications

in two ways: a) allowing interaction with

information contained in a product and

process model at different levels of detail; and b) link closely together that information

upon which the user is likely to execute

operations.

This paper has motivated the need for

Navigational Models by describing the

problems users have with levels of detail and

navigations through large data sets. We also

described the basic functions of such a model

and discussed several ways in which these

Navigational Models might enhance the

efficiency of interaction with mobile

computing solutions. Future work will

implement and test this concept further.

7 References

Dutoit, A.H., Creighton, O., Klinker, G.,

Kobylinski, R., Vilsmeier, C, Bruegge, B.

(2001), Architectural issues in mobile

augmented reality systems: a prototyping case study. In The Eighth Asian Pacific

Conference on Software Engineering

(APSEC'2001), Macau SAR, China,

December 4-7, 2001.

Bjoerk, S., Holmquist, L.E., Ljungstrand, P., Redstroem, J. (2001), PowerView:

Structured Access to Integrated

Information on Small Screens

Froese, T., Fischer, M., Grobler, F.,

Ritzenthaler, J., Yu, K., Sutherland, S., Staub, S., Akinci, B., Akbas, R., Koo, B.,

Barron, A., and Kunz, J. (1999), "Industry

Foundation Classes For Project

Management-A Trial Implementation",

Electronic Journal of Information

Technology in Construction, Vol.4, 1999,

pp. 17-36. Available online at http://itcon.Org/1999/2/

Chien, S.-F. and Flemming, U., Design space

navigation in generative design systems.

Automation in Construction, 11 (2002)

pp. 1-22. Dogan, F., Wang, F., Lee, G., Jordan J.D.,

Onsite Construction Data Input Device,

project description, available under

http://swiki.cc.

gatech.edu:8080/cs6750b/58, March 2002.

Rezgui, Y. and Debras, P., An Integrated

Approach for a Model Based Document

Production and Management, Electronic

Journal of Information Technology in Construction, V. 1 ( 1996).

Sunkpho, J., J. H. Garrett, Jr., and A.

Smailagic, Opportunities to use Speech

Recognition for Bridge Inspection, In the

Proceedings of the 2000 ASCE

Construction Congress, pp. 184-193,

Orlando, FL, Feb 20-22, 2000.

Buergy, C, Garrett, J. H. Jr., Klausner, M.,

Anlauf, J., Nobis, G., Speech-Controlled

Wearable Computers for Automotive Shop

Workers, Proceedings of SAE 2001 World

Congress, SAE Technical Paper Series No.

2001-01-0606, March 5-8, 2001, Detroit,

Michigan.

Reinhardt, Jan; Garrett, J. H. Jr., Scherer,

R.J., The preliminary design of a wearable

computer for supporting Construction

Progress Monitoring, Internationales,

Kolloquium iiber die Anwendung der

Informatik und der Mathematik in Architektur und Bauwesen, Weimar,

Germany, June 2000.

Akinci, B., Fischer, M., Kunz, M., Levitt, R.,

Automated Generation of Work Spaces

Required by Construction Activities, CIFE

Working Paper #58, CENTER FOR

INTEGRATED FACILITY

ENGINEERING, Stanford University, June

2000.

328
SESSION 7

ADVANCED SENSING AND

t IMAGING TECHNOLOGIES

I

1

329

Performance of Artificial Intelligence Approach on Bridge Coating Assessment

by

Po-Han Chen' and Luh-Maan Chang^

ABSTRACT: Digital image processing has been prevalently adopted in different areas. In the construction field, image processing has been used for defect detection on steel bridge painting and

underground sewer systems. However, non-uniformly illuminated images always cause recognition

problems and affect the accuracy. In order to resolve these problems, the neuro-fuzzy recognition

approach (NFRA) was proposed. The NFRA segments an image into three areas based on illumination

and conducts area-based thresholding. The neural network is used in this approach for automatic

generation of three threshold values, with the three average illumination values of the three areas as the

input. The fuzzy adjustment is utilized to smooth and adjust the gray level values of the image pixels

along the boundaries. In this paper, the fi-amework of NFRA and the rationale of the fuzzy adjustment will be presented, followed by the comparison of the recognition results using NFRA and the multi-resolution

pattern classification (MFC) method. The result shows that the proposed NFRA performs fairly well on

recognizing rust images. Finally, the conclusions will be drawn.

KEYWORDS: Fuzzy Adjustment; Multi-Resolution Pattern Classification (MFC); Neural Networks;

Neuro-Fuzzy Recognition Approach (NFRA)

1. INTRODUCTION

As computerized technologies were widely

utilized, digital image processing was also prevalently adopted in many industries (Abraham et al. 1997; Croall and Mason 1992;

AbdelRazig et al. 1999; Chen and Chang 2000).

In the construction area, image processing has

been used for defect recognition on steel bridge

painting and underground sewer systems.

There are a number of advantages when using

computerized digital image processing.

Computerized digital image processing is able to distinguish millions of shades of colors, which

are hard to be distinguished by human eyes, and

enables the analysis and comparison of images.

In addition, digital image processing can

accurately calculate defect percentages. Even

though digital image processing has such

powerful capabilities, there are still some

drawbacks that need to be resolved, especially

when image quality is poor. Non-uniform

illumination is the most fi-equent problem that accompanies a poor-quality image. In order to obtain better and reasonable results while

conducting digital image processing, methods

that can diminish the bad effects fi"om non- uniform illumination are needed.

Intelligent surface coating assessment uses neuro-fuzzy recognition approach (NFRA) to resolve the recognition problems resulting fi-om non-uniform illiunination. Because the colors in

steel bridge rust images are simple, all rust images are converted to grayscale before fiirther processing without losing much information

(Chang 2000). The conversion of color images

to grayscale images reasonably simplifies the complexity and expedites the recognition

process. Then, the illumination-based image

segmentation is conducted. In this segmentation,

each of the grayscale images is segmented into three areas in accordance with the illumination

values of the pixels in the image. The average

' Assistant Professor, Nanyang Technological

University, Singapore 639798. Tel: +65 6790

4562. Email: cphchen@ntu.edu.sg

^ Associate Professor, Purdue University, West

Lafayette, Indiana 47907, USA. Email:

changlm@ecn.purdue.edu

i

I 331
illumination values of the three areas are calculated afterwards and sent to a pre-trained neural network to obtain three corresponding

threshold values, which will be used for illumination-based image thresholding later. In the mean time, a fuzzy adjustment is utilized to smooth the threshold values of the pixels along

the boundaries between different areas. Finally,

image thresholding is applied based on the obtained threshold values to get a binary image

containing only the object pixels and the background pixels (Chen 2001).

In order to test the feasibility of the proposed

NFRA, the recognition results using NFRA and

the multi-resolution pattern classification (MFC)

method were compared (Chen 2001).

2. FUZZY ADJUSTMENT

The fiizzy adjustment is to be applied to the image pixels on both sides of the boundaries

between areas. Figure 1 illustrates the schematic

representation of the fiazzy adjustment. Two

inputs are included in this fuzzy system, the

"positive difference" and the "negative

difference." The output is the "gray level adjustment." A set of nine If-Then rules

constitutes the kernel of the fuzzy system, as

indicated in Table 1 (Chen 2001).

Both the inputs "positive difference" and

"negative difference" have three levels: large,

medium, and little. The universe of discourse

(the range of input) for both inputs ranges from

0 to 20. Differences (both positive and negative)

larger than 20 are counted as 20.

The "gray level adjustment" is the output of the

fiizzy system. It is a value ranging from -0.1 to

0.1 and contains five different levels: negatively

large, negatively a little, still, positively a little, and positively large. The adjusted gray level value can be expressed by the following

equation:

G^ix,y) = G^„(x,yri\ + P) (1)

where G„eUx.yJ and Goid(x,y) represent the new

gray level value and the old gray level value of

the pixel located on (x,y), respectively. /? is the gray level adjustment amount, which is the

output of the fuzzy adjustment system.

3. NEURO-FUZZY RECOGNITION

APPROACH (NFRA)

The neuro-fiizzy recognition approach (NFRA)

conducts an area-based image recognition

process. Figure 2 illusfrates the flow of NFRA,

which contains seven steps (Chen 2001).

Step 1 - Step 2: Image acquisition is the first step of NFRA.

Image data can be acquired using a digital camera and transferred to a computer. The

second step is to convert the image to gray scale using image processing software. In order to process in an efficient way, an image is usually

converted to gray scale before processing.

Step 3: After converting the image to gray scale, the illumination value of each pixel can be found.

All the pixels in the image are separated into three groups in accordance with their illumination values. Illumination values are between 0 and 1, with 0 the darkest and 1 the

brightest. The average illumination values of the three areas will be computed and serve as the input to a pre-frained neural network. Figure 3

illustrates the illumination-based image

segmentation.

Step 4: Once the image segmentation is completed, the

three average illumination values of the three areas will be sent to a pre-trained neural network

to generate three corresponding threshold values,

which range from 0 to 255. The training set for the neural network should be diverse so that the

trained neural network would be fauU-tolerant. Figure 4 illustrates the neural confuting process of the three threshold values.

Step 5: In this step, the fuzzy adjustment is utilized to adjust the gray level values of the image pixels

along the boundaries. The gray level adjustment

range is from -10% to +10%. Figure 5 shows

the flow of fuzzy adjustment.

332
Step 6: In this step, each area is thresholded according

to its corresponding threshold value. Pixels with

gray level values smaller than the threshold

values (i.e., darker) are considered as defects (or

rusts in this case), and pixels with gray level values larger than the threshold values (i.e., brighter) are considered as background. Figure 6

depicts the illumination-based thresholding

process. In Figure 6, the values in the grayscale

image represent the gray level values of pixels.

The thresholded image is a binary image, with

O's representing the background and I's representing the defects (rusts).

Step 7: When the thresholding of all the three areas is completed, the defects in the image can be

recognized and the defect percentage can be

calculated by counting the percentage of the

defect pixels out of all the pixels in the image.

Figure 7 illustrates the defect recognition and

calculation.

4. MULTI-RESOLUTION PATTERN

CLASSIFICATION (MPC) METHOD

There are two resolution levels involved in the

multi-resolution pattern classification (MPC)

method: the fine resolution level and the coarse

resolution level. The fine resolution level (sometimes called the measurement level) refers

to the original image. The coarse resolution level

refers to a high-dimensional feature space that is mapped fi-om the fine resolution level (Chang

2000). MPC can be broken down into the following steps:

1. At the fine resolution level, the original

image is divided into a number of small

image blocks. The number of image blocks

affects the resolution of the classified (or

clustered) image. The larger the number of

image blocks, the better the resolution of the

classified image.

2. After the division of an image at the fine resolution level, the features of each image

block will be extracted and serve as the basis

for image classification. In MPC, the spatial gray level dependence method (SGLDM)

and the gray level difference method

(GLDM) will be adopted for feature extraction (Chang 2000).

3. When feature extraction for each image

block is complete, each image block will be

mapped onto a high-dimensional feature space as a vector (which can also be thought

of as a point in the high-dimensional feature space), with the number of features equal to the dimension of the vector. All the feature vectors in the high-dimensional feature space form the coarse resolution level. The

number of vectors (or points) in the coarse

resolution level equals the number of image

blocks in the fine resolution level.

4. A clustering algorithm will be applied to the coarse resolution level to classify the feature vectors in the high-dimensional feature space. The nearest mean reclassification (NMR) algorithm will be used for feature vectors clustering in MPC (Fukunaga 1990).

5. When the classification of feature vectors is finished, the classification result will be

mapped back to the fine resolution level to further cluster the original image. Feature

vectors of the same group in the coarse

resolution level will make their corresponding image blocks in the fine resolution level fall in the same group.

Figure 8 illustrates the flow of MPC. The

structure of the MPC can be represented by the "multi-resolution pyramid" as shown in Figure

9, where n features were extracted fi-om each

image block (Chen 2001; Chang 2000).

5. COMPARISON OF NFRA AND MPC

In this section, NFRA, an artificial intelligence

method, was compared with MPC, a statistical method proven to be effective in recognizing

rust images (Chang 2000). In Figures 10 and 11,

it can be seen that both methods performed

effectively on rust images. In Figure 10, NFRA

seemed to have better performance, because some rust spots in the upper left comer were not recognized by MPC. In Figure 11, both methods

had similar recognition results. From the

333
viewpoint of processing time, MPC, which took

4.5 minutes to process an image, is faster than

NFRA, which took 5 minutes to process one. Through comparison to MPC, the performance

and effectiveness of NFRA can be proven and

justified.

6. CONCLUSIONS

In the construction industry, digital image

processing has been experimented for use in defect recognition of steel bridge painting.

However, there are still some problems

associated with this newly proposed application.

Poor quality images remarkably affect the accuracy of this application, and non-uniform

illumination is usually the cause.

In order to resolve the problem, an illuminationbased image recognition technique combining a

neural network and a fuzzy adjustment is proposed. The neuro-fiizzy recognition approach

(NFRA) segments an image into three parts in accordance with the illumination of the pixels in the image and thresholds an image based on the three areas. The intelligent learning ability of the neural network is utilized for automatic

generation of three threshold values through

input of the three average illumination values

from the three segmented areas. The fuzzy

adjustment is used for smoothing the gray level values of the image pixels along the boundaries.

From the application of NFRA to steel bridge

rust images, it can be seen that NFRA works

effectively on rust image recognition. Through

comparing NFRA to the multi-resolution pattern

classification (MPC) method, it was proven that NFRA is an effective approach for rust image

recognition. The advantage of NFRA is its fault- tolerance characteristic. The disadvantage of

NFRA is the system has to be trained before

being used.

In brief, the proposed NFRA provides a new

approach utilizing artificial intelligence for image recognition that may lead to automation

of steel bridge coating assessment in the near

future.

7. REFERENCES

AbdelRazig, Y., Chang, L. M., and Skibniewski,

M., Automated Quality Assessment of

Constructed Surfaces Through 'Intelligent'

Image Processing. Proceedings of the 16''' International Symposium on Automation and

Robotics in Construction (ISARC), pp 22-24

September 1999, Madrid, Spain (1999).

Abraham, D., Iseley, T., Prasanth, R., and

Wirahadikusumah, R., Integrating Sensing

Technologies for Underground Utilities Assessment. Infrastructure Condition Assessment: Art, Science, and Practice.

Proceedings of the conference sponsored by the

Facilities Management Committee of the Urban

Transportation Division ofthe American Society

of Civil Engineers, 25-27 August 1997, Boston,

MA, USA, pp 316-325 (1997).

Chang, Y. C, Statistical Modelfor MRF Image

Restoration and Segmentation. Ph.D. thesis,

Purdue University, West Lafayette, IN, USA

(2000).

Chen, P. H., Digital Image Recognition Methods

for Infrastructure Surface Coating Assessment. Ph.D. thesis, Purdue University, West Lafayette,

IN, USA (2001).

Chen, P. H., and Chang, L. M., Application of

Neuro-Fuzzy Thresholding to Bridge Painting

Defect Recognition. Proceedings of the 17''' International Symposium on Automation and

Robotics in Construction (ISARC), 18-20

September 2000, Taipei, Taiwan, pp 1105-1110

(2000).

Croall, I. F., and Mason, J. P., Industrial

Applications of Neural Networks. SpringerVeriag New York Inc., New York, NY, USA

(1992).

Fukunaga, K., Introduction to Statistical

Pattern Recognition. 2"'* Edition, Academic

Press (1990).

334
Table 1 . If-Then Rules for Fuzzy Adjustment

IF Positive Difference AND ^4egative Difference THEN Gray Level Adiustment

Large sail

Large Medium Positively SmaU

Large SmaU Positively Large Medium Large Negatively Small IF Medium AND

Medium THEN

SliU Medium SmaU Positively Small

SrruiU Large Negati\-ely Large

Small Medium Negatively Small

Snmll Small StlU

Figure 1 . Schematic Representation of Fuzzy

Adjustment

Figure 3. Illumination-Based Image

Segmentation

Three Illumination Pre-Trained Neural Three Threshold Values Network Values Figure 4. Neural Computing of Threshold

Values

Figure 5. Fuzzy Adjustment on Boundary Pixels

Step 1

Gel the three average Ulumination values from the three segmented areas in each image

Send the three illumination values to a pre-trained neural network

Obtain three threshold outputs

Arrificial Neural Network

Acquire images

' Step 2

Convert images lo gray scale

Step 3

Segment each image

into three areas according to the Uluminaiion values of

the pixels in this image

Say 6

Threshold each image based on the

three segmented areas with the three corresponding

threshold values

Step 7

Defect recognition and calculation

Saps

Use fiizzy logic theory to deal with

the boundaries of the three segmented areas

Figure 2. Neuro-Fuzzy Recognition Approach

(NFRA)

Grayscale Image After Fuzzy Adjustnrteni

J3

U lumi nation -Based

Thresholding Process

Thresholded Binar>' Image Figure 6. Illumination-Based Thresholding

Process

Number o( delect pixels (8) = Defect % (22%)

Thresholded Binary Image

Defect Recognition

Number ot total pixeb (36)

Defect Calculation

Figure 7. Defect Recognition and Calculation

335
Map the clustered results backi

to the fine resolution level and | segment the original image

accordingly

Figure 8. Flow of Multi-Resolution Pattern

Classification (MFC) Method

Coarse resolution

level

Fine resolution

level

• : Image pixels at fine resolution level O : Feature vectors at coarse resolution level

Image blocks Figure 9. Multi-Resolution Pyramid

(a) Original Rust Image (b) Grayscale Image

(c) NFRA Processed Image d) MPC Processed Image Figure 11. Comparison of NFRA and MPC (II)

336
THE APPLICATION OF A 3D SCANNER IN THE

REPRESENTATION OF BUILDING CONSTRUCTION SITE

Naai-Jung Shih

Professor, Department ofArchitecture

National Taiwan University ofScience and Technology

73, Section 4, Keelung road, Taipei, 106, Taiwan, ROC

Abstract: This study offers a method for creating a representation of an on-going

construction site by using a geometric approach. The representation includes the definition of 3D data between the design and construction stages. A method is proposed for using a 3D long-range laser scanner to retrieve information on site occurrences, in order to describe

the building construction process based on what really occurs at a site. 3D scans are made

in stages or at various time intervals. Retrieved shapes are collected in a discrete manner or

in a configuration as a whole. The data collection is conducted wholly or selectively for key

referencing based on registration points. Investigated issues involved are target positioning,

identification, retrieval, tracking of objects, behavior description, characteristic description,

and integration of segmental geometric information. A special procedure is developed to fabricate initiaUzed object parts through a 3D rapid prototyping process to faciUtate communication in substantiated form.

Keywords: 3D scanner, construction

Introduction

VR or 3D modeling approaches are used to simulate tasks to facilitate a better visualization of building construction. (Retik et

al., 2000; Retik & Shapira, 1999; Vaha et al., 1997). However, making a digital

representation of a construction site is a complicated task. Not only are some objects too trivial to be represented, but also the

undefined data may come from the

construction process itself. Starting from the

design stage, 3D computer models are usually

used to facilitate an inspection in the design

stage only, by showing related component

definitions like walls, columns, openings, etc. in a built form. This type of representation may

be sufficient to visualize a building in its final stage or be used as the basic definition of

process. But an actual construction is much

more complicated in terms of objects and

associated motions. Not only are the defined

activities in the construction schedule more

numerous than the original design models can

describe, but also the machinery, workers,

materials, and all objects presented and not included in the original 3D model are left to be

noted only in a text or chart form, based on

judgments derived from related experiences.

Construction site monitoring is an on-going

process that records and monitors data for

immediate and post-construction analysis (Al

& Salman, 1985; Atkin, 1986; Bjoerk, 1993).

The monitoring of a site and the

correspondence of activities defined by a schedule requires object identification and a thorough record of site occurrences. To

achieve this goal, the function of 4D

monitoring focuses on a pre-construction study

for the better management of a site afterward

(Haymaker & Fischer, 2001). During

construction, object identification and

comparison to scheduled activities are essential

functions of site monitoring, and are usually

conducted by supervisors as human-based

tasks. That means site monitoring is an

analogical process. Functions that could enable

the digital identification of an object and the

ability to check whether it is on schedule

would be very helpful.

337
A reversed description method is proposed to improve the disadvantages of 4D technologies

by recording site occurrences in geometric

form and comparing them with the activities recorded on the schedule. The comparison is made as a reference base for evaluating actual progress. In contrast to 4D technology, which

is based on data from the design stage, the

application of a 3D scanner retrieves data on a

construction site to facilitate an as-built

description of models in a precise and reversed

verification manner.

Proposes

This study proposes a method for represent an on-going construction site through a geometric

approach. The representation includes the

definition of 3D data between the design and

construction stages. A method is proposed for using a 3D long-range laser scanner to retrieve

information on site occurrences, in order to describe the building construction process

based on what really occurs at a site. 3D scans

are made in stages or at various time intervals. Retrieved shapes are collected in a discrete manner or in a configuration as a whole. The

data collection can be conducted wholly or

selectively for key referencing based on

registration points.

Systems

The system consists of a long-range (50-100

meters) 3D laser scanner Cyrax 2500 (see Fig.

1) that comes with an editing software.

Cyclone 3.1. The laser can create a matrix of

point clouds up to 999*999 dots in width and

height. Scans can be made individually or

registered onto a large project by referring to

tie-points. Each scan can reach a tolerance of

2mm / 50 meter. The system comes with a notebook computer, which figures IGHz CPU

and 512 MB RAM, to handle the data received on site.

Levels of manipulation

The possibilities for manipulation of scanned

geometric data can be classified into three

levels: • Level I - point clouds: Initial data

retrieval is collected through 3D scans. Each point is initialized with x-, y-, and

z-coordinates only. Points can either be

initialized with absolute coordinates or modified to show relative location. At

this level of three-dimensional

representation, measurements can be

made to estimate linear distance between

two points or between a point and a

plane. Data are in a generic form that opens up a referencing base for following

manipulation. It is suggested that at least one copy of raw scan data should be kept

unchanged in terms of point coordinates,

viewpoint, and the images associated

with scan orientations. • Level II - object initialization: Structural

detail, which represents the components

and their mutual relationships, is created

by fetching or matching points with

geometries like mesh or various shapes of

primitives. In contrast to one-dimensional

representation, volumetric description

enables calculations to be made of

surface area and of object volume.

Relative location between objects

becomes more meaningful for the

boundary of objects is defined and can be

manipulated afterward. In addition, the

volumetric data can be exported to domain-specific applications for further

visuaUzation or analysis. • Level III - attribute designation:

Initialized geometry objects are mapped

with images or textures to illustrate surface attributes. At this level, additional

visual detail is presented. Models created

at previous levels can be used to build up

a more visually attractive scene.

Figure 1 . Cyrax 2500 3D laser scan system, registration points, and site example
Object representation

Why do we need a detailed geometric

description of an object at a construction site, especially when the data retrieved can be too fragmental to facilitate further manipulation?

The reason is a construction site is a very

complicated scene; a detailed description of it can facilitates analysis without the risk of

missing any valuable data. The fragmental

nature of site information can now be changed

by registering the fragments together.

One of the 4D disadvantages actually comes

from the effectiveness of digital representation

of site occurrences. In general, two types of

comparison exist between real objects in physical form and digital form: • An object's digital representation: This

representation comes from scanning or computer modeling of real objects.

Computer models for design evaluation

are usually created before construction

begins. Objects initialized from scanned

point clouds represent a physical form in a finished stage. Nevertheless, the

intermediate stages between design and

construction stages can also be

represented through scans of partially

completed building parts and components

allocated accordingly. • An object's behavior and schedule: The

big picture of a digital construction

representation includes construction

components, component behavior, and

component relationship to the

construction schedule. The representation

of a construction at a certain stage does

not necessary reveal the behavior of its components. This behavior, as described

in a previous section of this paper, provides more details than the

information collected for a certain task.

Process and Methods

To match objects and their roles specified in construction schedule, there are many subtasks have to be conducted. Manipulation

geometric and image data are classified into

three levels of data manipulation: • dimension-related geometric

characteristics check: The initial level of

data manipulation emphasizes a preliminary use of scanned data and

dimension-related checks based on

geometric characteristics. Usage of

scanned data can be shown in analysis,

measurement, record, or visualization.

Measured data can be used for dimensioning, defining relative location,

and recording geometric atributes. For

example, a scan records geometric

information of a steel joint for further

control such as spacing or form works.

Steel-bar-related checks that can be

derived from the scanned data include

spacing, size, numbers, and the

relationship with adjacent components.

Dimension-related checks are made in terms of standard deviation, which

mainly comes from stress-related (pressure, force, fire) deflection or bad

construction quality. Geometry-related

attributes of the scanned data are categorized based on their usage in one, two, and three dimensions. • object identification and behavior

monitoring: During construction, when

objects are scanned and initialized into

geometries, there is a need to tell how

close the scanned geometries are to their product specification. The identification can be categorized into image-based and

geometry-based approaches. Images

usually contain more details than

geometric representation. While the

function of abstraction and segmentation

for images or videos is limited, a pre- design study in a visual form must be

conducted from a modeling approach,

leaving an image approach to be

conducted based upon what is already

constructed as an as-it-is situation. Behavior represents the spatial

movement of construction components

over a period of time. An object's

movement is the response of its own or

external forces along a time span. The

monitoring of behavior notifies us of an

object's activities. With the environment

scan included, the object's response to its surroundings is also specified from itself as well as construction instruments.

339
of segmental geometric

information: Due to unexpected blockage

of other objects, scanworlds have to be

integrated to complete an omni geometric

representation of an object. Scanned data

or image-derived photogrammetric data

offer partially complete descriptions.

Only when an object's movement or

orientation changes so as to lead to more

exposure to the receiving devices or

and is currently made by registration

through referencing points.

Exemplification of 3D scans has been made to construction site for dimension-related check

of geometric attributes. Related studies are also

made to interior design (proofing; as-built scan

for renovation documenting) and a long term

chronicle documenting of construction in the mean time.

**®8^ ' iili Miiiiiiii^ mmms^

1

Figure 2. Two referencing sections through1 whole site

"asm

Figure 3. Photo, point cloud, and RP output (from left to right) of retaining wall section

Figure 4. Two segmented clouds are shown in ordinary (left) and minimum volume (right)

presentation

Figure 5. Center parts of the cloud is segmented into two and stored in difference layers

applications can additional data be

perceived as a complete set. In a chronicle recording, each object may

inherit a different level of data

segmentation. Integrating the chroniclebased segmentation is a challenging task

Section referencing through whole site A 3D scan is suitable for a clear review of a cross-section of a site (see Fig. 2), not just to review an object as a whole from outside. The

process does not have to be undertaken in a

340
traditional manner, made by creating models

and conducting software cuts. The purposes of

the scan are to show: • structural and compositional relationship:

to reveal aggregation and segregation of

building parts • hidden components and spaces: to

illustrate what can be left unseen • part-whole generating process: to create a time-based transformation description of

the "how & why" of occurrences Most important of all, sections are made based on what really occurs at a site. The section is a good manner of spatial representation suitable

for construction quality control, such as for

levels or clearance between slabs. Additionally, initialized object parts can be

fabricated through a 3D rapid prototyping

process to facilitate communication with

substantiated forms (see Fig. 3).

Boundary and box approximation

The number and complexity of objects at a

construction site may be too numerous and

detailed to be modeled exactly. But recording

the presence of objects is still an important

task to be aware of. In order to conduct the

following study, a boundary or box

approximation is conducted for the following

purposes: • simplified volumetric representation: The

boundary representation can be created

based on either current orientation or minimum volume illustrated by a

rectangular wire frame (see Fig. 4). • interference analysis: The presence of a boundary enables an interference check

between adjacent objects in a user defined manner. For example, a designer

or site supervisor can select the

segmented clouds of interest to create a

group, and then compare the boundary

with another group for interference. This

method enhances current interference

checks provided by similar 3D modeling

applications in a systematic review of, for example, a plumbing part and an HVAC

part. Not only does the analysis provide

dimension-related data, but also a diagrammatic illustration of the field of

influence. • data segmentation: In each scan, all points in a cloud are considered as an

entity (see Fig. 5). Although intensitybased segmentation can be conducted, the

result subjects to the distribution of

points and the density may not provide a segmentation that matches the perception

of ordinary experience. Cloud

segmentation is usually manually made

and interpreted as needed.

Trade-off of 3D scan

• Time-saving operation: The data retrieval

is directly made by a scan that takes

about 17 minutes for each scanworld.

Even with the follow-up object

initialization included, the time needed is much less than for conducting computer

modeling from scratch. • Effort-saving operation: The geometric

data are retrieved with x-, y-, and z- coordinates. The effort required to process geometric data is much less than

for modeling that starts from each

component. • Spatial barrier free: Scans can be

conducted from different orientations to retrieve almost all the part of objects,

without being presented close to the

parts. A scan of a distance also helps to prevent possible dangers in positioning

oneself above ground level. • The trade-offs of the 3D scan approach

include: • Tolerance: Scanned data still bears

tolerance in terms of position, distance, or angles per unit length. • Data amount: When a scan is made of

999x999 points, the registration of

several scanworlds can easily accumulate

up to millions of points. The object

initialization and differentiation of

scanned data can still be effort consuming. One way to simplify the task

is to select key objects of interest only or

to apply box approximation

representation.

Conclusion

This study offers a method for representing a

site under construction through the data

retrieved from a 3D scanner. The data are point

clouds that can be stored as records or can be

initialized as geometry shapes afterward for

the purpose of analysis and visualization.

Although trade-offs exist, a site under

341
construction can now be digitized. In contrast

to the traditional 4D approach, the digitized

data provide a referencing base made after the

design stage for forward verification and

backward simulation.

REFERENCES

Al, S. and Salman, T.: 1985, Large-scale

construction projects: management, design

and execution, London: Batsford.

Atkin, B.: 1986, Computer supported

information interchange for construction

projects, p.55-65, lABSE workshop Zuerich.

Bjoerk, B.C.: Autumn 1993, A case study of a

national building industry strategy for

computer integrated construction.

International Journal of Construction

Information Technology.

Haymaker, J. and Fischer, M., "Challenges and

Benefits of 4D Modeling on the Walt Disney

Concert Hall Project," CIFE working paper

#064, January 18, 2001.

Retik, A., Clark, N., Fryer, R.: 2000,

Hasrdiman, R., McGregor, D., Mair, G., Retik,

N., and Revie K., Mobile Hybrid Virtual

Reality and Telepresence for Planning and

Monitoring of Engineering Projects,

http://www.brunel.ac.Uk/depts/mes/Research/G

roups/vvr/vrsig97/proceed/0 1 8/VRSIGTX.HTM.

Retik, A. and Shapira, A.: 1999, VR-based

planning of construction site activities, 8(6), pp. 671-680, Special issue: Organisation and

management ofconstruction.

Shih, N.J.; Tsai, Y.L.; Lai, Daniel, and Chang,

H. Y., " A Preliminary Application of

Panoramic Supervision System in Construction

Site," Proceedings of the 2001 Information

Visualization, pp. 103-8, July 25-27, 2001,

London, England (2001).

Vaha, P., Kansala, K., Heikkila, R. and Kaisto,

I. : 1997, Use of 3-D product models in construction process automation. Automation

in construction, 6(2), pp. 69-76.

342
DATA INTERPRETATION FROM LEUZE ROTOSCAN SENSOR

FOR ROBOT LOCALISATION AND ENVIRONMENT MAPPING.

by

D. W. Seward\ S. D. Quayle^ K. Zied^ C. Pace"*.

ABSTRACT: Two applications for the use of a laser-scanning device are currently

under investigation at Lancaster University. Lancaster University Computerised

Intelligent Excavator (LUCIE) is an autonomous excavator which navigates using

GPS and compass readings. Work is currently concentrating on navigational safety,

for which the rotoscan sensor is employed for obstacle detection, and for possible

self-localisation and environment comprehension in ambiguous operational states. Starlifter is a robotic arm built by Construction Robotics Ltd. The rotoscan sensor

in this instance is to be mounted on the tool head and used as a final positioning

navigation tool. Both these applications rely heavily on the interpretation of the

received data, and the ability to filter out any interference. This paper initially

outlines the mode of utilisation of the laser range finder within such applications

and then proceeds to investigate the implications and potential limitations of such a sensor following the analysis of the sensory data from external field trials. KEYWORDS: collision detection; navigation; robotics; sensors; surface estimation.

1.0 INTRODUCTION

Construction robots have been under

development for many years, although in the

field they have not yet fulfilled their potential

[1]. Although it is relatively straightforward to get the robot to achieve its coarse objectives, it

is considerably more difficult to ensure that the

task is completed safely and accurately. One of

the ways for handling safety is to fence the

robot off away from human beings, and other

disturbances, however this will often remove

the gains of using a robot in the first place. The

alternative approach is to have the robot

respond predictably to its changing external

environment. To do this effectively the robot

needs to accurately sense its surroundings.

Accurate sensing is also critical for tasks

requiring accurate positioning and operations.

With regards to safety, there are numerous

safety concerns that need to be catered for in the safety validation of such a system. Apart

from internal operational integrity, of

fundamental importance in such systems is the

need to ensure correct interaction between the

autonomous system and the environment. The

correctness of such interaction will be

dependent on the autonomous system's

perception of its surroundings, these being

dependent in turn on the exteroceptive sensory

suite of the system, of which the laser scanner

is a critical element.

Correct interpretation of the range sensing data

is also critical for accurate positioning

operations. In this case, accuracy becomes a

critical parameter.

However, the operation of the laser scanner as a range sensing device gives rise to substantial

' Engineering Department, Lancaster University, Lancaster, LAI 4YR, U.K., Tel: +44 1524 593010, Email:

d.seward@lancaster.ac.uk

- Engineering Department, Lancaster University, Lancaster, LAI 4YR, U.K., Tel: +44 1524 593095, Email:

s.quayle@lancasler.ac.uk

^ Engineering Department, Lancaster University, Lancaster, LAI 4YR. U.K., Tel: +44 1524 593824, Email

k.zied@lancaster.ac.uk

Departm.ent of Manufacturing Engineering, University of Malta, MSIDA MSD06, Malta. Tel: +356 32902058,

Email cmpace@eng.um.edu.mt

343
ambiguity in the interpretation of the data,

partly because of the limited information

provided by scanning only in one plane at a time and mainly due to inherent limitations of

the sensory system, such as dependency on

object reflectivity and other physical

parameters, which gives rise to uncertainty in the interpretation of the sensory information.

Knowledge of such limitations in the

information quality from such a sensor is a fundamental necessity in developing a system

that is capable of managing and utilising the

information adequately for the task at hand.

The focus therefore in such an application is to better comprehend;

1 . the application of the rotoscan itself as an additional verification tool for other

exteroceptive sensory data.

2. The inherent limitations in the

interpretation of the rotoscan data for

obstacle recognition, localisation, and

accurate measurement.

This paper thus looks at aspects of concern in the use of such a sensing device for the

underlying applications, given test runs that were performed for the sensor.

2.0 APPLICATION AREAS

The Rotoscan RS3 range sensor under test is a twin laser beam unit, with each beam scanning

90° leading to a 180° flat plane of view. The

range of detection is up to 25m with obstacles

as small as 70mm being detectable. Two

protection boundaries can be programmed into

the sensor, an object boundary and personal

boundary. Both boundaries trigger relays once

broken. Alternatively a serial data string is available.

Two application areas are being considered for

the sensor. The first is Starlifter which aims to combine the laser scanner data with a camera

view to enable accurate final positioning, the

second is Lancaster University's Computerised

Intelligent Excavator (LUCIE) which uses the sensor for navigation and operational safety.

2.1 Starlifter robot

Starlifter is a hydraulically powered portable

robot with six revolute joints. The joints can be

simultaneously locked in any position with

power and control shut down to provide a

stable platform to deploy heavy tools up to 200

kg at any orientation. Starlifter is currently

configured to carry diamond core drilling tools and concrete saws for construction

applications - for further details see reference

[2].

One of the uses of Starlifter is working in hazardous environments in which human

involvement is eliminated. In this case the

robot is located in a remote position from the

operator. Consequently information about the

position of the robot base relative to the

working area is required to enable the operator

to position the robot accurately and safely.

An important use of the range scanner with

Starlifter is to assist in the positioning of the

robot base relative to the working area so that the robot can operate correctly within its working envelope. In this case the laser scanner is attached to the robot base, which is kept level by using balancing rams. The

scanner's object safe field can then be adjusted

for collision avoidance. Working area perception is improved via the use of a vision

system.

2.2 LUCIE

LUCEE is a JCB801 retrofitted with Danfoss

electro-hydraulic valves and three individual

PC 104 units to act as Low Level Controller,

Activities Manager and Safety Manager [1]. The range sensor is mounted approximately

0.5m high on the excavator cab. This allows a

full field of vision around the side of the

excavator for slewing operations, as well as the area immediately around the arm and bucket.

For final implementation a second range

sensor would be placed on the opposite comer

of the vehicle giving a swept coverage of

approximately 300". The area directly behind

the excavator is of lesser importance and can be protected by other sensing means, whilst the

application of the frontal overlap removes

blind spots due to operation of the arm.

The investigation in the case of LUCIE

focuses on the evaluation of safety aspects and

the underlying causes of operational risks for an autonomous excavator in a construction site environment [3].

344
23 Sensor Data Processing

The serial data from the laser range sensor is extracted and processed using a user interface

specially developed using the LabVIEW

graphical programming environment. Figure 1 shows the front panel of the user interface. The

serial data includes start and end identifiers,

the scanner status bits and the user data. The

user data represent the measured distances in mm per 2 degrees of the 180-degree range. A

successive matrix manipulation of the serial data is employed to separate the user data and

the status bits in the data processing section of

the code diagram. Further processing of the user data is performed to visualise the

measured distances in a Cartesian or polar coordinate graph.

The processed data can then be stored for

further off-line evaluation. The data obtained

represents the co-ordinates of a horizontal

plane passing through the laser scanner known

as a segment. Moving the laser scanner up and

down at different levels, or by tilting the scanner, and by feeding back the vertical or tilt position of the scanner a three-dimensional

graph of the working area can be constructed.

Figure 1 illustrates a Cartesian map creation by

stacking a number of scans taken by shifting

the scanner in a vertical plane.

The data is also stored for post processing

purposes for further analytical work. The

processing and post-processing of the data and

the visual representation provide the necessary

tools to determine the operational

characteristics as seen in the experimental tests and conclusions that follow.

3.0 EXPERIMENTATION

A series of tests were carried out with the

range sensor to determine the performance

characteristics in external environments and

under the likely operational conditions to which the sensor will be subjected.

The objective of the tests was to determine the

reading reliability in external environments,

particularly:

i. when the scanner is utilised for the

detection of surfaces that are irregular

and with poor reflective properties

ii. When the scanner is attached to a moving platform and driven over rough terrain, and is therefore subject

to machine vibrations and sudden

displacement changes.

From the results obtained the level of accuracy

of the data, given the specific operating

conditions, was to be determined. In this manner, the interpretation of the data during

operation could be adapted according to the sensor characteristics.

Experimental runs consisted of both static and

dynamic tests, with 180° scans being recorded

every 0.75sec, The total number of scans per

test ranged from 50 to 80. The distance

measurements were extracted through the sensor data processing program and then postprocessed to extract statistical characteristics

of the data.

Final tests were performed on the plotted data

for surface extraction via the Iterative End

Point Fit algorithm [4], to determine the

portability of such a routine, given the quality

of the readings obtained in external

environments.

Figure 2 illustrates a typical test run for the

laser scanner, where the scanner is placed on a mobile platform and with the motion of the scanner as indicated.

3.1 Static Testing

Static tests were carried out with the laser scanner stationary and pointing to a static or

partly static environment (i.e. with random

object presence). Figure 3 illustrates the

scanned data for a completely static test with

figure 4 illustrating the mean and standard

deviation values for the test. The number of

scans recorded for this test was 50.

From the graph it is immediately appreciated

that as distances from the scanner increase the

standard deviation for the readings taken over

the total number of scans increases. Given the

prior measurements from the scanner of the

detected surfaces, the readings give a zero mean error for the vast majority of the

readings. Non-zero mean errors tend to occur mostly on poor reflective surfaces, since the

surface is not adequately detectable.

345
The rate of change of standard deviation

though, is relatively irregular and depends

greatly on the type of surface being detected.

This can be immediately noted from the

detection of vehicles that cause unexpected

fluctuations in readings due to the type of

surfaces (including glass) on which the laser beam impinges. Yet still, an exponential

relationship between distance and reading

variance has been found to suitably fit the vast majority of readings, as would be expected

from the general class of range sensor models

described by Elfes [5].

Spurious readings have also been noted to cause unexpected increases in standard

deviation readings, particularly at edges of

surfaces and mostly at relatively distant

surfaces. This is likely to be caused due to the

possible repeatability errors in the range sensor

output.

In the case of tests involving partial dynainic

features in the environment, where an object was placed within the identified zone for a

relatively short period of time at random, it was noted that the temporary presence of the

object mainly causes a substantial increase in standard deviation in the sensory readings with

a minor effect on mean value. The mean is found to only drop slightly in value as expected due to the presence of shorter

distance measurements within the time interval

where obstacles are present. Similar results were obtained when simulating rain conditions

with standard deviation readings increasing

whilst still maintaining relatively constant mean values.

3.2 Dynamic Testing

Dynamic tests were principally carried out with the laser scanner attached to a mobile

platform and moved over relatively rough

terrain, inducing minor vibrations to the

sensor. Figure 5 outlines the results from such

a dynamic test for the example illustrated in figure 2. In this specific test, the laser scanner

is brought close to the objects at a relatively

linear and constant speed.

To determine the repeatability of the sensory

data given such operating conditions,

successive readings were mapped onto each

other following an angular and linear

translation, so as to give the least mean square

error between successive readings. The least mean square error is given in figure 5(i) as the

test proceeds for each scan taken (a total of 55

scans were taken in this test). Figure 5(ii) and

(iii) outline the estimated linear and angular

translations to obtain the least mean square

error.

From the graphs it is easily noticeable that the root mean square error is much greater than the

standard deviation readings obtained for the

static readings. Most of this increase in the

readings" variance can be said to be due to the

motion of the sensor and the induced

vibrations. Indeed towards the end of the test with the sensor's velocity almost zero, root mean square error values drop down to values

close to those obtained for standard deviation

in the static tests. This clearly indicates a

substantial limitation of the laser scanner for accurate distance readings during motion,

where sensor variance increases as expected

due to the errors induced from the motion

vibrations.

It can also be noted that as distance

measurements increase a higher mean square

error is observed with the range sensor in motion, as would be expected given the results of the static tests. This can be noticed from

figure 5(i) where there is a gradual drop in root mean square error values as the laser scanner is brought closer to the obstacles. This drop is roughly exponential in nature, as would be

expected.

The root mean square error has also been noted

to increase with speed for the same distance

measurements. Again, this would be expected

partly because of the increased 'disturbance'

between two successive scans.

3.3 Surface Estimation

The Iterative End Point Fit algorithm was

applied to each and every set of test scans to determine the performance of the algorithm

given the characteristics of the tests. The

algorithm was found to perform poorly when

applying the plotted readings directly,

particularly under conditions where the

variance between successive readings was

large. This resulted in totally different surface

profiles being generated between successive

346
scans. Better results were obtained for tests with reduced variance in the readings,

although spurious readings did cause sudden

changes in the estimated surface profile.

Improvements to the algorithm were obtained

by introducing a filtering algorithm to eliminate spurious readings between

successive scans and by averaging multiple

readings to smooth out any ambiguities within

single scans.

However, due to the nature of the surfaces

being scanned, the algorithm still gave

erroneous interpretations when not scanning

large flat surfaces, and therefore was not found

to be adequate in its simple form for external

environment surface recognition.

4.0 CONCLUSIONS:

The tests outline a number of interesting

aspects with regards to the use of the Rotoscan

range sensor in the outlined applications.

Primarily it is seen that the reliability and

accuracy of the rotoscan readings degrades

with the motion of the range sensor, mostly as

a result of the induced irregular motion from

the terrain characteristics. However, this does

not diminish to any major extent the

applicability of the sensor given that the

measurements are made beyond the immediate

vicinity of the autonomous system.

Measurements made close to the autonomous

system, requiring high accuracy, , cannot be

made while the scanner is in motion. Accurate

close-up measurements therefore require a

stationary platform, which results in a drastic

reduction in variance. This reduction in variance has also been found to be related

exponentially with distance, and this exponential behaviour has been found to occur

both during stationary and dynamic scans.

The range sensor has been noted to be ideal for

detecting uniform surfaces perpendicular to the

scanning plane. Slopes and other obstacles

with uneven surfaces though detectable are much more difficult to identify, and

distinguish from sensor errors. Indeed, the

detection of such surfaces also induces larger

variance values than for flat surfaces. In addition the ability to distinguish features as distance increase drops drastically, particularly

if such features are of an irregular nature (i.e. not a flat perpendicular surface). It was also

noted that transparent materials such as glass

and water (rain) are not detectable to any

significant extent, resulting mostly in spurious

readings. However spurious readings seem to occur even in the absence of such surfaces and

at a rate greater than for internal environments.

With regards to the iterative end-point fit algorithm for feature extraction, as stated

earlier on, the algorithm was found to act poorly and was only useful in identifying large

flat, perpendicular surfaces. The nature of the

readings and the irregularity of the surfaces

tend to inhibit the correct identification of the

readings given the relatively high variance that occurs in external environments.

The above outline the main limitations for the use of the laser range finder in external

environments. The sensor has been found to perform suitably particularly if relatively

rough estimates of distance measurements are

required, particularly when the scanner is in motion. The relatively high variance in the

readings may not be too much of a hindrance if the data is only required to roughly estimate

the distance from obstacles. In addition, the

variance tends to drop as obstacles get closer

to the autonomous system.

However, the nature of the readings, inhibits

proper identification of environmental features

unless, the sensor is stationary and multiple

readings can be taken. In addition, feature

identification and consequently self- localisation requires the presence of regular

surfaces that are distinguishable for the relative

clutter in the data caused by other irregular and

poorly reflective surfaces. The absence of such

type of surfaces and adequate operating

conditions is highly likely to inhibit the correct application of the sensor for more accurate

identification tasks.

5.0 REFERENCES:

[1] D. W. Seward, S. D. Quayle 'System

Architectures and Safety for Mobile Construction

Robot', Proceedings of the 13* IS ARC, Tokyo,

Japan, 1996.

[2] K. Zied, D. Seward, J.Riehl, A. Dolman: 'The

Development of a Robotic System for Tool

Deployment in Hazardous Environments',

Proceedings of the 17* IS ARC, Taiwan, 2000.

347
[3] C. Pace, D. W. Seward ' A Safety Integrated

Architecture for an Autonomous Excavator',

Proceedings of the l?'^ IS ARC, Taiwan, 2000.

[4] K. Diath, A. Siadat, M. Dufaut, D. Wolf,

'Navigation of a mobile robot by locally optimal

trajectories', Robotica, Vol 17, pp553-562, 1999.

[5] A. Elfes 'Multi-source Spatial Data Fusion

using Bayesian Reasoning', in 'Data Fusion in Robotics and Machine InteUigence', Mongi A.

Abidi, R. C. Gonzales (Ed.), Academic Press, 1992.

F»l lid -fef/ Cr*

Figure 1. The front panel of the graphical user

interface of the laser scanner

Building / Walis

Garage door (reflectivity relatively high and partially open

I I

Container (flat surfaces

Fenced | area

with random'

;

material i inside i

Free Space

CAR CAR

^ Laser Scanner pushed on moving

platform on 'partially' irregular terrain afjprox 0.5m/s

Figure 2. Typical test layout for Laser Range

Sensor

Figure 3. Static sample scan test in polar

coordinates

, Mean

Objects next to fence

. 8. D. (Variance)

Slope Car Car Slope 25000

20 40 60 80 100 120 140 160 180 Scan Angle

Figure 4. Statistical data (mean and standard

deviation) for static test of figure 3.

5 9 13 17 21 25 29 33 37 41 45 49 53

Scan Number

Figure 5. Results for dynamic test in figure D.

(i) Root mean square error for every scan

sample, (ii) estimated incremental linear displacement, (iii) estimated incremental angular

displacement

348
Experiences with Point Cloud Registration *

by

Christoph Witzgall' and Geraldine S. Cheok^

ABSTRACT: The development of LADAR (laser distance and ranging) technology to acquire 3D

spatial data made it possible to create 3D models of complex objects. Because an unobstructed

line-of-sight is required to capture a point on an object, an individual LADAR scan may acquire

only a partial 3D image, and several scans from different vantage points are needed for complete

coverage of the object. As a result there is a need for software which registers various scans to a common coordinate frame. NIST is investigating direct optimization as an approach to numerically registering 3D LADAR data without utilizing fiduciary points or matching features. The primary capability is to register a point cloud to a triangulated surface - a "TIN" surface. If a

point cloud is to be registered against another point cloud, then the first point cloud is meshed in order to create a triangulated surface against which to register the second point cloud. The direct

optimization approach to registration depends on the choice of the measure-of-fit to quantify the extent to which the point cloud differs from the surface in areas of overlap. Two such measuresof-fit have been implemented. Data for an experimental evaluation were collected by scanning a box, and registration accuracy was gauged based on comparisons of the volume and height to known values.

KEYWORDS: LADAR; measures-of-fit; point cloud; registration; TIN; triangular mesh.

1. INTRODUCTION

In recent years, the National Institute of Standards

and Technology (NIST) has investigated

metrological aspects of LADAR (Laser Distance

and Ranging) scanning, addressing both hardware

and software issues [2,4,5]. Hardware calibration

issues include statistics for direct range

measurements, their dependence on target color,

distance, and angle of incidence. Corresponding

experiments will be the topic of a forthcoming

report [2]. In this work, the focus is on software

issues, in particular, the registration of LADAR

scans taken of the same scene from different

vantage points. Statistical experiments aimed at assessing triangular meshing for surface modeling

are described in another forthcoming report [5].

The data for the software experiments consist of

four LADAR scans taken indoors of a

0.914 mxl.219 mxl.524 m

{3fix 4fix 5 ft)

wooden box. The task is to create a triangular

mesh representing the box and surrounding floor. The accuracy of that representation is gauged by

calculating from it the volume and height of the

box. The accuracy of the box dimensions is ± 1.58 cm (1/16 in) and assuming worst case, the

volume error is ± 0.4 % [4].

The registration methods considered here match a

point cloud against a triangulated elevated

surface. The methods are conceived as optimization problems, which apply rigid trans-

' Official contribution of the National Institute of Standards and Technology (NIST); not subject to copyright in the United States. NIST, ITL, Mathematics and Computational Sciences Division, Mail Stop 8910, Gaithersburg, MD 20899-8910,

witzgall@mst.gov

^ NIST, BFRL, Construction Metrology and Automation Group, Mail Stop 861 1, Gaithersburg, MD 20899-861 1, cheok@nist.gov

349
formations to a point cloud in order to minimize a chosen "measure-of-fit", which quantifies the

divergence of the point cloud from the surface.

Several distinct measures-of-fit will be identified,

and the performance of two of them will be

examined using the box data. Evaluations of

additional options are in progress.

Direct minimization of a selected measure-of-fit

differs from the more commonly used ICP

(Iterative Closest Point) approach [1,3]- Direct

minimization, however, is suited to the purpose of

examining the effects of the choice of measuresof-fit.

In a first series of experiments, each of the four scans is registered individually to an exact

triangulated model of the box and surrounding

floor space. The registered four point clouds are combined into a single point cloud, which is then

"cleaned" and meshed to create a surface model

of the box. In a second series of experiments, the

recreation of the box is attempted by pair-wise

registration of the point clouds against themselves

without benefit of an accurate reference. The four

point clouds are examined in clockwise rotation.

A triangulated surface is determined by cleaning

and meshing the first point cloud. The second

cloud is then registered against the surface model

of the first cloud. Once that common frame has

been established, the two point clouds are combined, cleaned and meshed to generate a common surface representation of the first two

point clouds, against which to register the third

point cloud. The process is then repeated by

registering the fourth point cloud against the

surface representation of the other three point

clouds. Finally, all four point clouds — now

registered to the frame of the first ~ are combined,

cleaned, and meshed to produce a model of the

box.

Earlier experiments have been conducted along

the same lines [4]. Here we report the outcomes

of fully automated procedures.

2. MEASURES-OF-FIT

There are two distinct aspects to distance based

measures-of-fit to be identified in this report:

• The definition of generic point-to-surface

distance

• The selection of a "norm" by which to distill a

single number from many instances of such

distances

Commonly considered norms are the

MAX, RMS, and ASD norms.

The MAX norm assigns the maximum absolute

value or "size". The RMS ("root-mean-square") norm averages the sum of squares before taking

the square root. The ASD ("average-sizedeviation") represents the average of the absolute

values. Norms typically provide error estimates in the form of deviations from zero. The MAX norm

will not be considered here, since it is too dependent on "outliers". Each of the other two norms may be combined with a generic point-tosurface distance measure to arrive at a measureof-fit.

Three generic distance measures are considered:

• Vertical distance

• Euclidean distance

• Ray-directed distance

A surface is "elevated" or "2.5 D" if it has a unique projection into the x.j-footprint plane.

The term "TINsurface" (TIN=triangulated

irregular network) is frequently used for

triangulated surfaces that are also elevated, and

only such surfaces are considered in this report.

"Vertical distance" is defined as the absolute

value of the "residual" r- = Zj - C, of a point pi = (a'„ yi, Zi), where z, denotes the elevation of that

surface point Pj = {Xj , , Zj ) which has the same footprint (x„ j,) as the data point The

point p. is uniquely determined, provided the

surface is elevated. The point p. , however, does

not exist if the footprint (a-,, y,) of the data point

lies outside the footprint region of the surface.

This fact gives rise to a natural concept of

"overlap". Indeed, measures-of-fit should apply

350
only to areas of overlap between the point cloud

and the surface.

"Euclidean distance" is the conventional distance

between point /?, = (x„ v„ -,) and the surface, that

is. the smallest distance between and any point on the surface. This distance is always defined. It

is therefore necessary to exclude non-overlap

areas. Roughly speaking, "Ray-directed distance"

is defined as the distance measured in the

direction of the laser beam. The overlap area is determined by those rays which meet both point

cloud and surface.

In this report, only vertical distances are considered together with the RMS and ASD

norms, respectively. In other words, the following measures of fit are considered:

• Vertical distance with the ASD norm

• Vertical distance with the RMS norm

Vertical distance is a natural choice for 2.5D, that

is, TIN surfaces such as terrain representations.

3. OPTIMIZATION PROCEDURE

The intent of optimization-based registration

methods is to identify a rigid transformation

which - when applied to a given point cloud -

repositions the point cloud so as to minimize

deviation from the given surface as quantified by

a measure-of-fit. Rigid transformations may be

characterized by a translation with parameters,

Ax, Ay, Az,

combined with three rotations,

A(p , As, A0,

the yaw, roll, and pitch, respectively [4]. The

value of the measure-of-fit after transformation

may be therefore considered as a function, F, of

the above six transformation parameters, and this function is to be minimized.

In the case of the measures-of-fit based on vertical

distance, this minimization met with several

difficulties. First, in the neighborhood of an

optimal parameter choice, the function F assumes

the shape of a plateau with many local minima in close proximity of each other, and the quality of

the registration tends to be sensitive to the choice

of one of those local minima. Moreover, a global

minimum is typically a disastrous choice. The

automated procedure used for this work searches

among neighboring local minima within a fixed

radius and terminates if no improved measure-offit can be found. This procedure is, of course, very sensitive to the choice of starting point: If the starting point fails to be reasonably close to an

acceptable "solution", the procedure may, in fact,

lead to progressively worse registrations, all the

while "improving" the measure-of-fit. The

challenge is to find measures-of-fit which track

the quality of registration. Those considerations

lead to the following optimization process.

Having evaluated a particular set of parameters

(Ax°, A/, A::", A(p°, A£°, Ae°), the translation (Ac,

Ay, Az) is optimized, keeping the angle

parameters fixed. Here, the two planar parameters

(Ax, Ay) are considered first. This planar

optimization procedure will be described below in more detail. Once that optimization step is completed, the optimal vertical translation Az may

be determined in closed form by subtracting from

the previous value either the mean or the median

of all residuals, depending on whether the

measure-of-fit is RMS or ASD based,

respectively. If the new vertical translation

parameter A^; changes from its previous value,

then the planar optimization procedure resumes. Otherwise, the translation parameters (Ax, Ay,

Az), are considered optimized, and the process moves to the optimization of the angle parameters.

In order to avoid minima that correspond to unacceptable registration results, the optimization

of the planar parameters (Ax, Av) follows a "limited-horizon" search principle: Consider a

circle of radius r around a current "point" (Av°,

Ay°). Search for a "better" point (Ax, Ay) within

this circle only. If found, it becomes the center of

another search within a radius of r around it. If no

such improvement is found, then the planar search

terminates and, as described above, the optimal

vertical parameter A;: is determined. The

procedure consistently decreases with measure-of351
fit function F, and terminates with a particular

"local" minimum.

For the experiments reported here a search radius,

r = 5 cm, was used. If r is too large, it may lead

the search astray. If r is too small, the search may

terminate before reaching a "good" local minimum. As for most registration methods, the success of the search depends heavily on the

choice of the initial parameters ("warm start" vs. "cold start").

There are, of course, many approaches to optimizing a function in a given region. Most

advanced optimization algorithms for minimizing

a function / (^i , ^2 , • • • , ^n), however, stipulate

that a point (^°, , ... , ) is a local minimum

if perturbing single variables does not lead to lower values of /. This is not true for functions

that are not continuously differentiable such as the

measure-of-fit function F.

For this reason, we adopted a search based simply on sampling the search area. With (Aa-^ Ay^) as the center point, concentric sets of 20 trial points

at equal angle increments of 22.5° are considered

for 15 radii ranging from 0.02 cm to 5.0 cm.

Generally, the search starts with radius 1 .0 cm and

if necessary, moves to successively smaller ones

of the proposed radii. If reduction to the smallest

radii fails to yield an improvement, then the

search continues with increasing radii up to the

search radius of 5 cm. As F is calculated for up to 15 X 20 = 300 parameter settings for each planar

search step, the search procedure is computationally expensive and in this form, too slow for real-time purposes.

It was assumed, that the optimization of the angle

parameters does not need to be similarly restricted

except for reasons of efficiency. The planar

rotation Acp is varied in single steps of 0.05°

through a specified bracket and, for each value,

the full translation {Ax, Ay, Az) is re-optimized.

The selection of the roll and pitch parameters As,

AG has as yet not been automated, because

previous experiments [4] suggested that ~ for reasons as yet unclear ~ minimizing those

parameters actually worsened the quality of the

registration.

Given a TINsurface, each specification of a horizontal "cut plane", at elevation z, defines both

a "cut volume" and a "fill volume". The cut volume is bounded below by the cut plane and

above by the surface as far as it extends above the cut plane. The fill volume is bounded above by

the cut plane and below by the surface.

In the experiments to be described, evaluating a sequence of cut volumes was used for determining

volume and height of the box once its surface and

that of the surrounding floor has been modeled.

More precisely, the idea is to create a sequence of

cut volumes, starting with cut planes below the

floor level, as indicated by a fill volume of 0, and

proceeding by increasing the cut level z, in equal

increments of 0.2 cm, until the cut plane clears the

top of the box, as indicated by a cut volume of 0. As long as the cut plane remains below the

surface, the cut volume will decrease linearly, the

slope given by the area of the footprint region of

the surface. As the cut plane starts to intersect the

surface, a transition occurs to the regime in which

the cut plane only intersects the box, and where

the decrease is approximately linear with the box

footprint as its slope. A similar transition is observed as the cut plane moves beyond the top of

the box. The first transition marks the floor level. The second transition marks the top level of the

box. The two transition elevations show up as "spikes" in the sequence of second differences

[4]. The locations of these spikes define the

elevations for floor and box top, respectively.

Thus

box height = box top elevation - floor elevation

box vol. = cut vol. @ floor - cut vol. @ box top

4. EXPERIMENTS

As mentioned previously, four scans of a box

were obtained. These scans were obtained with

the scanner located "in front" of each box comer,

i.e., in each scan, the box top and two sides of the

box were visible. The scans are clockwise labeled

C, D, E, F. The four scans were visually

transformed so that they were in rough alignment

352
to each other, Figure 1. This was necessary as the

registration program assumes small

transformations - this is true for most registration

programs.

Two series of experiments were conducted: 1) registration against an exact model of the box and

2) registration of a point cloud to another point

cloud. For the second series, point cloud C was

arbitrarily selected as the reference point cloud.

Parameters for both series include: 1) starting

point of registration, cold vs. warm start and 2)

measure-of-fit, ASD or RMS. For the starting

point of registration, a cold start was a start at the

origin where (Ax, Ay, Az) = (0, 0, 0) and a warm

start was a start off the origin at some point (Ax,

Ay, Az) close to the expected final registration

point [4]. For the cold start, the (p value ranged

from -2.5° to 2.5°, and the increment size was

0.05°. For the warm start, the range of the 9 value was r starting close to the final value [4]. The

values for e and 0 were set to zero and not changed.

The results of the automated registration are given

in Tables 1 and 2. Summary of results:

• ASD vs. RMS: ASD yields a better

registration in terms of volume and box height

• Registration to box: ASD volume error on the

order of 2 % (cold and warm starts), RMS

volume error of 12 % (warm start) and 137 %

(cold start) - suspect registration got stuck on

local minima.

• Point cloud to point cloud registration: ASD

volume error on the order of 10% (cold and

warm starts), RMS volume error 13 % (warm

start) and 36 % (cold start). • Warm vs. cold start: For RMS, significant

reduction of volume error for warm start. For

ASD, no significant difference in volume

error for warm vs. cold start.

5. CONCLUSIONS

The experiments reported in this paper clearly

show the importance of selecting the correct measure-of-fit for optimizing the registration. In these experiments which were based on vertical

distance, the ASD norm produced a better

registration than the RMS norm in terms of box

volume and box height. Future work will include

using other measures-of-fit such as the "raydirected" distance.

6. REFERENCES

1. Besl, P., and McKay, N., "A Method for

Registration of 3-D Shapes," IEEE

Transactions on Pattern Analysis and Machine

Intelligence, Vol. 14, No. 2, 1992, pp. 239-256.

2. Cheok, G. S. and Leigh, S., Calibration of a Laser Scanner, in preparation.

3. Rusinkiewisc, S. and Levoy, M., "Efficient

Variants of the ICP Algorithm," in Proc,

International Conference on 3D Digital

Imaging and Modeling (3DIM2001)," EEE

Computer Society, 28 May - 1 June, 2001, pp. 145-152.

4. Witzgall, C. and Cheok, G. S., Registering 3D

Point Clouds: An Experimental Evaluation,

NISTIR 6743, NIST, Gaithersburg, MD, May,

2001,41 pp.

5. Witzgall, C. and Cheok, G. S., Triangular

Meshing for Volume Determination, in preparation.

Figures 2 (registration to box) and 3 (point cloud

to point cloud registration) show the final registration of the four scans. The reason for the

misalignment of the last scan in Figure 3 is being

examined.

Figure 1 . Triangulation of Footprint of Roughly

Aligned Scans - Starting Point for Registration.

353
Figure 2. Registration to Box - Final

Registration.

Figure 3. Point Cloud to Point Cloud

Registration - Final Registration.

Table 1 . Registration of Point Cloud to Exact Box Model.

Norm Used

Final Registration Values ASD

(cm) RMS(cm)

Volume

(m^)

Volume

Error (%)

Box

Height

(cm)

Box Ht. Error (%)

Ax

(cm) Ay(cm)

Az

(cm)

A<p

n

Ae

(") Ae

n

Start

at

(Ax,

Ay, A

z)

=

(0,

0,

0)

(Cold

Start)

ASD

C

D

6.550 -8.790

6.605 8.069

-1.000 _ 2.45

0.100 2.35

00

0

0

19.101

25.206

33.877

38.890

1.727 1.63 92.0 0.61 E 14.052 0.443 -3.900 -0.45 0 0 24.910 38.898 F 16.984 13.718 -1.900 1.20 0 0 24.089 38.111

RMS

C 0.370 -6.318 15.072 2.00 0 0 24.071 30.557

4.026 136.97 92.6 1.27 D 1.956 2.566 -27.112 2.50 0 0 27.395 31.056 E 18.636 " -t- 1 -13.208 18.423 2.30 0 0 27.565 33.550

F 19.047 12.148 -26.209 2.40 0 0 27.152 30.860

Start

off

origin

(warm

start) ASD

C 7.443 -9.829 -0.800 2.80 0 0 19.044 33.770

1.671 -1.65 92.8 1.49 D 6.048 8.564 0.100 2.20 0 0 25.211 38.895 E 20.246 -12.027 -1.900 2.25 0 25.005 38.838 F 25.812 6.232 -0.300 2.95 0 0 24.349 38.335

RMS

C 0.372 -6.308 15.072 2.00 0 0 24.071 30.557

1.906 12.20 97.5 6.63 D 8.936 8.038 20.235 2.80 0 0 27.540 33.569 E 18.626 -13.222 18.423 2.30 0 0 27.565 33.550 F 26.623 6.326 19.998 2.65 0 0 27.080 32.873

354
Table 2. Registration of Point Cloud to Point Cloud.

Final Registration Values ASD

(cm) RMS

(cm) Volume(m^)

V olume DUX Rnv DUX Hfni. Norm Used Ax

(cm) Ay(cm) Az(cm)

A<p

( ) Ae(

)

Ae

(°)

Error (%)Height

(cm) Error (%)

C 0 0 0 0 0 0 NA NA

(O'O ASD

D - /.ooy 1 1 A ID U.J J u u 16.910 25.728 o 1.861 9.53 93.3 2.03

II E 20.959 12.599 -1.456 0W.QS7J 14.020 25.250 <

1

Stun F

1 0 inA IZAUO iiS.iii U.jU4 U.OU U u 20.044 32.902 <

<

a

wu C 0 0 0 0 0 0 NA NA

RMS

D -8.122 17.584 -2.904 0.25 0 0 17.684 25.629

Start E 23.224 12.994 -7.367 1.30 0 0 16.829 25.761 2.304 35.59 92.6 1.27

F 14.741 31.937 -7.049 1.20 0 0 18.466 26.677

0 0 0 0 0 0 NA NA

tart) ASD

D -7.829 J

17.43 -0.267 0.35 0 0 16.908 25.727

IS 1.859 9.42 93.0 1.71

UIJI E 17.587 17.063 -1.521 0.10 0 0 14.123 25.330

s F 10.21 22.372 0.508 -0.10 0 0 20.887 33.774

off

origi C 0 0 0 0 0 0 NA NA

D -8.129 17.6 -2.839 0.25 0 0 17.661 25.629

'h 93.6 a RMS

E 16.261 3.19 1.348 0.05 0 0 17.335 27.595

1.913 12.57 2.36

F 12.499 22.903 1.773 0.10 0 0 17.140 25.873

355

Human-Assisted Object Fitting to Sparse Range Point Clouds for Rapid Workspace

Modeling in Construction Automation

by

Soon-Wook KwonS Katherine A. Liapi^, Carl T. Haas^, S.V. S^eenivasan^ and

Jared T. McLaughlin^

ABSTRACT: In large-scale construction sites there are constant needs for rapid

recognition and accurate measurement of objects so that on-site decisions can be

made quickly and safely. Current methods involve full area laser range scanning

systems that can produce very detailed models of a scanned scene, however the

computational and data acquisition time that is required precludes the methods from

being used for real time decision making. This paper presents algorithms to fit objects

to sparse point clouds of measured data in a construction scene, that significantly

decrease data acquisition time, and computational and modeling time. Two basic

fitting and matching algorithms that address construction site material of cuboid and

cylindrical shapes are discussed. Experimental results that indicate that the proposed

algorithms assist an operator to create models of construction objects rapidly and

with sufficient accuracy are also presented.

KEYWORD: CONSTRUCTION AUTOMATION; LASER RANGE FINDER;

LEAST SQUARES METHOD; OBJECT FITTING; OBJECT MATCHING;

WORKSPACE MODELING

L INTRODUCTION

Using automated or semi-automated

equipment on a large construction site requires

rapid recognition and accurate measurement of

objects in the workspace so that timely on-site

decisions can be made. Most methods for modeling work environments rely on analyzing

dense point cloud data, which requires

computationally intensive processing, and

usually takes much longer than the ongoing

construction operation. Low accuracy in extracting objects from dense clouds is an

additional limitation of full range scanning

methods. Since most objects in a construction

site are known and man made, they can be

graphically generated and stored in object

database as parametrically defined object classes

[1]. By exploiting a human operator's ability to

recognize objects in a construction scene, pre- stored graphic representations of construction

objects can be matched and fitted to sensed

data from 3D position sensors deployed in the

construction environment [2] [3]. The ability to extract models of real

' Graduate Research Assistant, Dept. of Civil Eng.,

The University of Texas, Austin, TX 78712,

swkwon @mail.utexas.edu

^ Assist. Professoj, Dept. of Civil Eng., The

University of Texas, Austin, TX 78712,

kliapi@mail.utexas.edu

^ Professor, Dept. of Civil Eng., The University of

Texas, Austin, TX 78712, haas@mail.utexas.edu

Assoc. Professor, Dept. of Mech. Eng., The

University of Texas, Austin, TX 78712,

sv.sreeni@mail.utexas.edu

^ Engineer, Los Alamos National Lab, NM,

jtmclau@sandia.gov

357
world objects in a construction workspace for equipment operations from only a limited

number of scanned points is a significant

advantage of this approach over full range

scanning methods that require intensive

computational load because of range data

processing for dense point clouds which consists

of tens of thousand data points.

This paper presents algorithms that accurately fit and match objects, with regard to location and orientation, to sparse point clouds

which have less than 50 scanned points for each

object in a construction scene. The

implementation of the algorithms will allow a human operator to rapidly construct a world

model from unfiltered real-world range data. With respect to the geometric

primitives most frequently encountered in a construction site, it appears that a few types of

objects can be used to model a wide range of

construction scenes [4]. Cuboids can be used for

fitting and matching structural objects such as columns, box-beams and walls and finishing

objects. Cylinders can be used to fit and match

chemical pipes, ventilation pipes, and concrete

piles. The following fitting and matching

algorithms were developed for each primitive:

1 . Cuboid algorithm

2. Cylindrical object algorithm

2. EXPERIMENTAL SETUP AND HUMAN

ASSISTED OBJECT FITTING AND

MATCHING PROCESS

A single-axis laser range finder, a pan

and tilt unit, and a personal computer were used

for the experimental set up (Figure 1). The

single-axis laser range finder (DistoMemo) that

is mounted on the pan and tilt unit is designed

not only for hand-held operation, but also for

computer use through interface. The

measurements can be remotely taken and

transferred directly into the computer. The range

of measurement of the laser range finder is 100

m with accuracy of ±3 mm. The step size of the

tele-operated pan and tilt unit, which controls

the laser range finder, is of high resolution

(0.01 2857 17step) and its maximum speed is a

little over 607second. Its error is 0.2 cm for

every 10 m in motion.

The sparse points cloud is acquired by

operator picking points to each object using

single-axis laser range finder. The modeling

process involves the following functions:

1 . Select object for scanning (by operator)

2. Acquire sparse point cloud data in the form

of range images

3. Convert range data into xyz coordinates

4. Analyze the features of each surface of the

object

5. Match all of the object surfaces with the

model's surfaces using matching algorithms

6. Fit the object into the point cloud using

fitting algorithm

Figure 2 displays a process diagram of these

functions.

3. OBJECT FITTING AND MATCHING

ALGORITHMS

Graphical workspace modeling can improve construction equipment control and

operations. Equipment operators can use

graphical workspace models as an interactive

visual feedback tool during equipment controls

[2][5].

For the rapid modeling of construction

site objects from sparse point clouds two basic

algorithms were developed that address

construction site objects of cuboid and

cylindrical shape. Since these two types of

primitives consist of 6 planar surfaces (cuboid),

and two planar surfaces and one curved surface

(cylinder), the algorithms were developed as a

surface based fitting and matching method.

Algorithm development and revisions were

based on lab experiments.

By using these algorithms we achieve:

(1) accurate and reliable methods to save computational cost and time, (2) improved

fitting and matching methods to attain real-time

execution, and (3) increased modeling accuracy

with operator's assistance.

The following sections explain the fitting

and matching methods which were developed

and used for rapid workspace modeling:

3.1 Cuboid Algorithm

This section describes how to fit a

sparse points cloud to a cuboid's surfaces using

the k-nearest neighbors and the least squares

358
methods. There is an assumption of this process

that three surfaces of cuboid should be visible in order to acquire data points.

3.1.1 Point Segmentation Using K-Nearest

Neiglibors Method

To find the nearest points for all measured points on a cuboid, a k-nearest

neighbors algorithm was used. The algorithm

finds the nearest two points by computing all the

distances from a scanned point to all other points

[6]. After determining two nearest neighbors for

each scanned point, a group of three-point sets was found. Then, a normal vector for each three- point set was computed. By analyzing normal

vectors, the scanned points were segmented by

each cuboid surface.

3.1.2 Plane Optimization Using the Least

Squares Fitting Method

The least squares method [7] was used

for the best-planar fit of point sets on each

surface of the cuboid after segmentation was

applied.

Since in a planar regression, Y is to be

regressed on two independent variables X and Z, a relationship, where both X and Z, are calculated as deviations from their means, was

used:

E(Y^) = a + fi.-X. + y-Z. (1)

For any given combination of X, and Z, the

expected yield E(Yi) is a point directly above the

plane, shown as a hollow dot in Figure 3. The

actual value of the component of an observed

point is somewhat greater than its expected

value and is shown as a solid dot lying on the

plane. The difference between the observed and

expected values of 7, is shown by the error term

e, and thus the observed value F, is expressed as

its expected value plus the error term e,: Y^=a + /5,-X. + yZ-e, (2)

While moving along the x-direction, y^, is interpreted as the slope of the plane. In the same way 7 is the subsidiary effect of z- To minimize

the error sum of the squares a coefficient is used:

jjY,_-Y)'^.j}Y-a+^-X,+rZf (3)

Taking the partial derivatives of the above

expression with respect tod,0 and 7, and

setting them to zero, finally alpha, beta, gamma

are found. Using this expression, the three

optimized surfaces of the cuboid are computed

(Figure 3). After segmenting all scanned points by

the three surfaces of the cuboid, the points were

projected onto the optimized surface to compute

dimensions.

3.1.3 Determining Intersecting Edges and

Computing Dimensions

The three surface planes of the cuboid,

from which range data were received, intersect

at a point, and each two planes intersect at a line. The intersection of the two planes of the cuboid was found by solving the two linear equations

representing the planes. After applying this for

all three surfaces of the cuboid, the three edges

of the cuboid were determined and matched. A

vertex of the cuboid was also determined.

Figures 4 and 5 show the results of point

segmentation, and matching vertex process. Once the three edges of the cuboid were

defined, the dimensions of the cuboid were

determined as follows: By computing the

distances of all measured points on each surface

to each one of the already defined edges of the same surface, the furthest point from each edge was found. The distances of the furthest points on the surfaces from the three intersecting edges

represent the dimensions of the cuboid.

Figure 6 shows a fitted and matched

model of an object after the application of the

cuboid algorithm.

3.2 Cylindrical Object Algorithm

Four parameters are required for fitting

and matching a solid cylinder: a scalar radius r; an axis vector, a; a center point to determine the

axis vector, c = (X^, Yc. Zc) and a set of scanned

points g= {(Xi, Yi, Zi)} to find out the boundary

of the cylinder. To determine the normal vector,

the "k-nearest neighbors method" was used.

Then, by analyzing normals, the scanned points were segmented by surface (planar or curved).

Subsequently, by projecting all points on the

curved surface onto the planar surface,

parameters r and c were estimated. The least

359
squares method was also used to optimize the

curved surface. The radius of the cylinder was

found as the distance from the center of the

circle to any point on the optimized curve. Projected points on the planar surface are considered end points of different chords in the

circle and used to estimate its center c. An

initial estimate of the radius, r, is found by

r = mean(\c - k]) ( k' = {the points on the

optimized curve of planar surface}). Then the

final values of a, c, and r are found by applying

the least squares method to all scanned data

(Figure 7).

4. EXPERIMENTAL RESULTS AND

CONCLUSIONS

The fitting and matching algorithms

discussed in this paper, are an integral part of a method that involves several other functions

such as: human object recognition, collecting of

range information, grouping of scanned points,

and computing dimensions to final fitting and

matching^ A basic feature of the method is that it takes advantage of human cognitive ability to recognize and classify objects in the workspace;

that is a human operator initiates scanning,

recognizes objects, and controls the system for

data acquisition. In addition fitted and matched

objects are verified by the operator and then

inserted into the workspace model.

Experiments were conducted to determine the efficiency of the human assisted

modeling method. The algorithms, which are based on the least squares method, were found to be useful for modeling construction objects of

cylindrical and cuboid shapes. They were

applied to determine the width, depth, and height

of cuboids, and the diameter, and height of solid

cylinders including the location and orientation.

Table 1 shows an example of experimental

results of a cuboid fitting and matching process. The test results of the algorithms present

approximately less than 1 -degree angular

deviation between model and real objects' axis. Respectively in all tests the size difference

between the modeled and the actual object's

surfaces is less than 5 %. For increased accuracy

further modifications of the algorithms are

required. In general low deviation values and the

low modeling times in Table 1 indicate that a system based on the above geometric algorithms

and a human-guided simple laser range finder can model construction objects rapidly and with

sufficient accuracy.

5. REFERENCES

[1] Cho, Y., Haas, C, Saidi, K., Liapi, K., and

Sreenivasan, S.V.(2001), "Rapid Local Area

Modeling for Construction Automation" Proc,

18"^ International Symposium on Automation

and Robotics in Construction, Krakow,

September

[2] Kim, Y.S. and Haas, C. (2000) "A Model for

Automation of Infrastructure Maintenance using

Representational Forms", Journal of Automation

in Construction, Vol.10, No.l.

[3] Cho, Y. (2000), "Human-Assisted Rapid

Workspace Modeling for Construction

Equipment Operations," PhD Dissertation, The

University of Texas at Austin

[4] Johnson A., Hoffman R., Osbom J., and

Hebert M.(1997), "A System for semi-automatic

Modeling of Complex Environment" Proc. IEEE

International Conference on 3-D Digital Imaging

and Modeling, Ottawa, May

[5] McLaughlin, J. T. (2002), "Rapid HumanAssisted Creation of Bounding Models for Obstacle Avoidance in Construction," Master's

Thesis, The University of Texas at Austin

[6] Duda R. O., Hart P.E., and Stork D.G.

(2001), "Pattern Classification" Wiley Inter- Science

[7] Duran B.S., and Amir-Moez A.R. (1973)

"Linear Algebra of The Plane", Texas Tech

University

ACKNOWLEDGEMENTS

This paper is based on the research

funded by the National Science Foundation

(Grant#: CMS-0000137) and the National

Institute Standard and Technology (Project

NBR: NA1341-02-W-0742). The authors

gratefully acknowledge their financial support

and encouragement throughout this study.

360
Ptimi Projected on Their QpHwfesd Ptsmss

Figure 1 . Experimental Setup

Figure 4. Matching Points and Segmentation

Three Edges oflhe Cuboid ( Sqtrirre : Measured, Circle r Ouesaed

)

Object Measurement

Data Acquisition Hunian iateraction

Data Conversion Object Identification I

Object Matching

Object Fitting

Figure 2. Fitting and Matching Process

i

Figure 3. Surface Optimization

-42

-43

-4S -46,

•47.

-6 \

Figure 5. Three Edges of a Cuboid and its Centroid

Figure 6. Fitted and Matched Cuboid

Gtwped l>( the Algoritlim

Figure 7. Fitted and Matched Cylinder

361
Table 1 . Test Results of the Cuboid Algorithm

Matching Point Modeled Actual Deviation Object X JS71 . 7J.0 1 Hy J / .0 1 o WuJCCl 1 Mr.

1 1 Ml 11 1I

. 7^^ 1 JC> n 0^7

z O J .'tH / n ni 7

:X:. so QRl \J.\JJ\3 -3.

1

n nA7

-41 370 -fl 1 71 X 59.967 60.028 U.L/U 1

;:}';;:;: -5.182 -5.108 yj.yj 1

J

-41.354 -41.492 vy. I DO

59.918 60.032 0.114

Object 4 -5.170 -5.109 0.061 -41.210 -41.621 -0.411 Angular Edge A 1.089

deviation EdgeB 1.824 between edges EdgeC 0.927 Measuring +

Computing titne pts Measuring

{sec.)

Computing

(sec.) Object 1 16 30.00 5.87 35.87 Object 2 18 50.00 5.66 55.66 Object 3 22 60.00 6.48 66.48 Object 4 26 80.00 5.60 85.60
Reconstructing Images of Bar Codes for Construction Site Object Recognition^

by

David E. Gilsinn", Geraldine S. Cheok"\ Dianne P. O'Leary'*

ABSTRACT: This paper discusses a general approach to reconstructing ground truth intensity

images of bar codes that have been distorted by LADAR optics. The first part of this paper

describes the experimental data collection of several bar code images along with experimental

estimates of the LADAR beam size and configuration at various distances from the source. Mathematical models of the beam size and configuration were developed and were applied

through a convolution process to a simulated set of bar code images similar to the original

experiment. This was done in order to estimate beam spread models (beam spread models are unique to each specific LADAR) to be used in a deconvolution process to reconstruct the original

bar code images from the distorted images. In the convolution process a distorted image in vector form g is associated with a ground truth image/ and each element of g is computed as a weighted

average of neighboring elements of / to that associated element. The deconvolution process

involves a least squares procedure that approximately solves a matrix equation of the form Hf = g

where // is a large sparse matrix that is made up of elements from the beam spread function.

KEYWORDS: bar codes, deconvolution, image processing, LADAR, object recognition, sparse

matrix.

L INTRODUCTION

Imaging sensors such as LADARs (laser

distance and ranging devices) are used to rapidly

acquire data of a scene to generate 3D models.

They are used to obtain two- or three- dimensional arrays of values such as range,

intensity, or other characteristics of a scene. Currently available LADARs can gather four

pieces of information - range to an object; two

spatial angular measurements; and the strength

of the returned signal (intensity). Various

methods are used to convert the data, which are

collected in the form of point clouds, into

meaningful 3-D models of the actual

environment for visualization and scene

interpretation. The points within a point cloud

are indistinguishable from each other with

regard to their origin; i.e., there is no way to tell

if a point is reflected from a tree or from a

building. As a result, the methods used to generate the models treat all points identically

and the results are indistinguishable

"humps/bumps" in the scene. Current surface

generation methods using LADAR data require

intensive manual intervention to recognize,

replace, and/or remove objects within a scene. As a result, aids to object identification have

been recognized by the end users as a highly

desirable feature and a high priority area of

research.

The use of bar codes or UPC (Universal Product

Code) symbols has become the universal method

for the rapid identification of objects ranging

from produce to airplane parts. The same method could also be used to identify objects

within a construction scene. This would involve

' Official contribution of the National Institute of Standards and Technology; not subject to copyright in

the United States -National Institute of Standards and Technology (NIST), Information Technology Lab, Mathematical and

Computational Sciences Division, Gaithersburg, MD 20899-8910: dgilsinn@nist.gov

^NIST, Building and Fire Research Lab, Construction Metrology and Automation Group, Gaithersburg,

MD, 20899-8611: cheok@nist.gov

^ Computer Science Department, University of Maryland, College Park, MD 20742: oleary@nist.gov

363
using the LADAR to "read" a bar code. The

concept is to use the intensity data from the

LADAR to distinguish the bar pattern. The

advantage of this concept is that no additional

hardware or other sensor data is required to gather the additional data. The basis for this concept lies in the high intensity values obtained

from highly reflective materials.

The challenges are the ability to read the bar

code from 100 m or greater, distinguish bar code

points from the other points in the scene, capture

a sufficient number of points to define the bar

code for correct identification, and the ability to read bar codes that are skewed.

At ISARC 2001 [1] methods of determining the

appropriate material for the bar codes and

determining if the use of bar codes was viable were reported. The results from these efforts showed that at distances beyond 20 m, the

intensity images were too blurred to be readable

and that image processing techniques were

necessary to reconstruct the image. The blurring or convolution of the image is a result of the low

resolution (number of pixels/unit area; a consequence of the instrument's angular

resolution) of the intensity images at larger

distances and of distortion of the intensity image

by the LADAR optics. As a result, an

investigation of possible methods to de-blur

(deconvolve) the intensity images was

conducted. Deconvolution of the image

involves reversing the convolution implying that

if the convolution process was known, the image

may be reconstructed. The results of the

deconvolution study are reported here.

2. BEAM SIZE AND DIVERGENCE

ESTIMATION

The data for determining the beam size as a

function of distance was obtained as part of an

experiment to determine the range accuracy of

the LADAR as a function of the angle of

incidence of the laser beam and distance. An

infrared viewer was used to see the projection of

the laser on the target so that an outline of the

beam could be drawn. The outline of the beam

was drawn by two or more observers and the

measurements were averaged. The LADAR

used consisted of three laser diodes. The

projection of the laser beam on the target was

seen as a bright rectangle for distances less than

10 m and three bright vertical bands separated

by dark bands for distances greater than 10 m. A

schematic of the beam is shown in Figure 1 . The

measurements are given in Table 1

.

The average vertical beam divergence was 2.14

mrad (o = 0.39 mrad) and the average horizontal

beam divergence, excluding an outlier (negative

divergence) was 1.86 mrad (a = 0.44 mrad).

The average beam divergence (horizontal and

vertical combined) was 2.01 mrad (a =

0.43 mrad) - compared with the manufacturer's

specified divergence of 3 mrad. The lower

experimental value was likely a result of the

inability of the unaided human eye to detect the

faint edges of the laser beam projection. A

schematic of the diverging beam is shown in Figure 2.

3. OPTICS MODEL FOR BEAM

DISTORTION

Discretize the ground truth image by defining: 0 = yi<>'2< ••• <y«/= 1,0 = zi< Z2< ... <z„f= 1, A yi = yi+i- yi, = A zj = Zj+i- zj, = A . The

intensity at patch AyiAzj is given by fiyi

,

Zj ) A y, A Zj where / is a function of (y, z) expressing the intensity response at some point

(yi\ Zj*) in the patch. Due to distortions, the

LADAR image of the response from the bar

code surface is smeared out into some form of

blurred spot shown in Figure 3. The distorted

image will be taken as a subset (to be defined

below) of the ground truth image for simulation

purpose. Points in the distorted image will be

identified by (F, Z) and those in the ground truth image by (v, z). These are different notations for

points in the same axis system. The distortion at a point (y, Z) due to a point (y, z) can be

described by a function h(y, z', Y, Z), called the

Beam Spread Function . For most practical

purposes, the Beam Spread Function can be

considered translation invariant in the sense that

its distortion value only depends on the distance

between {Y, Z) and (y, z) so that h has the form

364
h(Y-\\ Z-z) (see Figure 4). The incremental

distortion effect at (7, Z) due to a neighboring

patch of i}',z) is g(Y, Z) = h(Y-y, Z-z)

fi}', z)/^yAz.To describe the total effect g{Y, Z)

of all of the points (y, z) in the ground truth image one sums over all of the patches in the

ground truth image. As the number of grid

points nf in the ground truth image grows and

the patch size tends to 0, the sum can be

replaced by an integral. This integral is called a convolution integral .

g{Y, Z) =

j

°°\hiY -y,Z- z)f{y, z)dydz

Assume that the distorted image g is sampled at points (y = (/7-l)A,Z^ = (^-DA) for p, q =

1, ... , ng, forming a vector G of ng' elements.

Let h be sampled at (ma)' points (/A, ;A) for i,j = -k, -k+l, k-l, k. This gives a total of ma'

data values H , where ma = 2k+ 1 , and we define

all other values of our approximation of h to be

zero. Assume that we approximate the ground

truth image by /((/ -1)A,(;-1)A) = F(/,;) for i,j=\,...,nf, and again arrange these values as a vector. Then our convolution integral can be

approximated by

This gives us ng^ linear conditions on nf

unknowns F(i, j). Let H be the matrix derived

from the values H so that our approximation

becomes G = HF.

4. COMPUTATIONAL ASPECTS FOR

IMAGE RESTORATION

Since the ground truth image F is larger than the

distorted image G there are more degrees-offreedom involved in reconstructing F from a measured G. A computable approach is to determine F in a least squares manner to satisfy

nun||//F-G||.

This is an ill-posed problem since there may not be a single solution. In fact it is known that if F

is combined with high frequency sinusoidal data,

then, under convolution, it produces the same G.

A penalty term can be added to this minimization problem that puts a premium on

the size of F selected. Introduce A > 0 and

form the following minimization problem

mnj ||fff-G|| + A||F||

}

The second term is called a regularization term

and its function is to control the magnitude of

the final F. In practice, A is selected as a small

positive number.

We solve the least squares problem using the

LSQR algorithm of Paige and Saunders [2]. This algorithm never modifies elements of H

and uses the matrix only to form products Hy

with various vectors y. Thus we need only store the ma' coefficients of H rather than the ng' x nf matrix H.

5. CONCLUSIONS

In order to determine the effect of beam spread

models on ground truth images, one has to determine the nature of ground truth. The

LADAR returns intensity levels in the range 0 to 255. From measured images, it was determined

that the intensity of the return signal of the board on which the bars were mounted was

approximately 150 and the intensity levels of the

bars were approximately 250. Simulated ground

truth data files were created for three sets of

barcodes (see ISARC 2001 [1]) with an example

of 25.4 mm (1 in) bars shown in Figure 5. Based upon the measurements of the beam

spread function three beam matrices were

created to represent the spread function at 10 m,

20 m, and 40 m. Since it was difficult to obtain a precise measurement of the beam spread

function, matrices representing the three spatial

beam spread configurations were created. They

365
were defined in sucti a manner that the area

representing the dark regions was set to zero and

the constant value assigned to the hght areas was

chosen so that the volume under the bright bars

summed to unity. With the simulated barcodes

and the simulated beam spread functions given,

convolution calculations were performed in order to determine how close the simulated

distorted images compared to the measured

images. The simulated distorted images did not produce the horizontal spread distortion that the

measured images produce. Although both the

ground truth and beam spread images were

simulated it is likely that the lack of prediction was produced by poorly understood beam spread

functions. Since the preliminary measurements

of the beam spread functions using an infrared

scope were crude, this is not surprising. What

was surprising, though, was that when the beam

spread function at 10 m was used to deconvolve

two images it was possible in a limited fashion

to recover the basic details of the ground truth images. In particular, for the case of 25.4 mm

( 1 in) bars at 10 m, the measured data is given in Figure 6 and shows the lower three bars

enmeshed together. The simulated beam spread

function for 10 m was used to recover the

ground truth image, and the result is shown in Figure 7. An attempt was then made to reconstruct the ground truth image for the

50.8 mm (2 in) bars at 10 m with the same

simulated beam spread function. Figure 8 shows

that the full reconstruction was not completely

obtained. This suggests that the beam spread

function might be influenced by the individual

image being deconvolved, especially in the

presence of noise. It, therefore, is clear that the

nature of the beam spread function and its relation to the image being deconvolved is significant. An attempt was then made to construct the beam spread function using the

least squares algorithm but in this case, set the

matrix H to be the ground truth image and the

unknown F to be the unknown beam spread

matrix. Figure 9 shows the distorted image

created for (25.4 mm (1 in) bars using the best

fit Beam Spread matrix. It is very close to the

actual data measured for the same bars as given

in Figure 6. All of the results, though, point to the fact that reconstructing ground truth from

distorted LADAR images is critically dependent on knowledge of the Beam Spread Function and

how it relates to individual images.

6. REFERENCES

1. W. C. Stone, G. S. Cheok, K. M. Furlani, D.

E. Gilsinn, "Object Identification Using Bar

Codes Based on LADAR Intensity", Proc. of the 18"' lAARC / CIB / IEEE / IFAC

International Symposium on Automation and

Robotics in Construction, ISARC 2001, 10- 12 September, 2001, Krakow, Poland.

2. C. C. Paige, M. A. Saunders, 'Algorithm

583: LSQR: Sparse Linear Equations and

Least Squares Problems'. ACM-Trans.

Math. Software, Vol. 8, No. 2, Jun. 1982,

pp. 195-209

3. G. Golub, W. Kahan, 'Calculating the

singular values and pseudo-inverse of a

matrix', J. SIAM Numer. Anal., Ser. B, Vol.

2, No. 2, 1965, pp. 205-224.

366
cW

Figure 1. "a", "c" and "e" are the widths

of the bright bands and "b" and "d" are

the widths of the dark bands.

10 m 20 m 40 m

L 27.5 56.2 108

W 52.4 64 111 a 12.7 15

b 13.2 25

c 14.7 22.3

d 11.7 30.5

e 12 18

Table 1. Average height and

widths in millimeters of the bright

and dark bands of the beam shown

in Figure 1.

Figure 2. Beam divergence.

Value at image is weighted average

of neighboring points

in the ground truth image D

Distorted or Blurred Image Ground Truth Figure 3. Distortion on the image caused by

averaging of pixels in the ground truth image.

nf

Ground Truth Image ^ ng

g(Y, Z)

Distorted Image

H(Y-y, Z-z)/^^'^^

(y,z) f(y, z)

Figure 4. Distorted image overlaid on the

ground truth image.

25.4 mm (I in) Bars

Figure 5. Simulated 25.4 mm ( 1 in) barcodes.

367
Figure 6. Measured intensity data by

LADAR for 25.4 mm ( 1 in) bars.

B3r-2-Deblurred

Figure 8. Partial reconstruction of 50.8 mm

(2 in) bars at 10 m.

Figure 7. Reconstructed 25.4 mm (1 in) bars

at 10 m.

From

,eered Fitter

Figure 9. Distorted 25.4 mm (1 in) bars

based on a least squares estimate of the Beam Spread Function.

t

368
ARTIFICIAL INTELLIGENCE BASED QUALITY CONTROL

OF AGGREGATE PRODUCTION

by

Hyoungkwan Kim\ Carl T. Haas^, Alan F. Rauch^

ABSTRACT: This paper discusses a quality control method, based on artificial neural networks, that enables a plant operator to quickly detect property variations

during the production of stone aggregates. The group texture concept in digital

image analyses, two-dimensional wavelet transforms, and artificial neural networks

are reviewed fu"st. An artificial intelligence based aggregate classification system is then described. This system relies on three-dimensional aggregate particle surface

data, acquired with a laser profiler, and conversion of this data into digital images.

Two-dimensional wavelet transforms are applied to the images and used to extract important features that can help to differentiate between in-spec and out-of-spec

aggregates. These wavelet-based features are used as inputs to an artificial neural

network, which is used to assign a predefined class to the aggregate sample.

Verification tests show that this approach can potentially help a plant operator

determine, in a fast and accurate manner, if the aggregates currently being

produced are in-spec or out-of-spec.

KEYWORDS: aggregate, artificial neural networks, group texture, laser profiling,

wavelet transforms

1. INTRODUCTION

The importance of using high quality stone aggregates is gaining increased recognition

within the construction industry. To rapidly

acquire the data needed to ensure that aggregate products have the desired properties,

automated methods for characterizing

construction aggregates have been developed.

By implementing automated methods of

measuring basic material properties in testing

laboratories, at large construction sites, and so

forth, construction material quality can be

improved.

Digital image analysis (DIA) has been widely

studied as a means of automating aggregate

tests [1]. In DIA, an aggregate sample from the

production stream is photographed with a camera; this image is then digitized for

computer analysis. To extract size information

on each particle in the digital image,

algorithms for image segmentation and size

measurement are used. That is, after the

particles in the image are separated by the

segmentation algorithm, all of the particles are measured, one by one, in a computationally

intensive manner.

However, if the application is primarily

concerned with variations in the product rather

than complete sample characterization, a much

faster approach is possible. For example, in aggregate production plants, product gradation can be monitored by tracking variations in the

percent passing a selected sieve size [2]. By

monitoring variances in this one measure, plant

operators can know when the production

process needs to be adjusted. The method of

extracting simple variance information

facilitates faster analysis because it does not

require the complete characterization of each

' Post Doc. Researcher, Department of Civil Engineering, The University of Texas at Austin, Austin, TX 78712,

USA, hyoungkwan@mail.utexas.edu.

" Professor, Department of Civil Engineering, The University of Texas at Austin, Austin, TX 78712, USA,

haas @mail.utexas.edu.

^Assistant Professor, Department of Civil Engineering, The University of Texas at Austin, Austin, TX 78712,

USA, arauch@mail.utexas.edu.

369
particle following segmentation. In addition,

this approach can potentially enable the plant

operator to assess the properties of aggregates on a conveyor belt without acquiring discrete

samples from the belt.

This paper proposes a neural network based

quality control method for aggregate

production. The Laser-based Aggregate

Scanning System (LASS) [3], developed at the

University of Texas at Austin, is used to acquire accurate three-dimensional (3D) data on stone particles. To generate meaningful

features for input to the neural network, twodimensional (2D) wavelet transforms are suggested for processing the 3D data. Aided by

the multi-resolution feature of the wavelet

transform, the neural network is expected to provide the necessary information for real-time

quality control during aggregate production.

This paper begins with a literature review

covering group texture, 2D wavelet transforms,

and artificial neural networks. Then, an

aggregate classification system is proposed for

monitoring variations in an aggregate product

stream. This system is focused on detecting

variations in particle size distribution

(gradation). Finally, experimental results and

conclusions are presented.

2. LITERATURE REVIEW

2. 1 Group Texture and Wavelet Transforms

In the machine vision field, texture is defined

as "something consisting of mutually related

elements" [4]. Namely, texture can mean a combination of texture elements and the

relation between each element. In an attempt to identify the most suitable method for

objectively quantifying the properties of an

aggregate sample, machine-vision-based

texture quantification (or classification)

methods were investigated. These methods

included the use of statistical moments, co- occurrence matrix, edge based method. Law's

energy, surface based method, fractal geometry, mathematical morphology, and

Fourier transform.

Wavelet analysis, where edges on various

scales are detected and processed, is a method

that belongs to the edge based texture

quantification methods. A wavelet analysis

decomposes a signal into a group of linear

combinations, with each combination having

different resolutions. This transform is conducted using the finite length of a basis

function called a "mother wavelet". The

mother wavelet is compared with the signal to be analyzed by changing its length (dilation)

and location (translation) in order to find

where and how much each dilated and

translated version of the mother wavelet

coincides with the signal. The dilation and

translation mechanism of the mother wavelet

enables not only production of localized

information in the space and frequency

domains, but also effective representation of

the data signal.

A comprehensive explanation of 2D wavelet

transforms can be found in [5,6,7]. With a 2D

wavelet transform, a digital grayscale image

can be represented as:

f(x,y)= £ Y.^^{j,k)(p(x- j)(p(y-k)

+ ZZ Y.d..oihk)(pi2- X- j)xi/{l'' y-k)

+ Z % f^d.,(j,k)y/(2-x-j)<pa-'y-k)

+ Z Z f,d^ Aj,k)y/i2-' X- j)y/(2-' y-k)

where f(x, y) is the grayscale image, ^ is the scaling function of the ID wavelet

transform, y/ is the wavelet of the ID wavelet

transform, j and k represent a location in the

wavelet domain, / represents a decomposition

level, and Cq and J. y (/ = 0, 1, 2) are

coefficients for a scaling function and

wavelets, respectively.

2.2 Artificial Neural Networks

Artificial Neural Networks (ANNs) are pattern

recognition systems that imitate biological nervous systems. ANNs can be used either as

classifiers, to allocate a predefined category to the data representing a given case, or as estimators for predicting a certain value based on the given environment. A typical ANN

consists of three different layers: the input

layer, hidden layer, and output layer. While

there is only one input layer and one output

layer, the number of hidden layers used usually

370
depends on the degree of complexity in the

pattern recognition problem. Each layer has one or more processing elements called neurons (or nodes), which are typically

connected with those of the next layer. These

neurons take input signals, process them, and

produce output signals. These signals are weighted and transferred using the connections

between neurons.

To operate properly, ANNs must be trained

with many examples. This study uses a backpropagation training algorithm, one of the

simplest and most general methods for training

multilayer neural networks [8]. In the

backpropagation method, the network

propagates the errors, determined by the

differences between the actual and desired

output values, backward (from the output layer

to the input layer) while adjusting the

connection weights between neurons. A more

comprehensive treatment of ANNs can be

found in [8].

3. PROPOSED METHOD

3.1 Laser-based Aggregate Scanning System

The "Laser-based Aggregate Scanning

System" (LASS) was developed to acquire 3D

aggregate particle surface data. The LASS

consists of a laser line scanner, a horizontal

gantry system, and a personal computer (Fig.

1). The laser scanner, which is mounted on the

gantry system, passes over an aggregate

sample, scanning it with a vertical laser plane.

The laser line scanner can move approximately

1.5 m along the Y axis while performing 25

scans per second, with a scan width (X axis) of

120 mm and a scan height (Z axis) of 220 mm.

i-- Power Source Power Line

Control

Motion Controller

t t

Computer

Support Frame

Aggregates Scanning Platform

Figure 1 . The Laser-based Aggregate Scanning

System (LASS).

The resolution of the LASS data is as good as 0.3 mm, 0.1 mm, and 0.5 mm in X, Y, and Z

directions, respectively. A comprehensive

description of the LASS can be found in [3].

3.2 Artificial Intelligence Based Aggregate

Classification System

Texture can be defined as a combination of

texture elements and the relations between

each element. Aggregate particles can

correspond to texture elements with certain

special relationships with each other. If a group of construction aggregates is scanned

into an image, this image can be considered as a texture. One method to quantify texture uses edge information in the image. For example,

the number of edge pixels in a certain area can be used for texture description.

Texture descriptions are highly scale

dependent [4]. For instance, edges detected

with high resolution would be ignored if low

resolution was used. However, wavelet

analyses can be used to advantage in overcoming this problem. 2D wavelet analysis

provides vertical, horizontal, and diagonal

edge information on various scales. With this information, it is possible to quantify the

texture of an aggregate image effectively and

objectively. Then, by comparing this quantified information between in-spec and

out-of-spec aggregate images, an aggregate

group with an out-of-spec gradation can be

detected as unacceptable.

A flow chart for the proposed aggregate

classification system is shown in Fig. 2. Aggregate samples are first scanned by the

LASS to obtain 3D laser images. The height

value of each data point is represented by a grayscale value ranging from 0 to 255. Then,

2D wavelet transforms are applied to the

images so that the following features can be

obtained:

ttt\d,Ahk) (2)

Basically, the features are energies (summation

of absolute values of all the elements) of the

decomposition level i. Since particles are randomly spread and scanned, no distinction is necessary between horizontal, vertical, and

371
diagonal edges in the wavelet transformed

image. This is why d^, d^, and cf, can be

added together. In other words, all the edge

information on a resolution level is summed to obtain one feature value, which is then put into a classifier to determine the appropriate

categories for the aggregate sample. In this approach, the number of decomposition levels

in the 2D wavelet transforms applied to the

image is naturally the maximum number of

features that can be used in the proposed

classification system.

Aggregate

sample

I

3D laser Profiling I

3D grayscale image

creation z

2D wavelet transform I

Neural Network

Classification

Figure 2. Artificial intelligence based

aggregate classification system.

In this study, an artificial neural network

(ANN) is used as a classifier to determine

whether or not an aggregate sample is out-of- spec. Since this research is focused on

detecting only variations in particle size

distribution, the following three groups

(categories) are defined: Norm, Large, and

Small. Group Norm is composed of 100 % of

the same size of aggregates (which would pass

a certain mesh size and be retained on a certain

smaller mesh size). Group Large has a certain

percentage of larger particles and Group Small

has a certain percentage of smaller particles.

Thus, this system can classify an aggregate

sample into three categories: in-spec, out-ofspec with larger particles, and out-of-spec with

smaller particles.

In a field application, these classifications

could be used to adjust the aggregate

production process. If the plant operator finds

that the aggregates currently being produced

are classified as out-of-spec with larger

particles, the crusher settings could be

tightened to produce fewer oversized particles.

If the categorization indicates out-of-spec with

smaller particles, the crusher's settings could

be opened to produce fewer small particles.

Depending on the specific needs of the

aggregate producing plant, more than three

categories could also be defined.

Fig. 3 shows the neural network model for the

aggregate classification system. It is composed

of an input layer with two neurons, a hidden

layer with five neurons, and an output layer

with three neurons. The number of input

features naturally determines the number of

input neurons, while the number of output neurons is determined by the number of

categories used to classify the aggregate

samples. A sigmoid nonlinear function and

backpropagation with a momentum learning

method were adopted for training the neural

network model.

Hidden

layer

Output

layer

Energy 6

Energy 7

Group

Norm

Group

Large

Group

Small

Figure 3. Neural network model for the aggregate classification system.

Sixth and seventh energy levels, which

correspond to relatively low frequencies in the

wavelet domain, are fed into the neural

network model. These two features were

selected because preliminary experiments

indicated that those energy levels are most apt

to differentiate between aggregate groups with

different gradations. This preliminary

examination of the energy features saves a

significant amount of computing effort by

reducing the complexity of the neural network.

It is also worth noting that the network has

three output neurons matching the three

categories defined as Norm, Large, and Small,

whereas the number of neurons for the hidden

layer was determined from trial and error.

372
The aggregate classification system was

implemented using the C++ programming

language, LabView (a graphical programming

language), the IMAQ Vision image processing

tool, the Wavelet and Filter Bank Design

Toolkit, and the DataEngine (an off-the-shelf

Neural Network subroutine). LabView, IMAQ

Vision, and the Wavelet and Filter Bank

Design Toolkit are all products of National Instruments (Austin, Texas), while the DataEngine is a product of MIT GmbH

(Germany).

4. EXPERIMENTS

To check the validity of the group texture and

artificial intelligence based aggregate

classification method, the proposed system was used to classify three aggregate samples

described in Table 1. Norm particles. Large

particles, and Small particles are defined as

particles that fall within the size ranges of 1/2"

to 3/4" (12.7 mm ~ 19.0 mm), 1" to 1-1/4"

(25.0 mm ~ 31.5 mm), and No. 4 to 3/8" (4.75

mm ~ 9.5 mm), respectively. Then, Group

Norm consists of 100 % of Norm particles.

Group Large has 50 % of Large particles and

50 % of Norm particles, and Group Small has

50 % of Small particles and 50 % of Norm

particles. These aggregate samples were randomly spread on the scanning platform of

the LASS such that there are no overlapping

particles. They were then scanned and

converted into digital images. Fifty-six images were created for each group, resulting in a total of 168 images. Each image is 566 by 180

pixels and covers a rectangular area of 120 mm

by 50 mm. Eighty-four images (half the total number of images) were used to train the

neural network model described in Fig. 3, while the other 84 images were used to test the

classification system.

To obtain the energy values that are representative of each aggregate sample, a running (moving) average value of every five

images was used instead of separate energy

values for each image, as follows:

1 /+4 RA=-yi, (3)

where /M is a running average and / is an energy feature of one image. In other words,

for every five images in the same aggregate

group, the energy values were averaged to produce more stable and representative

features. Note that this running average

approach reduced the total number of training

sets (or test sets) from 84 to 72.

Table 1.1 Description of aggregate test samples.

Group Size fraction % kg

Group

Norm

No. 4 ~ 3/8"

(4.75 mm ~ 9.5 mm) 0 0

1/2" ~ Va" (12.7 mm ~ 19.0 mm) 100 5

1" ~ 1-1/4"

(25.0 mm ~ 31.5 mm) 0 0

Group

Large

No. 4 ~ 3/8"

(4.75 mm ~ 9.5 mm) 0 0

1/2" -3/4" (12.7 mm - 19.0 mm) 50 2.5 1"~ 1-1/4"

(25.0 mm ~ 31.5 mm) 50 2.5

Group

Small

No. 4 ~ 3/8"

(4.75 mm ~ 9.5 mm) 50 2.5

1/2" ~ y4"

(12.7 mm - 19.0 mm) 50 2.5

1" - 1-1/4"

(25.0 mm - 31.5 mm) 0 0

Table 2 shows the classification results. With

only one incorrect classification in identifying

Group Large, the 99 % classification accuracy

demonstrates that the group texture approach,

in conjunction with artificial intelligence

classifiers, is a promising method to detect

variations in an aggregate production stream.

Table 2. Classification results. Group

Accuracy Accuracy

( Number) (%)

'

Group Norm 24/24 100

Group Large 23 / 24 96

Group Small 24/24 100

Total 71/72 99

5. CONCLUSION

This paper explored the possibility of using

group texture of aggregate images in conjunction with an artificial neural network to quantify gradation properties. First, an

aggregate sample was scanned by the Laser- based Aggregate Scanning System, and

373
converted into 3D images. Then, 2D wavelet

transforms were applied to those images to extract wavelet coefficients and calculate

energies at different scales. Finally, these

energies were used as inputs to an artificial neural network that assigns a predefined class to the aggregate sample. Verification tests show that this approach can potentially classify

aggregates in a fast and accurate manner.

Further work is needed to develop and verify

the proposed artificial intelligence based

approach. First, while reducing gradation

variations in the training samples, different

network architectures can be constructed and

evaluated to optimize the neural network

model. This requires testing with different

numbers of neurons, different numbers of

hidden layers, different transfer functions, and

different learning methods. Second, efforts are needed to develop good features that can

represent the aggregate properties well. A

system using the standard deviation or other

statistics of the wavelet coefficients at a certain

decomposition level might be successful in

grouping similar aggregate samples. Third,

different classifiers, such as the K-NearestNeighbor method. Linear discriminant

function. Fuzzy logics, etc. [8], could be

investigated. These relatively simple methods

are sometimes more effective than complicated

neural networks.

6. ACKNOWLEDGMENT

Funding for this study was provided by the

International Center for Aggregates Research

(ICAR).

7. REFERENCES

L Browne, C, Rauch, A. F., Haas, C. T., and Kim, H. (2001). "Comparison tests of

automated equipment for analyzing

aggregate gradation." Proc, 9th Annual

Symposium, ICAR, Austin, Texas.

2. National Stone Association. (1993), The

Aggregate Handbook, Mercury Press,

Rockville, MD.

3. Kim, H., Haas, C. T., Rauch, A. F., and Browne, C. (2001). "A prototype laser scanner for characterizing size and shape

parameters in aggregates." Proc, 9th

Annual Symposium, ICAR. Austin, Texas.

4. Sonka, M., Hlavac, V., and Boyle, R. (1999). Image Processing, Analysis, and

Machine Vision, PWS Publishing, Pacific

Grove, CA.

5. Daubechies, I. (1992). Ten Lectures on

Wavelets, CBMS series, SIAM,

Philadelphia, PA.

6. Mallat, S. (1999). A Wavelet Tour of

Signal Processing, Second Edition,

Academic Press, San Diego, CA.

7. Rao, R. M., and Bopardikar, A. S. (1998).

Wavelet Transforms, Addison Wesley

Longman, Inc., Reading, MA.

8. Duda, R. O., Hart, P. E., and Stork, D. G.

(2001). Pattern Classification, John Wiley

& Sons, Inc., New York, NY.

374
A MEMS Transducer for Ultrasonic Flaw Detection

by

Akash Jain, David W. Greve, and Irving J. Oppenheim'

ABSTRACT

Metal structures can fail because of fatigue crack propagation or because of section loss from corrosion.

Regular inspection is required to intercept such failures, and m situ sensors would be a superior

technology for that purpose. We have designed and fabricated arrays of MEMS capacitive diaphragm

transducers and we report on their performance as pulse-echo detectors in direct contact with solids. Our

chip is approximately 1-cm square and features nine detectors in a linear array, each detector containing

180 hexagonal diaphragms. Performance of the detector array was studied by bonding the chip to test specimens and applying an ultrasonic pulse using a commercial ultrasonic transducer. One experiment

recreates an on-axis excitation in which the pulse arrives uniformly at all detectors, and another

experiment recreates an off-axis excitation in which the pulse arrival is delayed from one detector to the next along the length of the array, permitting accurate localization of the source using phased array signal

processing. The results establish that MEMS transducers can function successfully as phased array detectors of ultrasonic signals in solids. KEYWORDS

Diaphragm; flaw detection; MEMS; phased array; ultrasonics

1. INTRODUCTION

Steel is used in buildings, bridges, pressure

piping, and industrial construction, but the safe

performance of any steel structure is threatened

by section loss from corrosion or wear, by crack

propagation from fatigue or cyclic loading, by

weld failure from overload or seismic loading,

or by other discontinuities. Such flaws can develop with time, and the continued service of

major structures often requires confirmation that such flaws have not developed. Ultrasonic flaw

detection [1] is a versatile technology for

nondestructive evaluation, but it must typically

be performed by skilled personnel. The

principles of pulse-echo flaw detection are depicted in a through-thickness geometry in Figures 1 and 2. Figure 1 depicts an ultrasonic

pulse transmitted into the material. A typical

transducer frequency is 5 MHz, corresponding to a 1.2-mm wavelength in steel, which is sufficiently short to resolve flaws at that same

scale. The typical transducer is a piezoelectric

ceramic, most often PZT (lead-zirconiumtitanate), with a diameter much greater than the

wavelength. The ultrasonic pulse will reflect from the first boundary it encounters, which in an unflawed specimen is the back surface of the

steel plate. The time at which the echo returns

to the front surface reveals the total travel distance, equal to twice the thickness. Figure 2 records a measurement using a mm-scale PZT

sample affixed to brass (velocity of sound c =

4400 m/s) with a thickness of 9.8 mm, showing

successive echo returns. The time from the

pulse to the return of the echo, and the time

between successive echoes, is under 5 |J.s, which

correctly approximates the thickness. Ultrasonic

inspection can be used in this manner to measure

thickness, which would reveal any section loss, or to reveal reflections that arrive prematurely,

which would signal the presence of a flaw.

' Department of Civil and Environmental Engineering (IJO), Department of Electrical and Computer Engineering

(DWG, AJ), Carnegie Mellon University, Pittsburgh, PA 15213; Phone 412-268-2950 (IJO); Email ijo@cmu.edu.

375
Although ultrasonic flaw detection is quite

versatile, there are two limitations that could be

eliminated by the development of resident

sensors. In current practice the inspection is performed manually, and is therefore subject to

interpretation. Moreover, the process is most

often memoryless, making no use of the earlier signal history. We envision building a resident

ultrasonic flaw detection system to be mounted

at critical locations on metal structures, which

would retain a signal history to allow signature

analysis in the detection of developing flaws.

We intend that the device be polled remotely

using RF communications. This paper describes

the design and initial testing of a MEMS

capacitive (diaphragm-type) transducer array to function as the receiver in the flaw detection

system. In order to scan a volume of material

from a fixed position it is necessary for the

transducer to function as a phased array, and

experiments to demonstrate signal detection and

phased array processing were a main purpose of

this study.

2. PREVIOUS WORK

Ultrasonic pulse-echo detection is used in many

applications including range/motion sensing,

embedded object detection, surface

characterization, and medical ultrasound

imaging. There is a considerable history of

research into MEMS transducers for fluid- coupled and air-coupled applications. Our

approach to designing microscale ultrasonic

diaphragms was based on the important work of

Khuri-Yakub at Stanford University [2,3,4].

One paper [2] outlines the mechanical and

electrical analysis of capacitive diaphragm

transducers and presents experimental results for

air-coupled and fluid-coupled transmission

through aluminum, showing that practical

applications (including flaw detection) are

feasible. Another paper [3] records in detail the

fabrication steps needed to produce capacitive

ultrasonic transducers suitable for immersion

applications and the characterization, both

experimental and analytical, of their performance. Another reference [4] discusses

one-dimensional transducer arrays and presents

initial imaging results, in which solids immersed

within fluids are detected. Other investigators of

MEMS ultrasonics include Schindel [5] with numerous contributions to immersion

applications, and Eccardt [6], at Siemens, with

the demonstration of surface micromachined

transducers in a modified CMOS process. The

present authors [7] have recently published an

earlier version of the experimental results described herein.

3. DEVICE DESIGN

In a MEMS capacitive transducer, a DC bias

voltage is maintained across the plates of the

capacitor and diaphragm deflection then

produces a change in capacitance that can be

detected electrically. The sensitivity of a single

diaphragm increases linearly with its area and

with the bias voltage, and inversely with the

cube of the gap dimension. Moreover, the

sensitivity of a detector composed of

diaphragms in parallel increases with the

number of diaphragms, and therefore a favorable

utilization of area is preferred in order to obtain

maximum signal strength. Accordingly, a hexagonal geometry was chosen for the

individual diaphragm unit and the transducer was fabricated by the MUMPS surface

micromachining process. The diaphragm is constructed in the polysilicon-1 structural layer

with a thickness of 2 \xm and is a regular

hexagon with leg length equal to 49 |im, chosen

to yield a resonant frequency near 4 MHz. A

target capacitance of a few pf was chosen, but

the predicted capacitance for a single diaphragm was only 0.016 pf; therefore the basic detector was fabricated as a group of 180 diaphragm

units in parallel. Figure 3 is the layout drawing

for a typical detector, with approximate

dimensions of 0.9x2 mm.

The overall device layout is shown in Figure 4. The chip is approximately 1-cm square and

contains 23 detectors. The primary detector

array is the set of nine in the right-hand column,

spanning a 1-cm baseline for phased array implementation. The nine detectors in the

middle column are an alternate design

attempting to use the substrate, rather than a deposited electrode surface, as the stationary

plate of the capacitor. The three detectors at the

top of the left-hand column constitute variations

376
on the diaphragm design, using closer-spaced

etch release holes, to perform experiments on

squeeze film damping. The two largest

detectors in the left-hand column are alternate diaphragm designs constructed with two

polysilicon layers, for a thickness of 4 |Lim, and a correspondingly larger leg dimension of 69 |im.

4. EXPERIMENTAL RESULTS

To our knowledge, our tests were the first to attempt signal detection by MEMS transducers

in direct contact with solids. The experiments were performed with chips bonded to plexiglass

specimens using Gelest Zipcone CG silicone

adhesive. Commercial ultrasonic transducers,

with nominal diameters of 15 mm and rated

operating frequencies of 3.5 MHz and 5 MHz,

were the signal sources. Figures 5a and 5b

depict the specimen geometries; the MEMS chip

appears on-edge as a small rectangle, and the

dimension records the closest distance between

the signal source and the nearest detector. In the

test depicted in Figure 5 a the baseline of nine

detectors appears as a single point, the point

closest to the transducer. Because the transducer

is approximately 15 mm wide and the detector

baseline is less than 10 mm long, the signal is expected to arrive simultaneously at each

detector; the test is termed the on-axis geometry.

In the test depicted in Figure 5b the baseline of

nine detectors appears as the heavy line. The

dimension shown (0.72-inch, or 18 mm) is the

distance between the signal source and the nearest single detector. Therefore, the signal

will reach the nine detectors along the baseline

at an extreme raking angle (65° from the normal)

and with considerable delay in arrival time

across the baseline; the test is termed the off- axis geometry. The main purpose of these tests was to obtain the distance and angle between the

transducer and the source in Figure 5b, using

phased array signal processing.

Figure 6a shows experimental results for a pulse

in the on-axis geometry illuminating the array of

nine detectors from a distance of approximately

0.53-inch, or 13 mm. The signal received at each detector is displayed on the plot at the

appropriate relative spatial position of each

detector, and we note the following:

• Each signal shows a pulse near 1 |iis because of stray electrical coupling,

followed by the signal arrival approximately 4.5 |lis later, corresponding roughly to the specimen

thickness along that travel path. • As predicted, the arrival time is uniform

at all detectors.

• The signals at each detector are

relatively uniform in appearance and

comparable in amplitude.

Figure 6b shows experimental results for a pulse

in the off-axis geometry raking across the array of detectors, and we note the following:

• Only seven detectors are shown,

because two detectors became nonoperative during the course of the tests. • The signal arrives first at the closest

detector, with successive delay in its arrival at each subsequent detector.

• The arrival times are consistent with the

distance between the pulse source and

the array. • The delay permits localization of the source, determining the distance and

angle to that source, using the principles

of radar imaging.

• A simple geometric localization can be

envisioned directly on Figure 6b. If a

vertical line is drawn through the start of

the pulses, and another straight line is drawn through the start of the received

signals, those lines will intersect at a position that can be scaled (either from

the inter-detector spacing or from the

whole baseline dimension) to obtain the

location of the pulse origin to the "left" of the array as it appears in Figure 5b. A simple signal processing approach was used.

Because the detectors are equally spaced, the

delay between them will be roughly constant. If each signal is shifted successively by some

delay, and then all signals are added together,

the sum should be maximum when the correct delay is used. Equivalently, "guessing" the

distance and the angle to the source constitutes a "guess" at a delay, with which the signals can be

summed, and when the best estimates of

377
distance and angle are used the sum should be a maximum. Figure 7 depicts the results of that process, using arbitrary units, and the isolated

peak represents the best estimate of distance and

angle to the source; the axis projecting into the

foreground represents the distance and the other

axis right represents the angle to the source. (The peaks along the distance axis represent the

stray-coupled pulses, and should be ignored.)

5. CONCLUSIONS

Experimental results in Figures 6 and 7 show

that MEMS capacitive (diaphragm-type)

transducers can successfully detect ultrasonic

pulses when in contact with a solid. The phased

array implementation shows that the transducer can successfully localize a source in an off-axis

geometry. This first-generation device was

designed to test the feasibility of phased array

detection, to evaluate design alternatives, and to conduct related experiments in diaphragm

behavior. The detectors fabricated in this first device are sufficiently sensitive to detect pulses

from a commercial PZT transducer. More

recent results (not shown) demonstrate that the

detectors are sufficiently sensitive to detect

pulses from mm-scale PZT sources if geometric

spreading from the signal source is kept small.

However, demonstration of flaw detection in practical geometries will require greater

sensitivity in order to detect signals from small

sources (creating a spherical wave) after considerable geometry spreading. Currently the

sensitivity is limited by the capacitor gap and the

detector area, and detection limits are severely

constrained by parasitic capacitances. A secondgeneration device is presently being fabricated

with a number of design improvements to these

conditions, and is expected to improve

performance by an order of magnitude.

Additional improvements in effective sensitivity,

by orders of magnitude, can be achieved when

the mechanical transducer and the electronic

circuits are fabricated as an integrated system on

a single chip.

6. ACKNOWLEDGEMENTS

This work has been funded by the

Commonwealth of Pennsylvania through the

Pennsylvania Infrastructure Technology

Alliance program, administered at Carnegie

Mellon by the Institute for Complex Engineering

Systems, and by gifts from Krautkramer Inc., and the authors gratefully acknowledge that support.

7. REFERENCES

1. Krautkramer, J. and Krautkramer. H.,

Ultrasonic Testing of Materials, edition,

Springer Verlag, Berlin, 1989.

2. Ladabaum, I., Jin, X., Soh, H., Atalar, A., and

Khuri-Yakub, B., "Surface micromachined

capacitive ultrasonic transducers," IEEE Trans.

Ultrasonics, Vol. 45, 678-690, 1998.

3. Jin, X., Ladabaum, Degertkin, F., Calmes, S., and Khuri-Yakub, B., "Fabrication and

characterization of surface micromachined

capacitive ultrasonic immersion transducers,"

IEEE Jnl. Of Microelectricmechanical Systems,

Vol. 8, 100-114, 1999.

4. Oralkan, O., Jin, X., Kaviani, K., Ergun, A.,

Degertkin, F., Karaman, M., and Khuri-Yakub,

B., "Initial pulse-echo imaging results with one- dimensional capacitive micromachined

ultrasonic transducer arrays," IEEE Ultrasonics

Symposium, 959-962, 2000.

5. Schindel, D., "Air-coupled generation and

detection of ultrasonic bulk-waves in metals

using micromachined capacitive transducers,"

Ultrasonics, Vol. 35, 179-181, 1995.

6. Eccardt, P., Niederer, K., Scheiter ,T., and

Hierold, C, "Surface micromachined ultrasound

transducers in CMOS technology," IEEE

Ultrasonics Symposium, 959-962, 1996.

7. Jain, A., Greve, D. W., and Oppenheim, I. J., "A MEMS Ultrasonic Transducer for Monitoring of Steel Structures," SPIE Smart

Systems for Bridges, Structures, and Highways,

Paper 4696-31, San Diego, March 2002.

378
ias m ' '12^ 1S61 19(? ' n$i ssl

Figure 1. Pulse-echo flaw detection, ref [1] Figure 2. Results using mm-scale PZT specimen

I

Figure 3. Typical detector, approximately 0.9x2mm, containing 180 diaphragms

Figure 4. Layout drawing of MEMS chip, array of nine detectors in right-hand column

379
Figure 5a. Test specimen, on-axis geometry Figure 5b. Test specimen, off-axis geometry

time [scL-j time [sec]

Figure 6a. Experimental results, on-axis geometry Figure 6b. Experimental results, off-axis geometry

1500

Figure 7. Signal processing results, distance and incidence angle to source given by the peak

380
Utilizing Radio Frequency Identification on Precast Concrete Components -

Supplier's Perspective

Burcu Akinci,' Mark Patton^, Esin Ergen^

ABSTRACT: Precast concrete material suppliers are responsible for the components that they

manufacture from casting until up to 25 years after installation. To effectively manage the

production and storage at a the production facility, to streamline the construction process and to quickly repair a component should there be a problem, information about components must be

readily available and updated throughout the 25 year life cycle. Currently, suppliers use barcodes to track precast components and paper-based documents to store information about

them. These approaches are time-consuming and error prone. Suppliers also face the problem

of not finding the right information in a timely manner. This paper discusses the utilization of

radio frequency identification technology (RFID) for tracking precast concrete components and

their historical information from fabrication to post-construction. RFID is an automatic

identification technology that uses memory chips attached/embedded to objects to transmit data

about them. Our discussion revolves around one use case that we developed describing the current component tracking approach and the proposed approach utilization of RFID technology

from a large-scale precast manufacturer/erector's perspective. We conclude with an assessment

of benefits and limitations of the proposed utilization of RFID system for tracking precast concrete materials.

KEYWORDS: RFID; precast concrete; construction; material management

1. INTRODUCTION

A precast concrete manufacturer is liable for a component from the time that they cast the

component until 25 years after installation. Precast components used in a facility are expected to maintain their original condition

throughout their life cycles. Any problem

that might have occurred during the

manufacturing and erection of a component

might not surface until late in service. Once

a problem is detected during service, it is important to know the full history of a component to address the issue effectively.

At the manufacturing phase, the material

information about precast components

should be documented during casting. After

' Assist. Prof., Civil and Env. Eng. Dept.,

Carnegie Mellon University, Pittsburgh, PA,

15213, bakinci@andrew.cmu.edu

^ Research Prof., Civil and Env. Eng. Dept.,

Carnegie Mellon University, Pittsburgh, PA,

15213, mp3c@andrew.cmu.edu

^ Graduate student, Civil and Env. Eng. Dept.,

Carnegie Mellon University, Pittsburgh, PA,

15213, eergen@andrew.cmu.edu

the components are cured the information on

where they are being stored should be

documented to minimize the time-loss in locating components in a large storage area. At the construction phase, deliveries should

be inspected to ensure that the components

have the desired quality. Any problems

during installation should be documented as

part of a component's history.

Currently, critical information about

fabrication and installation processes is not

stored at all or cannot be accessed easily

after the completion of a project, since they

are mostly paper-based and stored at different locations. As a result, when a problem occurs with a component, it is hard

to access the relevant historical data

important to identify the cause of a problem.

Part of material tracking problem, especially

at the site or a large storage area is being

addressed by barcodes (Bemold 1990). Even

though barcodes provide an easier way to track components, it has been noted that barcodes are being damaged in the harsh

construction environment. In addition, in some cases, it is difficult to access the tag

381
for scanning (especially in storage areas)

since one needs to be next to a barcode to be

able to read the information (Furlani 2000).

Finally, barcodes do not have any memory

and hence it would be impossible to store the history of a component on a barcode.

Radio Frequency Identification (RFID) is another identification technology that uses memory chips attached or embedded to objects to transmit data about them. In this paper, we discuss the utilization of RFLD

technology to locate and track the precast

pieces and to store information about them

from their fabrication to installation. Our

discussion revolves around a use case developed based on data obtained from a

large-scale precast manufacturer.

2. BACKGROUND ON RFID

RFID is an automatic identification

technology used to identify, track, and detect

various objects. RFID systems are composed

of two components: a tag, and a reader. RFID tag is an electronic label that stores data and is attached to objects. Readers,

which send RF (Radio Frequency) signals

for communication, are used to read data

from these tags. A reader is composed of an

antenna, a transmitter/receiver and decoder.

Current RFID technologies use three

frequency ranges: low (100-500 kHz),

intermediate (10-15 Mhz), and high (850-

950 Mhz / 2.4-5.8 Ghz). Table 1 lists some

of the unique characteristics of each

frequency range. Low and intermediate

frequencies are commonly used for

inventory control, while high frequencies are used for railroad car monitoring and toll collection systems (AIM 2002).

RFID tags can be classified as either active or passive based on the power source. An

active tag has an internal battery for power.

A passive tag utilizes the energy generated

by a reader/antenna. Active tags have a

greater read/write range (up to 30 m.).

However, they are larger in size, more

expensive, and have a limited life span (5-10

years). Passive tags are cheaper, smaller,

lighter, and have unlimited life span. However, they require a more powerful

reader and have shorter read ranges.

Table 1. Characteristics of frequency bands

Frequency Characteristics

Low

100-500Khz

Short to medium reading range

Inexpensive

Low reading speed

Intermediate

10-15 MHz

Short to medium reading range

Potentially inexpensive

Medium reading speed

High

850-950

MHz

2.4-5.8 GHz

Long reading range High reading speed

Line of sight required

Expensive

Tags also can be read only (RO), read / write

(RAV) or write once / read many (WORM)

(Paolo 2002). RO tags are pre-programmed

with unique information, and this data

cannot be modified afterwards. In RAV tags,

additional data can be written by overriding or extending the existing data stored in a tag. In WORM tags, information in a tag can be

changed only once. After the data is read

from any type of transponder, it can be sent

to a host computer, or stored on a reader to be later uploaded to a computer (AIM 2002).

Tag cost, size and memory capabilities vary. Tag information can be limited to a unique

code, or include detailed information, e.g., manufacturer, storage conditions, etc. A

passive tag can store up to 2k bits of user information (TI 2001) while an active tag can have a memory up to 1MB (AIM 2002).

Price of a tag increases with the amount of

information that can be stored on a tag.

Current prices are between 50 cents to $50

depending on the memory, type

(active/passive, RO, RAV or WORM) and

operating frequency. However, prices are decreasing as the technology develops. For

example, in 1995 prices for various tags were between $10-$100 (Jaselskis 1995).

RFID tags are technically more

advantageous than barcodes in material

tracking and documenting the history of a component. RFID tags have capability of

larger data storage. In addition, they can

382
operate in harsh environments and do not

require line of sight like barcodes. Besides,

it is much faster to collect information about

a batch of components using RFTD since

RFID technology allows collection of up to forty items per second (Marconi 2002). Data

security is achieved in RPID tags with an

optional password mode, which requires a password to enable read and write functions.

Data in a tag can be locked by the user to prevent future modification (Atmel 2002).

3. PREVIOUS EXAMPLES OF RFID

USAGE AT CONSTRUCTION SITES

Several applications of RFID in other

sectors include tracking pallets, mail, and

automation processes in manufacturing.

Schell (2001) suggests that the utihzation of

RFID tags during the maintenance of a

plant's pressure relief valves has reduced

manual data entry by 70%.

Jaselskis (1995) proposed some potential

applications, such as, cost coding for labor

and equipment, and material control, which

utilizes RFTD technology during a

construction project. He identified three

major barriers for the utilization of RFID

technology at construction sites: (1) lack of

standardization among different RFTD

manufacturers impeding interchangeable

usage of RFTDs from different brands; (2)

hampering effect of metals caused by the

reflection of RF energy from metal surfaces;

(3) requirement for a battery management

program for the active tags (Jaselskis 2000).

Today, current technology has overcome the

metal effect problem (Forster 2002), and

various industry and standards organizations

are working on RFTD standards.

4. USE CASES

In this section, a potential application of

RFID in precast components is discussed

from a supplier/erector's perspective. The

data presented is based on real data obtained

from a large-scale precast manufacturer.

The large-scale precast manufacturer that we

studied works on design-build arrangement,

where an architect designs a facility, and

then through a bidding process selects a manufacturer to design, engineer, fabricate

and erect the structure. Precast components

vary from structural beams to miscellaneous

items such as columns, and curved sections.

Their production is 17,200 pieces per year. The manufacturer's storage area is approximately 60 acres, and the average

number of precast elements stored at the

production facility is 3,500 pieces at a given

time. After casting, the components are sent

to the storage area after one or two days

maximum. Once at the storage area a precast

component is either shipped within a few

days or going to be stored there for months.

The main reason for long storage periods is that the manufacturer prefers to fabricate

similar pieces in a casting bed at the same

time. Thus, some pieces can be produced

months in advance since they are similar to the ones that will be delivered in a week.

The locations of ones that are stored for

longer durations are typically changed

several times before their delivery date.

4.1 Current Material Tracking Process

Currently, barcodes are used to identify each

piece, along with a piece mark that is written on one end with marker. Since thousands of

different pieces are stored in the storage area and line of sight is required for barcodes,

finding the necessary component becomes

very difficult. Currently, about 10 workers

work at the storage area, and it takes about

30 minutes to 1 hour to locate a component

in that large area. In some cases, when the

workers cannot locate some pieces at a

storage area, those pieces have to be cast again, resulting in late deliveries. Currently,

the manufacturer pays approximately

$60,000 for annual penalties for late deliveries, which are mainly caused by

delays associated with locating materials.

After a delivery is made, a field engineer is required to inspect each delivery to check if the right pieces are delivered. Then, the

precast pieces are stacked in lay down areas

for preferably 1-2 weeks (Pheng 2001).

383
In addition to tracking storage and delivery

of precast pieces, precast manufacturers are also liable for any possible defects and

failures of the precast pieces for up to 25

years. Different factors, e.g., cement,

aggregates, the number of times a component is handled, the site conditions

during construction, etc., can cause a defect on a precast component. When there is a defect or failure, they need to quickly

identify these factors that the defective

component is being exposed to so that they can fix the problem efficiently and prevent

any similar failures in other pieces.

Currently, much of the information related

to the history of a component is not stored at

all, and the ones, which are stored in documents, are not easily accessible.

In summary, precast suppliers/builders face

two major problems associated with

component tracking: (1) locating the precast

pieces at their storage facilities and (2)

accessing a component's history after construction. Current approaches for locating components and accessing a component's history are time-consuming,

costly and not effective. RFID technology

provides a way to address both of these

problems. The next section describes the

proposed system.

4.2 Proposed System

The proposed system utilizes RFID

technology to locate each precast piece on a storage area without line of sight

requirement, and ensure a reliable delivery

schedule to a construction site. Additionally,

information about manufacturing,

inspection, and construction can be entered

to a tag.

When an owner places an order, the

designers in the company designs the

components, and assigns an ID for each

piece. During the fabrication of each piece,

passive RAV tags with unique IDs are attached to the pieces. During that time all production related information is entered to the tag (Figure 1). After 1-2 days when the

curing is complete, the pieces are checked

by the inspector. The inspector's approval

about the quality of precast components will

also be stored on the tag before the

components are sent to the storage area. A grid of transponders ("tags") are embedded in the floor of a storage area. When a piece is placed in a storage area,

first its tag is read to retrieve its ID and all the other information, and then the

embedded transponders are read to match

the transponder's code with the location in the storage area. This information in the

reader is then sent to a supplier's material

database. This would enable quick

identification of the member at the storage area (Figure 2) and hence just-in time

delivery of the pieces to a construction site. Whenever the location of a piece is changed,

the same process is repeated, and any new

handling information will be stored in the

tag as part of the history of a component.

Once components that need to be delivered

are identified, they are loaded onto a truck,

which is also tagged with a W/R

transponder. The IDs of the pieces are read

and entered to truck's tag by a handheld

reader. When the truck departs, a reader

installed at the exit records the components

that are shipped. The date, truck ID,

component IDs are sent to the supplier's

material database, and to the scheduler who

works for the erector. Receiving this information, staging areas are determined on

a site, and a crane is assigned for unloading.

Additionally, during transportation of

materials, the delivery truck can be tracked

by GPS; thus, both the manufacturer and the erector can be informed about the real-time

location of the truck and the components.

At the entrance of a construction site, truck

ID is read, components recorded as arrived

in a database, which can be used for

invoices and payments, and the

manufacturer is notified that the delivery is completed. Another inspector who works for

the erector company, checks the pieces, and

enters any damage or defect that might have

occurred during transportation. Finally,

pieces are installed according to their Ids,

384
and the current site conditions, and

information about installation methodology

are also stored in the tag as part of the

history of components

As a result of this new process, delays due to locating materials at a manufacturing

storage area and on a construction site are minimized and all the important information

about the history of a component is stored on a tag. This information can be retrieved

any time after the installation of a component should there be a problem. As a

result, a manufacturer can efficiently

identify the cause of the problem, effectively

manage the problem, and take precautions

for similar problems that can be observed in other components.

5. COST / BENEFIT ANALYSIS

The following cost/benefit analysis attempts

to assess costs and benefits of locating

materials on in a large storage area using

RFID. The analysis is based on the

quantitative data obtained from the

manufacturer and on the current RFID costs.

It is assumed that all precast components are tagged with a passive RAV tag, and workers

are using three readers (Table 2).

Table 2; RFID equipment cost for one year number Cost ($)

tag 17,200 172,000

reader 3 6,000

Total 178,000

As Table 2 shows, the cost of embedding

tags and retrieving information from the tags

is $178,000. To recover this cost, nominally

7,120 hours of worker time should be

eliminated as seen in Table 3. We believe

that using tags will save at least half of the

actual time spent on locating the

components. This corresponds to approximately 5 workers, which is 9,600

hours of worker time. This exceeds the

7,120 hours required to nominally recover

the cost of implementing the RFID system

and hence suggests that the savings will outweigh the cost of utilizing RFID tags

Table 3: Worker time need to be saved

Tag cost

($)

Hourly rate for a worker ($)

Worker time

(h) 178,000 25 7.120

The cost benefit analysis based on the

quantitative data shows that it is beneficial

to use RFID for material tracking purposes.

Also, there will be additional savings

associated with just in time (JIT) delivery of

components. Since currently the cost of

delayed delivery is $60,000 per year, the JIT

delivery of the components will enable

additional savings up to that amount.

The proposed analysis, however, does not consider the potential additional benefits

that will be received when the tags are also

used for storing historical information of a component as described in Section 4.2. It is foreseeable that additional benefits will be

incurred when same tags are used for storing

historical information. Current memory

capacity of a RAV passive tag, which is around 2k bits, might not be sufficient to store all information necessary. In the next phase of this research, we will be

performing tests to assess how much of the

necessary historical information.

Regardless, the technology is developing

rapidly, and memory capacity is likely to increase significantly in few years. With

that, additional benefits associated with

storing historical information will be

achieved. This will create significant

savings to the precast suppliers since

currently majority of their consultants' time

is spent in collecting historical data rather

than analyzing it to repair a component.

In the future, when the memory capacity

increases, the digital picture of any defect can also be stored in the tag.

6. CONCLUSION

In this paper, we propose a system, which

utilizes RFID technology to locate precast

components in a storage area at the

manufacturing plant, tracks the delivery of

the components, and stores all the necessary

information about the components for the

future use. In this system, passive RFID tags

385
are suggested to be used for storing data,

and for tracking precast pieces.

The system improves the efficiency of

locating the components in storage areas in manufacturing plants. In addition, tracking

the components during the delivery process

is beneficial for just-in-time delivery.

Finally, storing the necessary information in the tag helps the manufacturers to retrieve

the history of a component quickly and

identify the cause of any problem that might

occur after construction.

Our future work includes the

implementation of this system in a precast

manufacturing plant. Through that, we will

further identify the technological capabilities

of current RFID tags in storing historical

information and develop a more

comprehensive cost/benefit analyses for the

proposed use case.

7. REFERENCES

Association for automatic identification and

data capture technologies (AIM) : http://www.aimglobal.org/technologies/rfid/

what is rfid.htm, 06/27/2002.

Atmel Corp.: http://eu.atmel.com/atmel/

acrobat/doc2003.pdf, 06/27/2002.

Bemold, L.E.: "Barcode-driven equipment

and materials tracking for construction", J. of Comp. in Civil Eng., 1990, Vol. 4, No. 4,

381 -395.

Forster, I.J: "Resolving Problems in Using

RFID Tags with Metal Objects",

http://www.isit.eom/feature.cfm'?tech=AIDC

&ArticleID=3829. 06/27/2002.

Furlani, K. M., Pfeffer L. E : " Automated

tracking of structural steel members at the

construction site", ISARC 2000, 1201-1206.

Jaselskis, E. J., Anderson M. R., Jahren, C.

T., Rodriguez, Y., Njos S.: "Radiofrequency identification applications in construction industry", J. of Const. Eng. and

Manag., 1995, Vol. 121, No. 2, 189-196.

Marconi InfoChain: http://www.marconiinfochain.com/tech/rfid.htm, 06/27/2002

Paolo, M. D., Furr, W., Ream, N. N: "RFID:

Replacement or supplement to barcodes?",

http://citeseer.ni.nec.com/49058 1 .html, 06/27/2002

Pheng, L.S., Chuan, C. J.: "Just-In-Time

management of precast concrete components", J. of Const. Eng. and Manag.,

2001, Vol. 127, No. 6, 494 -501.

Schell, D.: "Oil refinery uses RFID to eliminate rework and reduce data entry by

70%", Business Solutions, January 2001.

Texas Instruments,

http://www.ti.com/tiris/docs/manuals/pdfSpe

cs/RI-102- 112A.pdf, 06/27/2002.

FIGURES

tag

1 Precast concrete

-date of manufactrue: 06/30/2002

-aggrates: ASTM C 33. ASTO C 330

-admixtures: ASTM C260, ASTM C494 Type A

-cement: ASTM C 150

-reinforcing bars: ASTM A 615. Grade 40

-connection materials: ASTM A 36, ASTM A 47

-quality control; no defect

-inspector: John Waters Figure 1: Information entered to a tag during

casting of a precast member

Figure 2: Grid of transponders

in the storacfp area

386
MEMS Application in Pavement Condition Monitoring - Challenges

by

Nii O. Attoh-Okine*

Stephen Mensah*

ABSTRACT

Although the universal definition of MEMS product possesses a number of distinctive features, they are miniature systems involving one or more micro-mechanical components or structure. Infrastructure

assessment has recently addressed an important field for MEMS application. For example, satisfactory

laboratory experiment in the area of concrete monitoring has been developed. Although the experiment is at an infant stage, it demonstrates the enormous potential of MEMS application in civil infrastructure

systems. This paper proposes to develop a framework for the application of MEMS technology in pavement condition monitoring and evaluation. Some difficulties which may be encountered, especially

in asphaltic medium and loading condition of the pavement will be discussed.

Keywords: devices, evaluation, microelectromechanical, monitoring, non-destructive, pavement, system

1. INTRODUCTION

Pavement condition monitoring and evaluation

is important in many areas of pavement

engineering, especially in pavement

management. The in-service performance of the

pavement depends on consistent, cost-effective

and accurate monitoring of condition for early

scheduling of repair and maintenance. For the

past decade, nondestructive evaluation (NDE)

testing has played a major role in pavement

condition monitoring, assessments and

evaluation. The NDE evaluation methods

include seismic evaluation such as wave

propagation, vibration methods, acoustic and

ultrasonic methods, electromagnetic method and

electrical resistivity methods.

The accuracy and repeatability of the

interpretation of these NDE techniques are dependent on the limitations imposed by the

operating conditions and material properties. For

example, the use of acoustic methods is well

established in water but in a dense material,

especially concrete pavements, specially

developed sensors are required [1].

Researchers from diverse disciplines especially

electrical, computer and mechanical

engineering, have been drawn into vigorous

efforts to develop sensing technologies and

nano-technology in infrastructure condition

assessment [2], crack detection [3] and building

monitoring [4]. Recently, MEMS have been

proposed as a tool in infrastructure condition

monitoring. Researchers over the years have

developed microfabricated sensors for measuring position, acceleration, pressure, force,

torque, flow, magnetic field, temperature, gas

composition, himidity, and biological gas/liquid

molecular concenfration [5]. Its miniature size

has enabled widespread use in the medical field and the automotive industry. MEMS have had a fremendous impact on our modem society: it has

led to creation of jobs; it has a significant

leverage factor enabling the production of

sensor-based systems exceeding sensor cost by

several orders of magnitude; and in some

instances have even become critical components

that determine the feasibility of new products

[6]. While the success of MEMS continues to grow, it appears its use in civil infrastructure

monitoring is yet to make any impact.

387
This paper delves into the potential application

of MEMS in infrastructure monitoring and some

of the technological as well as technical issues to grapple with.

2. MICROELECTROMECHANICAL

SYSTEMS (MEMS)

• MEMS can generally be characterized by

the following. They are miniature systems

involving one or more micro-machined

components or structures. The inherently

small size of MEMS enables high-level

functions by virtue of the large-scale

integration process. This permits multiple

functions or capabilities integrated o the same silicon chip or package for greater

utility.

While MEMS devices are sought to be of

somewhat dimensions of only a few

micrometers, the small size of a device does not

automatically qualify it as a MEMS device. The

distinctive features are [8]: miniaturization,

micro-electronic and multiplicity. Also he

device consists of components which act together in a systematic fashion for a desired

purpose. MEMS has been described as a

toolbox, a physical product and a methodology

[7]: • It is a portfolio of techniques and processes

to design and create miniature systems;

It is a physical product often specialized and

unique to a final application

The MEMS technology will have an impact on

engineering in the following ways [9]: • By causing orders of magnitude increase in the number of sensors and actuators

• By enabling the use of very large-scale

integration (VLSI) as a design and synthesis

approach for electromagnetics.

• By becoming a driver for multiple, mixed

and emerging technology integration.

• By being both a beneficiary of and a driver

for information systems.

In addition to the potential economic benefits

MEMS has the ability to integrate mechanical

(or chemical, biological and environmental)

functions. It will also allow for consideration of

concepts such as the highly distributed networks

for the condition monitoring of large civil infrastructure systems. The fundamental

technological issues in MEMS include:

• Materials

• Machining process

• Micro-mechanical devices

• Application

2.1 Materials

Silicon has been used extensively however there

have been advances in new materials exploration

and the study of material properties for microsensors and actuators has opened up new

frontiers of materials. The progress of

microactuator technology depends critically

upon the development of actuation forms that are compatible with the materials and processing

technologies of silicon microelectronics [5]. Mechanically, silicon is an elastic and robust

material whose characteristics have been well

studied and documented. Furthermore silicon as

a material exists in three forms: crystalline,

polycrystalline or amorphous. Each of the forms

has unique properties which make them useful

for different applications. Another important

property of silicon is its ability to integrate with

electronic circuits and sensors. Three important

material properties which are of great interest to MEMS are: • Piezoresistivity - the phenomenon where a

material's resistivity changes with

mechanical strain. • Piezoelectricity - when crystals exhibit the

peculiar property of producing an electric

field when subjected to external force.

• Thermoelectricity - the interaction between

electricity and temperature.

The choice of material depends on its compatibility with the current fabrication

process as well as other materials to be used in the device fabrication. A material property of

significance cannot be exploited if this compatibility is not met.

388
2.2 Micromachining

Three fabrication routes or methods account for the majority of MEMS devices: surface

micromachining, bulk micromachining and

molding. Surface micromachining [10] uses the

CMOS (complementary metal oxide

semiconductor) process to fabricate VLSI (very

large scale integration) devices. In the surface

micromachined MEMS, the layers are patterned

and etched to yield electromechanical elements

to allow motion of the mechanical layers. Bulk

micromachining involves etching features

directly into the silicon wafers, it is an important

consideration in MEMS where higher

mechanical power or force levels are desired

[11]. Molding is the third prevalent

manufacturing process used for MEMS. It is the

creation of the mechanical elements of the

device by the deposition of material into a microfabricated model.

23 Microelectromechanical Devices

Microelectromechanical devices generally

comprise of microsensors, microactuators, and

electronic circuits or signal processing units

integrated on a single chip. The miniaturization

of the devices makes them inherently smaller,

lighter and faster than their macroscopic

counterparts and are usually more precise. The

microsensors sense or collect information from

the environment whereas microactuators alter the state of the environment. This process

essentially involves the conversion of a mechanical force or physical effect in the

environment (such as change in pressure or temperature) into electrical signals and viceversa. This is possible by taking advantage of

peculiar material properties such as

piezoresistive, piezoelectric and thermoelectric

effects to convert the change in the environment

to electricity. The signal processing unit or

electronics will then process the information and

provide inputs to the actuators. The actuators in turn can manipulate the environment for a desired purpose or trigger another action to compensate for the change. Microactuators are

the key devices allowing MEMS to perform

physical functions. They are categorized in two

perspectives: one based on driving forces and

the other based on mechanisms.

2.4 Application

Microdevices are being embedded in structures

to enhance their performance. Such structures are called smart structures or smart materials.

Smart materials and structures technology is a new field of study that is finding its way into

many applications in civil infrastructure

systems. The applications include structural control, condition health monitoring, damage

assessment, structural repair and integrity assessment. More recently and extension has

been made to cover asset management and

preservation and operation of civil infrastructure. The drawback to extensive

MEMS application is that there are no generic

MEMS products but rather they are application

specific. The vast majority of applications

require unique solutions that often necessitate

the funding a completion of an evaluation or development program. This process could take

several years, typically 2-5years, and it impacts

directly on the performance of MEMS devices on the market [5].

3. PAVEMENT CONDITION

MONITORING

3.1 Infrastructure maintenance is undertaken

based on the perceived health of the

infrastructure based on information gathered

from the performance indicators. The need to

collect data reflective of the true state of health

of the infrastructure is therefore crucial for an

efficient management of the system. Condition

based maintenance (CBM) or on-demand

maintenance are gaining currency due to the

superior advantage they afford. Microsensors can be embedded unobtrusively and

inconspicuously in structures to monitor

parameters critical to the safe operation and

performance. Bennet et al. [12] developed a wireless monitoring system for highways. The

system consists of a retrofitted instrumented

asphalt core, which is bonded into the pavement

structure. The core contains all of the electronics

necessary to record two pavement temperatures

(surface and base) and two strains (longitudinal

and transverse). The data when collected is transmitted via low power radio link to a

receiver and data logger positioned by the side

of the road. Also Sackin [13] proposed a new

389
laboratory approach for the feasibiUty of

embedded microdevices for infrastructure

monitoring in concrete. This microdevice will be

termed as "smart aggregate". One of the

objectives of the work is to investigate how an embedded device will behave under real working and environmental conditions.

Although the laboratory test was successful,

most questions vital to the MEMS application in

infrastructure systems were not adequately

considered. Some of these will be highlighted in

the subsequent paragraph. Table 1 summarizes

the potential application of MEMS based on

condition deterioration mechanism.

3.2 Important Considerations

It is envisaged that MEMS devices can be

embedded in the road infrastructure to monitor

the condition at all times. The information

collected can then be relayed via wireless

technology into a database. Or MEMS devices

with remote query capability can be interrogated

at any given time to assess the condition of the

pavement system as mentioned earlier. For the

successfril application and implementation of

MEMS in pavement for continuous monitoring, some issues need to be addressed. Some of these

issues are listed below:

• The effect of asphaltic medium on MEMS.

• How many MEMS devices are to be

installed per 1km of pavement

• Where will the designer install or embed the

microdevices (MEMS) in the pavement?

• Pavements have a life span of 20-30 years,

will MEMS devices be able to perform

throughout this period?

5. REFERENCES

1. W. Uddin and F. Najafi, "Deterioration

mechanisms and nondestructive evaluation

for infrastructure life-cycle analysis".

Infrastructure Condition Assessment: Art,

Science and Practice. Edited by Mitsuru

Saito, pp 524-533, 1997.

2. R. Ansari. "Theory and applications of

integrated fiber optic sensors in structures".

Intelligent Civil Engineering Materials and

Structure 22, pp 2-28, 1997.

• How will environmental conditions affect the performance of MEMS in pavement

condition monitoring?

• How will the effects of chemical medium

such as corrosion in reinforced concrete

structures, affect the performance of MEMS.

• Although the cost of MEMS is predicted to be reasonable, will it be a cost-effective

method of collecting continuous data?

Some of these considerations have been

addressed in other fields. For example, MEMS

has been used in various chemical media in

bioengineering applications [14].

4. CONCLUSIONS

The paper presents some challenges that need to be addressed for a successful implementation of

MEMS technology in pavement monitoring. For

example, laboratory investigation on the

behavior of embedded MEMS in asphaltic

material medium under dynamic loading needs

to be addressed. Finally, it is required to test and

frack the field behavior of the pavement to establish both repeatability and long-term

behavior of MEMS embedded in the pavement.

3. P. Rossi and F. LeMaou. "New method for

detecting cracks in concrete using fiber optics".

RILEM, Materials and Structure 22, pp. 437-

442, 1989.

4. P. L. Fuhr et al. "Performance and health

monitoring of the Stafford Medical building

using embedded sensors". Journal of Smart

Materials and Structures 1, pp. 63-68, 1992.

5. M. Mehregany. Microelectromechanical

Systems". IEEE Circuits and Devices 9 (4),

pp 14-22.

6. J. Bryzek. "Impact of MEMS technology

on society". Sensors and Actuators A (56),

PP 1-9.

390
7. N. Maluf. "An introduction to microelectromechanical systems

engineering". Artech House Publishers,

2000.

8. H. Fujita. "Microactuators and

Micromachines". Proceedings of IEEE, 86

No. 8, pp 1721-1732, August 1998.

9. K. J. Gabriel, Microelectromechanical

Systems". Proceedings of IEEE, 86 No. 8 pp. 1534-1535, August 1998.

10. J. M. Bustillo, R. T. Howe, and R. S. Muller, "Surface micromachining for

microelectromechanical sytems".

Proceedings of IEEE, 86 No. 8 pp 1552-

1574, August 1998.

U.S. M. Spearing. "Materials issues in

microelectromechanical systems

(MEMS)". ACTA Material 48, pp. 179-

196, 2000.

12. R. Bennet. "Wireless monitoring of

highways". SPIE Conference on Smart

Systems for Bridges, Structures and

Highways 3671, pp 273-182, 1999.

13. M. Sackin. "A feasibility study of

embedded microdevices for

infrastructure monitoring: Smart

aggregate for concrete". A thesis

submitted in partial fulfillment of the

requirements for the degree of Master of

Science, December 1999.

14. A. Pedrochhi et al. "Perspectives on MEMS

in bioengineering: a novel capacitive

position microsensor". IEEE Transactions on Biomedical Engineering 47 No. 1 pp 8-

11, January 2000.

391
Table 1. Potential application of MEMS based on condition deterioration mechanism.

Condition Deterioration mechanisms Potential use of MEMS

deterioration Load/usage, environment, material

degradation, construction quality,

interaction

Other

1. Surface

defects

Primary (environment, material

degradation)

Secondary (load/usage, poor construction

quality)

Interaction (material/environment and

extended by load)

Man-made

defects,

maintenance

patches

Fair

2.DeformationPrimary (environment, material

degradation)

Secondary (load/usage, poor construction

quality)

Interaction (material/environment/load)

Loss of

support,

inadequate

maintenance

Excellent

3. Cracking,

disintegration

Primary (environment, material

degradation)

Secondary (load/usage, poor construction

quality)

Interaction (load /environment/ material

degradation)

Accidents,

inadequate

maintenance

Very good to excellent

4. Failure

(a)

Aging/inadequ

ate structural capacity or retirement

The facility is structurally deficient

because the limiting threshold values of

(1) surface defects

(2) deformation

(3) cracking and disintegration are exceeded or the facility is retired

because it is functionally obsolescent.

Interaction (nature)

Capacity and

safety

considerations,

inadequate

maintenance

Good

(b)

Catastrophic

failure

Primary causes: earthquake, floods,

freeze/snow, ice, tornado/cyclones, wind

storms, foundation and soil failure and

sink holes.

Interaction (poor construction

quality/design deficiency

Fire, arson,

terrorist act or

other accident

Poor

392
Towards the Ultimate Construction Site Sensor^

by

William C. Stone^ and Maris Juberts^

ABSTRACT: The NIST Construction Metrology and Automation Group (CMAG), in cooperation with the NIST Intelligent Systems Division (ISD), is developing performance metrics and

researching issues related to the design and development of a "Next Generation LADAR" sensor that will enable general automation in structured and unstructured environments. This paper

quickly reviews the basic physics and implementation of various LADAR technologies,

describes the problems associated with available "off-the-shelf LADAR systems, summarizes

State-of-the-Art work underway around the world, and elaborates on general directions that

advanced research in this area of sensor design will take in the coming years and its likely

impact on construction automation.

KEYWORDS: AM-modulation, construction automation, FM-modulation, laser radar, multiple returns, phantom points, pulse time-of-flight, range image sensors

1.0 INTRODUCTION

Laser Detection and Ranging (LADAR) is currently poised to become the ubiquitous 3D spatial

measurement tool in many disciplines. Initially

used for remote sensing and aerial surveying,

LADAR applications now include reverse engineering (3D models), ground surveys, automated

process control, target recognition, and

autonomous machinery guidance and collision

avoidance to name just a few. Efforts are currently underway at NIST to develop national arti- fact-traceable LADAR calibration facilities; to develop rapid, LADAR-based long range autoID

systems; and to establish the scientific and engineering underpinning needed to develop miniature, high resolution next-generation LADAR

systems.

The power of LADAR lies in the inherent 3D

nature of the data it produces, namely spatial

coordinates associated with each pixel in a socalled "range image" acquired by the device. A

range image is effectively a spherically acquired

(r, 0, (p) dataset mapped to a 2D matrix, or "frame." LADAR frames are frequently presented as false color depth images. Additional data,

including reflectance intensity associated with

each pixel and multi-spectral intensity information, are commonly available. Color reflectance

intensity (as opposed to active illumination fre- quency-specific reflected intensity) is obtained

from co-boresighted RGB CCD sensors. Such a wealth of information can be rapidly segmented

for use by a wide variety of real-time systems for machine control and post-processed for such

metrology applications as as-built geometry

checking for buildings and other civil infrastructure. This said, why are we not seeing LADAR

systems on every construction site? The reasons most frequently cited are: slow speed of operation, bulky, high cost, and widely varying accura- cy that presently lacks standardized calibration

metrics. There are other related issues such as

^ Official contribution of the National Institute of Standards and Technology (NIST); not subject to copyright in the United

States. 2 NIST, BFRL, Construction Metrology and Automation Group, Mail Stop 8611, Gaithersburg, MD 20899-8611;

william.stone@nist.gov.

^ NIST, MEL, Systems Integration Group, Mail Stop 8230, Gaithersburg, MD 20899-8230; maris.juberts@mst.gov

393
methods for processing the data (both real-time

and offline) but that is the subject of another

paper. Frequently the performance of a LADAR

is defined by the following metrics:

• Maximum permissible illumination power

• Sensor horizontal Field of View (FOV)

• Sensor vertical FOV

• Wavelength of optical source

• Maximum distance to be measured

• Measurement time

• Measurement resolution (depth)

• Measurement resolution (angular)

• Range Measurement accuracy

To these one frequently must consider:

• Intensity of background (passive) illumination

• Color temperature of the (passive) background

• Target reflectivity (texture, color, specularity)

• Angle of beam incidence on the object

• Overall size (volume) of the sensor

• Manufactured cost of the sensor

At the conclusion of this paper we will present a

set of design criteria we feel are representative of

those needed to achieve ubiquitous use of

LADAR sensing for construction operations. We

will also comment on the research needed to achieve a physical sensor meeting such criteria.

2.0 LADAR PHYSICS SUMMARY

2.1 Pulse Time-of-FIight (TOF)

Figure 1 shows a "family tree" of LADAR

devices that have at one time or another been

built to operate at optical and near-optical wavelengths. References 1 and 2 provide useful in- depth discussions on many of these devices. The

simplest of the concepts uses pulse time-of-flight

(TOF), as illustrated in Figure 2. An illumination

pulse is generated, frequently by means of a NdYAG microchip laser, and the time of this event

is made available to a timing circuit. The beam

traverses a distance equal to 2d and arrives at a photonic detector in time:

Time-of-Flight Measurement

cw

Modulation

AM

Homodyne

Phase-shift

AM

Heterodyne

ZF-phase

Pseudo^oiM

Modulation

FM

Chirp Modulation

AM

Sequential Phase Coding

Lightbeam

(10-lllumlnatlon) OD-d«tector OO-mixer 2D-scannsr

I Lightstripe

i (30-lllumlnation) ID-detector ID^nixer 10-scanner

Lightvolume

(2D-lllumination) 2D-detector

2D-n)ixer No-scanner

Figure 1 : "Family Tree" of optical and near-optical

wavelength time-of-flight range measurement devices.

Figure 2: Fundamental physics of pure "pulsed" timeof-flight. Key performance metrics are synchronization precision of pulse initiation between the source and detector, pulse width, and detector bandwidth.

3-axi5 micromeler APO focusing"

pan

"galvanometer'

drive

power supply (OfAPD

.shielded (8NC)

stgnal out Uom APD to AloD

converter in laptop con^puier

tfll "galvar»omt»lfif anve Passive

heat sink

microchip laser

spWler

Figure 3: Typical physical implementation of a pure

pulsed time-of-flight LADAR Scale is approximately

300 mm long by 1 50 mm wide.

394
t- —

c

where c = speed of light. A clock time of 1 ns

represents a 300 mm round-trip flight or an

absolute range of 150 mm. One can immediately

see that an extremely accurate clock is required

to achieve a level of accuracy sufficient for autonomous fabrication. Figure 3 shows a typi- cal physical implementation of a pulse TOF

LADAR [8]. The microchip laser generates 1 ns pulses at a rate of 10 kHz, producing an imambiguous range interval of 1 5 km. The signals are detected by an avalanche photodiode (APD).

In this particular implementation an optical beam

splitter is used to divert a portion of the source

signal to the APD, thus providing the "start timer"mark for range determination. The accuracy of such systems depends on a number of

factors including the pulse width, detector elec- tronics bandwidth, and the processor implementation. If the APD bandwidth is 2 GHz and the

analog-to-digital readout (also known as ROIC)

is matched, then the timing "bin" width is approximately 0.5 ns, but since that is round-trip, the range bin accuracy is thus 75 mm. This "0- D" ranging system is then scanned in 2D using

electromechanically steered mirror systems.

2.1.1 Limitarions of Pulse TOF

Thus far we have made the assumption that all of

the photons that are generated hit one specific

object and are reflected back to the detector in a narrowly discriminating beam yielding one range measurement per pixel. This is not the case as shown in Figure 4. Due to imperfect optics and

atmospheric dispersion the source illumination

beam (pulse) expands with range; good industrial LADARS that have achieved near-diffraction limited optics have beam dispersion angles of

around 0.2 mrad. Even so, this produces a finite beam diameter at 100 m of around 20 mm. This

has interesting physical consequences. Because

the un-ambiguous range of the device shown in Figure 3 is on the order of 1 5 km, one receives,

in time, responses from photons from the illumi- nation pulse arriving at different times related to

Uncompensated Microchip Laser Beam Divergence

100 m

With Diffraction-Limited Optics

100 m

Figure 4: Source beam divergence variance and its effect on absolute beam diameter at 100 m range.

Figure 5: Due to beam divergence photons associated with a single "pixel" in a LADAR frame may repre- sent significantly differing range data.

the different objects they hit within the cone of

the dispersed beam. Figure 5 illustrates this point. A single "pixel" in the LADAR frame will

in fact have multiple valid ranges. Figure 6

shows a time-domain response out to a range of

approximately 120 m. Any strong return above

the noise threshold represents a valid object

detection. Thus, one could store not one value,

but a vector of values, for each pixel. Some

LADARs now being developed illuminate at more than one wavelength. The response at each

395
Noise

Threshold

Foliage

Foliage

/

Vehicles

Time from Source Pulse Trigger (ns. full frame width = 400 ns)

Figure 6: Full time-domain response for a Ins pulse.

Response was captured in 801 "range bins." The

time-width of each bin was 0.5 ns, or 150 mm.

pixel can then be represented by a matrix with n

returns per source frequency f:

i./i

2,/,

3. /,

R«/,

R1.^

R

At present, no commercial pulse TOF LADAR

provides the user with this kind of pixel response

matrix (or even a single frequency time domain

vector). Instead, it is common to average earlier arrivals that have strong S/N (signal-to-noise)

ratios and report that as a single range per pixel.

The results of this averaging are shown in Figure

7, where non-existent "phantom" points become

part of the point cloud data set. The point here

is that each of the valid returns shown in Figure 6

represent usable engineering information that is presently not available. Pulse TOF systems are limited in their accuracy not only by the bandwidth of the detector (currently pegged at around

2 GHz, although current research in fiber optic

tele-communications is pushing this higher), but

also by the pulse width of the source illumination, since edge detection is enhanced by a shorter, sharper pulse. The shortest pulse source curI

Figure 7: "Phantom" points (sloping ledges leading

diagonally downward from the top) generated during

scans of a rectangular box using single-point-per-pixel

reporting from an industrial pulse TOF LADAR.

Averaging of multiple returns (see Figure 6) to pro- vide a single range per pixel leads to the erroneous

reported locations.

modulation

frequency:

Signal A >. = c/f = i5m/

return / /

signal

1 Thus....

Aip of 2n = Ad of 7.5 m

Figure 8: Phase-based determination of time-of-flight. Primary modulation frequency establishes the maximum unambiguous range for the device.

rently used in LADAR devices is 250 ps [5].

2.2 AM Homodyne Phase Modulation

One way to beat the "brute force" approach to time-of-flight accuracy is through the use of

phase detection. This concept is illustrated in Figure 8. If the source is modulated at a single

sinusoidal frequency, f, then a phase shift of

c

396
will be observed between the transmitted and

received signal. Since the range, R, is equal to half the round-trip distance, L,

R =

A0C

The unambiguous range resolution is directly

proportional to the source modulation frequency,

f, while the accuracy is directly proportional to the signal-to-noise ratio. The two are directly

related; the tighter the unambiguous range the

finer can be parsed the phase difference, thus improving the accuracy. For the case shown in Figure 8, the unambiguous range is half the wavelength at f= 20 MHz, or 7.5 m. Signal-tonoise ratio can be improved by integration over many cycles, but at the cost of raw throughput

(frame rate).

Range determination using phase measurement is adapted from earlier work in radar in which the source and received signals are mixed and the phase, amplitude, and offset of the resulting sig- nal are determined through Fourier theory. If the

resulting signal is sampled at four intervals separated by phase angles of k/2, it can be shown

[2,6] that the phaseshift, A({), is given by

= arctan

where Aq, Aj, A2, A3 represent the integration of

the mixed signal over the intervals shown in Figure 8. The trick is m the formation of the

f=20MHz, T=50ns

Figure 8: In a phase-based solution the transmitted and received signals are mixed. Discrete Fourier Transform (DFT) theory allows extraction of the phase, amplitude, and offset by sampling four points

at an interval of n/2 along the resulting waveform.

vss J,

P*

p-sut»Hmt9

'kii

•i>i*4..qr f-i

CMOS APS imagar

Figure 9: Example of an "Active Pixel Sensor," one

of many versions of a Focal Plane Array (FPA) that can be used to simultaneous ly sample hundreds to thousands of pixels. FPAs form the core of "flash" LADAR and can utilize either phase or pure time-offlight ranging.

mixed signal and in the integrations to be per- formed. One of the more clever solutions to this problem makes use of so-called photonic mixing

(Figure 9) in which a standard CMOS photo

diode is reverse biased by the same frequency

source that modulates the transmitted illumination signal. This diode responds directly to the mixed signal consisting of the modulated bias and the incoming photo electrons. Timing cir- cuitry dumps the white portions of the curve in Figure 8 while summing (through a capacitor) the regions Aq, Aj, A2, A3 and selectively storing

those values. It is possible to implement such

detectors in 2D arrays in the form of Focal Plane

Arrays (FPAs) as shown in Figure 9. Individual

pixels within a LADAR frame are mapped (optically) to pixels on the FPA. Similar FPAs can be

constructed to work on the pulse TOF principle.

Both approaches are referred to as flash LADAR.

397
Range Retolution & Accuracy

Reiolufion = ability fo differentiate between two

objects at different range (controlled by the "bin" lize)

Accuracy = obtolute error in ttie range meoiurement (largely

controlled by S/N ratio)

Figure 10: Due to beam divergence and varying

reflectivity of target surfaces, both accuracy and resolution are affected for all types of LADAR, but particularly for AM-homodyne class devices which in effect integrate the reflected photons from all surfaces that are illuminated, thereby producing an erroneous aver- age range.

2.2.1 Limitations of AM Phase Measurements

Pure homodyne (single frequency) LADARs suffer from two significant limitations. As the modulation frequency is increased, thereby improving

potential accuracy, the un-ambiguous range is reduced — leading to aliasing or false targets. A

solution to this problem is to use multiple fre- quencies [4] in which a lower frequency signal is used to establish an im-ambiguous interval over a

longer distance within which the higher frequency response is located. The mathematics for solving this approach are not significantly more

complicated than for the pure homodyne solution, but it has yet to be implemented in silicon. A more serious problem with phase-based measurement is illustrated in Figure 10. For the same

reasons that multiple returns are received in pulse

TOF systems, the integration response of the photonically mixed signal includes the energy

reflected from all the surfaces shown in Figtu^e

10, regardless of their different ranges, as long as they are within the illiunination cone of the dis- persed source beam. Thus, the range reported is an average of the objects within that pixel, lead- ing to the same type ofphantom points described

earlier.

Figure 1 1 : Block diagram for an experimental FMCW LADAR. This design overcomes range averaging

issues with AM-CW system [7].

2.3 FM-CW Modulation

It is possible to recover multiple ranges per pixel

in a frequency modulated LADAR by producing

a very specifically-shaped source pulse, known

as a chirp. The theory for such an approach has

been around since the advent of radar [7] but

only recently has been adapted to optical sys- tems. In a chirp pulse the frequency is varied

linearly with time; typically over the range of

200 MHz to 600 MHz with a frequency response of 800 MHz or more. The range resolution (per

pixel) in such a device is given as AR=

" 2A/

in which Af is the chirp frequency step size. The

detector in Figure 1 1 consists of a photonic FPA

mixer and CMOS read out circuit. The result is a frequency-domain signal (an integrated intensi- ty for each of n frequencies contained in the chirp bandwidth). This signal must be subsequently processed, using an FFT, to obtain a time

domain response. Nyquist sampling criteria increases the range bin size by a factor of 2.

The chief limitations of the FM-CW LADAR

approach are the need for additional front end

hardware (complicated chirp-generation electronics that add both cost and an additional level of

noise), the frequency response of the laser source (which may be bandwidth limited); and the manifold increased mathematical post-processing that

is involved.

398
3.0 IDEAL LADAR PERFORMANCE

NIST has for a number of years conducted

research in autonomous robotic platforms and

machinery and has reached a consensus regarding

the required performance of a "vision" system

needed for effective control. A LADAR meeting

these criteria would have the following attributes:

Illumination Source: eyesafe

Field of View (FOV): 60° x 60°

Range resolution: 1 mm @ < 15 m

3 mm @ < 100 m

Angular resolution: < 0.03°

Frame rate: >10 Hz

Size: coffee cup

Cost: < $1000 US

Some of these criteria can be met by existing sys- tems but most cannot. Frequently there is a tradeoff between speed and accuracy. 2D frames

can be created using high resolution laser rangers

by a method known as "scanning" in which a sin- gle-degree-of-freedom laser radar is mechanically

swept over the scene using either encoderequipped pan/tilt servos or a rotating mirror combined with either a pan or tilt servo. Because of

this mechanical reliance, however, these systems

have inherent speed and accuracy limitations

associated with the servos and their encoders.

New work in FPA design shows promise for both

improving range resolution as well as speed.

And only this latter approach shows promise for the miniaturization needed to achieve the last two

criteria listed above. The FOV and angular resolutions listed above translate to a 2048 x 2048

pixel FPA. The largest range-imaging FPA yet to be demonstrated successfully is 25 x 64, although

several labs have 128x128 arrays under development. There are other significant issues: to illu- minate a large FOV requires considerable laser power, possibly making the output unsafe (eyesafe) at most of the compatible wavelengths.

Parallel FPAs or MEMs-based steering provide

possible solutions.

4.0 Conclusions and Avenues for Research

The joint NIST effort to develop a Next

Generation LADAR (NGL) for autonomous

machine control and construction metrology has

identified four key areas for research needed to achieve a fiinctioning sensor with the above specifications:

• Ultra-fast Chip-Level Laser technology: build

and test compact pulsed femtosecond (-lO"^^ s) coherent laser sources. The performance, power

needed, source-detector cross-talk and ranging

accuracy of prototype lasers and APD receivers

will be characterized at NIST. It will be deter- mined whether nonlinear quantum dot saturable

absorbers can be implemented in micro-laser cavities to achieve shortest possible pulse duration.

Initial efforts will be to experimentally determine

if extensions to known micro-chip laser systems

can achieve desired femtosecond performance

followed by work on candidate new designs.

• Ultra-precise Chip-Level Time and Frequency

Standards: Investigate development of

MEMs/CMOS-based manufacture of on-chip,

high accuracy time and frequency standards and

phase correlators. Investigate development of

candidate designs for CMOS implementation of

the best timing and frequency designs and ulti- mately to the fabrication of test articles. Refine

designs of an on-chip timing and frequency stan- dard that could be readily integrated with a candidate APD/FPA for testing with either the chip

light source developed in task 1 or by means of

external femtosecond laser sources.

• Fast Beam Steering: There are several different

technologies available for fast beam steering.

The most popular of these are acousto-optic, tilt- ing mirrors and electro-holography. Miniature

beam steering devices are being investigated at NIST based on these technologies. The tilting

mirror technology has received special attention

recently, because MEMS-size mirror arrays have

been built. Acousto-optic devices use acoustic waves propagating in a variety of optic materials

to control the refractive index of the material and

thus the angle of the output light beam. The

399
electro-holography technology involves the writing of Bragg grating holograms of specific wavelengths on photo-refractive crystals. NIST is evaluating these beam steering technologies and

will select the most promising of them for prototype devices.

• Systems Integration and Performance Analysis:

Early analysis here has focused on the advantages and disadvantages of direct TOF versus phase correlation methods for range determination within the context of systems capable of

being fabricated using MEMs and CMOS technology combined with InGaAs / InP detectors

that are either bump or bridge-bonded to the read

out circuit. This effort is also investigating issues

and techniques for integrating a single channel

micro-steerable LADAR. Computer simulations

are being developed to evaluate the feasibility of

miniaturization, operation in various environments, sensor detection limits, and performance

characteristics - distance, accuracy, and speed.

The results of this research in the coming years

will prove the feasibility of building the ultimate

construction site sensor.

5. AuII, B.F. et al, "Geiger-Mode Avalanche

Photodiodes for Three-Dimensional Imaging,"

Lincoln Laboratory Journal, Volume 13, Number

1, 2001.

6. Spirig, T., "Smart CCD/CMOS Based Image

Sensors with Programmable, Real-Time,

Temporal and Spatial Convolution Capabilities

for Applications in Machine Vision and Optical

Metrology," Doctoral Dissertation, Swiss Federal

Institute of Technology, Zurich, 1997.

7. Stann, B.L., Ruff, W.C., and Sztankay, Z.G,

"Intensity-Modulated Diode Laser Radar using

Frequency-Modulation / Continuous-Wave

Ranging Techniques," Optical Engineering,

November 1996.

8. Schilling, B.W., Barr, D.N., Templeton,

GC, Mizerka, L.J., and Trussell, C.W.,

Multiple-return laser radar for three-dimensional

imaging through obscurations, APPLIED

OPTICS, Vol. 41, No. 15 pp 2791-2799, May

2002

5.0 REFERENCES

1 . BesI, P.J., "Active, Optical Range Imaging

Sensors," Machine Vision and Applications

(1988) 1:127-152.

2. Lange, R., "3D Time-of-Flight Distance

Measurement with Custom Solid-State Image

Sensors in CMOS/CCD-Technology," Doctoral

Dissertation, Dept. of Electrical Engineering and

Computer Science at University of Siegen,

Siegen, Germany, June 28, 2000.

3. Stettner, R., and Bailey, H.W., "3D Imaging

Laser Radar," United States Patent 6,133,989,

October 17, 2000.

4. Frohlich, C, Mettenleiter, M., Hartl, F., Dalton, G, and Hines, D., "Imaging Laser

Radar for 3-D Modeling of Real World

Envirotmients," Sensor Review, Volume 20, No.

4, 2000, pp 273-281.

400
SESSION 8

CONTROL SYSTEMS FOR

CONSTRUCTION EQUIPMENT

401

A Cost-Effective Positioning Solution for Asphalt Rollers

Based on Low-Cost DGPS Receivers

by

Jaroslaw Jurasf , Karl Ludwig Kley'

ABSTRACT: As of today, the DGPS-based Computer Integrated Road Construction systems for compaction support require high investments (about 50% of total machine cost), mostly due to the high cost of the positioning equipment. Worksite

tests show that the majority of the compaction errors are serious omissions of the compaction plan. The article discusses the accuracy requirements and implementation structure of a cost-effective system based on the low -cost DGPS receivers,

aimed at detection and correction of the major compaction errors. First results of

the experimental validation confirm the feasibility of the approach. The full-scale implementation is currently under development and scheduled for worksite tests. The availability of cost-effective and robust positioning solutions should improve

the acceptance of the DGPS-based compaction support systems.

KEYWORDS: compactor pass map; computer integrated road construction; low

cost DGPS; positioning; unscented Kalman filter

1. INTRODUCTION

The purpose of the Computer Integrated Road

Construction (CIRC) is to increase the quality

of the road works by tracking the construction processes in the real time [1]. As the basic

concept is based on the comparison of the actual position of the machine's tool with the

desired value, e.g. with a digital terrain model

(DTM), the positioning sub-system is a crucial element of every CIRC system and greatly in- fluences its performance.

As of today, the CIRC systems use two basic

positioning techniques: the Robotic Total Station for high precision measurements (mm

range) and Differential GPS (DGPS) receivers

for lower accuracy (cm-dm range). The DGPSbased compaction support systems introduced

recently, both in research and commercial domain (e.g. [2][3][7]), share the disadvantage of

a relatively high price and have not yet found

market acceptance. The cost-effectiveness is an especially important factor for the compaction support applications, as the asphalt rollers are considered not cost-intensive machines.

Still, the correct compaction is critical for the

quality of the asphaU pavement.

For this reason, an economical positioning solution

based on low-cost DGPS receivers has been

studied, and is now implemented in the scope of the OSYRIS project [9]. The intermediate

results are presented in this paper.

2. MOTIVATION

CIRC products for the broad market must take

the total system cost into account. Compared

to the total investment costs of an asphah roller, additional CIRC equipment is still quite ex- pensive (approximately half of total costs),

where most of the price is due to the positioning equipment. Therefore it is justified to cmsider cheaper positioning solutions.

Required positioning accuracy is the critical factor determining the cost. For surfacing machines, such as asphalt rollers, a 2 dimensional

positioning, at a working speed between 5 and

10 km/h is required. For this purpose, Peyret [1]

' Institute for Technology and Management in Construction (TMB), University of Karlsruhe, Am Fasanengarten, D-76128 Karlsruhe, Germany, tel. +49

721 608-8222, e-mail: liurasz ! klev)(5: tmb. uka.de

403
recommends decimetre accuracy. Also Do et al.

[6] suggest an accuracy better than 15 cm, in order to monitor the overlap between consecutive passes.

Existing DGPS systems can be classified ac- cording to the used technology, resulting accu- racy and price level as follows:^ > Centimetre accuracy Phase DGPS with

fixed ambiguities - price range 15-25 k6. > Decimetre accuracy Phase DGPS with

floating ambiguities - price range 3-8 k€ > Meter accuracy Code DGPS - price range

0.1-0.2 k€

As of today, the surveying centimetre accuracy

receivers are mostly used for compaction support tasks. Due to the limited market, their price has remained high in recent years. The

costly GPS differential phase processing has

additional disadvantages: low robustness and

long initialisation times. This has to be op- posed to the widely applied meter-accuracy

DGPS, where the market is well-established,

applications are numerous and the price reduction has been achieved using specialised inte- grated circuits. Moreover, the code measure- ment is much more robust and is available al- most instantly, partly due to the relatively simple processing. This is very important in the context of the road construction site, where the

satellite visibility may be limited due to pre- existing bridges, urban canyons etc.

The question arises to what extent the codedifferential GPS, possibly aided by inertial positioning and Kalman filtering, may be ap- plied in compaction support context. The ec- perimental tests conducted in 1967 in [7] suggest that extremities of the pavement, the join

and edge, tend to receive substantially less compaction. In more recent tests [8], the number of passes at many sections vary between 1

0

and 50, and the compaction plan has clearly not been kept (see Fig. 1.). Apparently this tendency has not changed during last 35 years.

" As the reference station can be shared, its cost is not taken into account here

1s

J — '

> \

i \

: I \

\

1

i

4

J

/

' W V u ^

? I

S ii

.VjsSi.'

Fig. 1 : Minimum, mean and maximum number

of drum passes at given curvilinear abscissa

measured experimentally on a motorway section.

Clearly, a sub-metre accuracy system would be

sufficient to detect and help to correct such major compaction errors. The minimum re- quirement of the positioning accuracy is posed

by the lane defmition (typical width 1.8 m).

Such level of accuracy can possibly be reached

with the Code DGPS. However, it is necessary

to investigate the configuration of the sensors and evaluate the resulting accuracy in terms of

the man-machine interface (MMI) result.

3. SYSTEM DESCRIPTION

3.1. Configuration

The preliminary study has shown that the ^

plication of multiple DGPS receivers on one machine offers several advantages: > Increased precision can be reached by

averaging, as the positioning noise of the

receivers is only weakly correlated. The

achieved improvement of RMS error was

close to 2~"'. This suggests that the majority of the error is due to the multipath

effects, dependent mostly on the antenna

placement. > The heading of the machine can be deter- mined, also in static conditions. > As the distance between the antennas re- main approximately constant, the reliability of the measurement can be monitored.

For practical reasons the number of the receiv- ers has been limited to two, over the front and

rear drum. The additional inertial sensors have

been introduced in order to provide independent measurements of the machine speeds: lin- ear and angular. The chosen inertial sensors

404
are relatively inexpensive and should be inte- grated in the machine in order to improve the robustness of the system.

Fig. 2. shows the basic structure of the system.

NMEA—

Post

Processing (Kalman RItering)

j can-Bus

j Dtstanc <^.^ \ / Dtsianc \

Figure 2: Basic System Structure

The used positioning equipment consist of: > Two low-cost GPS OEM modules (CEP

in DGPS mode < 1 m)^ > Two active GPS antennas at the machine

extremities > Wheel odometer > Optionally: Wire sensor for the articula- tion angle measurement

The articulation angle measurement can possibly be omitted, as the typical compaction pattern consists of a combination of straight lines, in order to avoid destroying the fresh asphalt

surface. The turns are made on already c«npacted material, with the vibration switched off, and do not have to be counted as passes. However, the articulation angle measurement may

be of advantage for curved compaction plans.

The GPS measurements are carried out with

IHz DGPS mode (with RTCM 2.1 correction

messages received from a high quality base

station), the inertial sensors work with a meas- urement cycle of 2.5 Hz.

^ Manufacturer specifications. CEP, The Circular Error Probability indicates a circle, which encloses 50% of the measured positions.

3.2. Mathematical Modelling

Considering a compactor with an articulation

joint, moving in the two dimensional space, the location of the vehicle can represented by the

state vector X = [x,y,<p, v,(of (1)

where x and y describe the position of the ar- ticulation joint, (j) describes the heading (yaw),

V and ft) denote respectively the translational and rotational speed (see Fig. 3.). Both drums

can be modelled by a stick of a length w (equal

to the drum width) attached at to the joint. This

simplified model can still accurately represent

the longitudinal overlaps.

y

Figure 3: Model geometry

Assuming constant speeds and no lateral slip, and taking into account the articulation angle, the kinematic model is represented by the nonlinear model

X = VCOS(/>

>' = vsin0

X = F{X) = \(^=(0 (2)

Q) = v[y-7t) or 0

v = 0

The measurement vector Z includes the position measurement from the front and the rear GPS, placed /y and 12 from the articulation joint,

above the front and the rear drum of the roller.

405
Moreover the angle and speed measurement

are used.

The discrete system equations can be then

written as

where and F and H are system and measure- ment functions and V, W are additive system

and measurement noises. Based on the estimated speed, a Boolean esti- mate of the static/kinematic mode can be pro- duced. The passes of the machine are counted

only in the kinematic mode.

3.3. The Unscented Kalman Filter

The observations are processed with an Lhscented Kalman Filter (UKF). The UKF for nonlinear estimation [4] is based on the lAi- scented Transformation, presented by Julier and Uhlmann [5]. Consider a recursive estimation

The full Kalman step is calculated in a 1 Hz

cycle, with each new GPS measurement. As- suming a working speed of 2 m/s this results in a real-time uncertainty of 2 m on the MMI,

additionally influenced by the GPS latency (<

0.5 s corresponding to 1 m). For these reasons

a filter with a 2-5 Hz prediction step and a 1 Hz correction step has been considered.

4. EXPERIMENTAL VALIDATION

To conclude on the accuracy of the presented

positioning solution, several static and dynamic tests were performed and evaluated. As no asphalt roller was available for the first test period, a wheel loader with similar kinematic characteristics was chosen (Fig. 4.). The

two GPS antennas are mounted at the front shovel and on a framework at the back, where

also the wheel-distance sensor is fixed. To reduce the multirpath errors, a metallic disc,

diameter ~40 cm, is mounted under both ai- tennas. The last tests were performed, using an

additional framework at the back, to reach an

antenna height of 2.50 m. Also the shovel at the front was lifted, to reach the same antenna

height as at the front.

- ^k.pred + '{^k ~^k.pred ) (5)

for the optimal minimum mean-squared error estimate for , assuming that the prior esti- mate X,. and the state observation are Gaussian Random Variables.

The UKF extends (5), redefining the state ran- dom variable as the concatenation of the origi- nal state and noise variables [3]. An unscented

transformation sigma point selection scheme is applied to the new augmented state random

variable to calculate the corresponding sigma

matrix [5]. The UKF algorithm can be found in

[4]. Compared to the traditionally applied Extended Kalman Filter (EKF), the UKF offers better performance and adapts better to nongaussian noise present in this non- linear sys- tem. Moreover, as the explicit linearisation is not required, it is easy to test alternative models and filtering structure. The disadvantage is increased computation cost in terms of CPU

time and memory.

Figure 4: The machine and equipment used in the preliminary tests.

The raw data from the GPS and the inertial measurements are processed, using an UKF

filter, with the kinematic model, presented

above.

The test results (Fig. 5.) showed that in the

static conditions one can observe a drift of the measured position. To account for this effect UKF switches to a static model, represented by:

^..,c=^(^) = 0 (6)

406
Figure 5: X-coordinate of the position: raw

front measurement, raw rear measurement,

processed by the Kahnan filter

In order to establish the reference for the (b- tained accuracy, the recorded raw GPS observables (code pseudoranges and integrated carrier phases) have been processed using ccmmercial GPS post-processing software. Its per- formance can be judged similar to the best GPS receivers available. In this way centimetre-accurate trajectories of both antennas have

been measured.

The obtained trajectories together with the heading information have been converted into ribbons [10] and presented as pass maps in the

Fig. 6. Except of the overlaps, both maps are qualitatively very similar and give the operator

the required overview of the performed canpaction work. The major omissions and the tendency to over-compaction in the middle of

the pavement and under-compaction close to the edges can be easily detected.

Figure 6: Pass maps observed in the experiment, a. Code - measured on-line based on

code -differential processing, b. Phase - postprocessed using phase observables

The comparison between the Code and the Phase results has brought the following results:

> The Code-DGPS modules estimate driv- ing/stopped state and perform position,

vetocity, time (PVT) type filtering on

their own. This has an effect of additionally smoothing the resuh. However, the movements at low speed (< 2 km/h) are

filtered out. This effect can be observed on the Code pass map as an early stop

condition, leading to an underestimation

of the compacted surface. This effect is not critical in the practice, as the breaking/acceleration occurs with the vibration

switched off and should not be counted as a valid pass. > At the moment the absolute accuracy of

the 2 Code DGPS system can be judged at about 80-90 cm, after removing an ob- served constant offset between the Code

and Phase results. This is sufficient to ob- tain clear lanes in the pass map. However,

longer tests are required to confirm this finding. > The GPS signal reflections caused by the machine and mounting seem to have great

impact on the multipath error and the final

result. The validation on the target machine is necessary > The performance of the filter with and

without the articulation angle measure- ment was similar. For studied trajectories

it is possible to remove it fi-om the filter structure. However, due to varying width,

this measurement is required for the rmchines with 2 articulation joints.

5. CONCLUSIONS

The presented positioning solution reaches

good performance in static and dynamic mode.

The pass maps obtained with the low-cost sys- tem are qualitatively very similar and allow for detection and correction of the major ccanpaction errors identified by the experimental tests. Long term tests on the target machine are necessary in order to tune the filtering algorithms

and fially asses the accuracy and robustness of

the proposed solution. The availability of suitable cost-effective and

robust DGPS positioning solutions should im- prove the acceptance of compaction sipport

systems in the near future. The full scale tests of the presented algorithm

are scheduled in Summer and Autumn 2002.

407
Acknowledgements

The work described in the paper was carried out in the framework of the European Project

OSYRIS: Open System for Road Infomiation

Support (Growth No. GRDl-1999- 10815),

2000-2003 [9].

6. REFERENCES

[10] J. Jurasz. Universal digital environment

model for computer integrated road construction. Proc. 18"^ ISARC, Cracow 2001.

[1] F. Peyret. The paradigm of Computer Inte- grated Construction applied to Civil- Engineering,?roc. 16"" ISARC, Madrid 1999.

[2] F. Peyret, J. Jurasz, A. Carrel, E. Zekri, B. Gorham: The Computer Integrated Road Co n- struction project. Automation in Construction

9(5-6) (2000) pp. 447-461.

[3] D. Bouvet, M. Froumentin, G. Garcia. A

real-time localization system for compactors.

Automation in Construction, 10 (4) (2001), pp. 417-428.

[4] E.A. Wan, R. van der Merwe. The Lh- scented Kalman Filter for Nonlinear Estimation, Proceedings of Symposium 2000 on

Adaptive Systems for Signal Processing,

Communication and Control (AS-SPCC),

IEEE, Lake Louise, Alberta CA, 2000.

[5] S.J. Julier, K. Uhlman. A new Extension of

the Kalman Filter to Nonlinear Systems. Proc. Of AeroSense, ll"' Int. Symp. On Aerospace/

Defence Sensing, Simulation and Controls,

1997.

[6] W.-S. Do, A.A. Oloufa, H.R. Thomas.

Evaluation of Global Positioning System E^-

vices for a Quality Control System for Compaction Operations. Transportation Research

Record 1675, Paper No. 99-0139, pp. 67-74.

[7] M.J. Kilpatrick, R-G. McQuate: Bitumi- nous pavement construction. Federal Highway

Administration, Washington, DC, 1967.

[8] Geodynamik Internet site, online resource

at http://www.geodvnamik.com.

[9] Osyris Internet site, online resource at http://ww\v.osvris.org.

408
On-Board Data Management Structure

For Advanced Construction Machine Support

by

Jaroslaw Jurasz', Agata Ligier', Alfons HornS Jochen Wendebaum'

ABSTRACT: A flexible on-board data management structure for a construction

machine and interfaces between its elements are discussed. The solution, which

grants the required flexibility and enables advanced, distributed functions is dis- cussed on the example of the road paving process.

KEYWORDS: CANopen; digital work documentation; computer integrated road

construction; road product model; site information systems; OPC; XML

1. INTRODUCTION

Nowadays the construction machines are in- creasingly often equipped with the on-board

computers, which support the operator and take over the control and documentation functions.

Their application is especially promising in

civil engineering, where the machines perform

repeatable and well-defined tasks, e.g. laying,

compacting, grading. Thanks to advances in positioning technology, on-board communication and following the need of the users, who

wish to actively participate in the quality control (Build-Own-Operate etc.), the on-board IT

plays increasing role on the modem construction site. Major part of the

requirements set for the on- board IT is due to the need

for applicability to different machines and worksites. This

includes varying configuration

of positioning equipment, sensors %

and measurement systems coming

from different providers.

With the increasing number and extending

functionality of CIRC systems in existence, the problems of interoperability and standardisation start to play a major role. Those topics are addressed in the Osyris project, in the frame of

which this work is carried out.

The goal set by the authors is to design a

flexible on-board data management structure

for a construction machine, equipped with

standardised interfaces. The article is structured

as follows: after discussing the context and the requirements for the on-board structure the contents of the information is investigated.

Then the Osyris layered on-board structure is presented, followed by two examples of advanced, distributed functionality.

2. CONTEXT

Figure 1. Heterogenous

structure of the road construction site.

' Institute for Technology and Management in Construction (TMB), University of Karlsruhe, Am Fasanengarten, D-76128 Karlsruhe, Germany, tel. +49

721 608-3884, e-mail: {jurasz | ligier | wendebaum)@tmb. uka.de

^ Moba Mobile Automation GmbH, Vor den Eichen

4, D-65604 Elz, Germany, tel. +49 6431 9577-132,

e-mail: hom@moba.de

409
The major challenge for the Osyris on-board

data management structure is due to the heterogeneous information structure of the worksite

(see Fig. 1.). featuring:

Separate processes (e.g. earthmoving, laying, re-profiling, transport), often per- formed by separate organisations,

< Few standardised interfaces; GPS NMEA

standard^ is one notable exception.

Differently equipped machines coming

from different manufacturers,

Varying configuration (ad-hoc task allocation and team definition, add-on sensors,

different operating modes).

Clearly a separation is needed between the

managed process information and the details of

the algorithm used to obtain or process it. To

assure flexibility and extensibility of the implementation we propose to fix only data stor- age structure and its interfaces. In this way the information can be accessed and/or provided

from any component without revealing the details of how the information was acquired. As

the machines work in team, wireless real-time

interfaces to the other machines have to be

taken into account. Nowadays 80. .90% of the projects con- ducted by European road contractors are vari- ous maintenance tasks. The typical limited

maintenance configuration (small paver and 1-2 small rollers) requires simple and cost-effective

solutions.

3. INFORMATION CONTENTS

The contents of the managed information is defined in the Osyris Functional Design. A

distinction between volatile real-time and static information can be made here. The most important data categories managed on-board are

(see Fig. 2.): < Design - a description of a target road in a

suitable digital form (what). Remains static during the project execution.

Mission - a description of the task to be

performed by a given machine (how). Remains static for the given mission, changing

typically daily.

*l* Machine state consists of position, tool geometry and the process data, which vary

in real-time. It can be used to derive the achieved work.

> Target machine state is a subset of machine state subject to automatic control, derived from design, mission and current machine state, for example designed elevation

at the given point.

<* Achieved worii is a record of work execution. It is gathered in real time and remains

static after the work execution.

All the data categories listed above can be

expressed as parameter values assigned to a geometry, where design, tool or achieved ge- ometry can be used to carry the parameters.

Depending on the geometry they are assigned

to, the same parameters can be used to specify

the actual or target values. The managed pa- rameters can be outlined as follows: < Position: Geographic, Curvilinear coordinates, linear and angular speed

*l* Inherent properties of the material: temperature and contents Geometrical properties: thickness, evenness, volume, level deviation Process and machine parameters: vibration,

tampering, hydraulic pressure. > Ambient conditions (temperature, wind,

sunlight)

Measurement &

Control System

Machlne_

state -Target state

,

On-Board

computer

Worksite network

Inputs

On-Board

computer

- Design -

Mission- Achieved work

Office computer

Visualisation Guiding

Mission

Inputs Quenes

Operator

Reports

Analysis

Manager

Another machine

Figure 2. Functional decomposition of an OSYRIS system

^ Although many GPS receivers offer best performance using custom interfaces.

Clearly it is not possible to define an exhaustive list of the parameters, so the definition of

the additional parameters must

be possible at the runtime. The

identification of parameters can be performed using standardised names or codes. In any case it is very important to clearly define

the meaning and units of the parameter values.

410
The piecewise-linear ribbon structure'* [1] can be used to efficiently represent all data

categories listed above. In the case of achieved

work description, the tool geometry with as- signed parameters describing state can be used

as a ribbon generator. The ribbons introduce

the natural ordering of the target parameter

values along the road axis, so that extrapolation

principle can be used to limit the number of

managed parameter values.

It is important to note that multiple values of one parameter may coexist at given time. For

example the following values of machine speed

need to be managed concurrently on-board:

measured by absolute positioning device,

e.g. GPS or Robotic Total Station

measured by local positioning device, e.g. encoder

< elaborated by data fusion algorithm, e.g. Kalman filter specified as target for the mission.

4. LAYERED ON-BOARD STRUCTURE

ised components which

services (e.g. soft sensors).

provide advanced

Product Model

Office XML interface

Ribbon database

OPC interface

OPC Server

CANopen interface M^surement &

CcsTtrol System

<MCS)

Custom low-)evel Interfaces Physical Layer

(Sensors &

Actuators)

PMO

OB

MCS

Figure 3. Osyris layered on-board structure The Osyris system is based on components.

In comparison with monolithic systems (e.g. CIRC [3]) this approach enables easy reconfiguration and provides framework for specialThe ribbon is created by moving a planar figure called generator along a curve called axis [1]

The on-board system layers are presented in the Fig. 3. The abstraction level, amount of

managed data, and required performance de- pend on the specialisation level: PMO - responsible for permanent storage, mission preparation and work analyses [2]. OB - responsible for visualisation and storage

functions, best effort (not guaranteed) real time behaviour.

MCS - responsible for guaranteed real time

interfacing, filtering and control fianctions. Multiple MCS devices are possible, al- though as of today an architecture with single, central MCS is the most economical

solution.

4.]. CANopen interface

The Osyris CANopen interface approach is based on concept of a device profile, describing

the measurement and control objects provided

by the real time measurement and control sys- tems. The fast exchange of measured data be- tween the MCS and the on-board computer is guaranteed by the efficient CANopen communication layer (so called communication profile). The CANopen communication profile is already standardised.

Former approaches to the interfacing to the measurement and control systems on construction machines were based on lower level solu- tions (e.g. CAN) and, as the interface description was hardcoded, changes in the system

structure required a lot of modifications on

software and hardware level, which led to additional costs and less reliable systems.

Therefore the Osyris solution promotes a

standardised communication for construction

machines. As a part of the proposed solution

the standard connector is also presented. The

advantages of standardised devices are numerous. It encourages the manufacturers to produce

standard measurement and control devices with

their own technology hidden behind the stan- dard interface.

Furthermore the open solution allows contractors to use construction machines coming

from different manufactures and connect them

411
to one on-site management system, without any

adaptations or modification in the MCS.

The central part of the device profile is the object dictionary description (an extract is shown in Table 1). The object dictionary is essentially a grouping of objects accessible via

CANopen in an ordered, predefined fashion.

Each object within the dictionary is addressed

using a 16-bit index and 8-bit sub-index. The

Object Dictionary contains only few mandatory

items. They can be accessed according to the worksite requirements and a current configuration. The MCS not only offers but also requires

items. The availability of items is resolved by

the on-board computer in runtime.

Table 1. Extract of the paver device profile

OPCAutomation

Wrcqjper

Index Object Description 6000 Type of machine

Kind and type of machine

6010 MCS functionality

Indices of items supported by particular implementation 6020 Event General {start, stop etc) and machinespecific (vltjration on/off etc) events 6100 Position The geograpNc position of machine's

tooi in local coordinate system (E,N,H) 6101 Angle Positfon The attitude of the tool

6102 Curvilinear Co-ordinates The coordinates of the tool in the local curvilinear system 6103 Level Deviation The levelling error

6200 Thictcness The thickness of the laid layer 6300 Screed width The width of the screed and its extensions 6310 Volume The volume of the laid material 6500 IVIaterial core temperature

The temperature of the laid material

8010 MCS wisti list Indices of items required by the MSC

4.2. OPC layer

The standardised interface to the actual machine state parameters at the level of on-board

computer is defined with help of the OPC.

OPC (OLE for Process Control) is a stan- dardised set of interfaces, based on OLE/COM

and DCOM technology, for open software application interoperability between control applications, field systems and devices, and business/office applications [4]. Osyris uses a subset of OPC called Data Access. The data ex- change is based on the server (provider)-client

(consumer) principle (see Fig. 4.).

OPC Custom Inerfai

(Shared by mmy chetis)

Senvr Data Cache

Figure 4. OPC Architecture

OPC provides a snapshot of current machine

state as a hierarchy of named items together

with the time stamp and quality information.

The items have standardised names and are mostly numeric values (vector and string are also possible). The scaling between metric (SI) units and device units is performed by the Osyris OPC Server.

Osyris OPC namespace is divided in the following groups, mostly according to the ori- gin:

*> CanOpen - machine state as received fi-om the MCS

< CanOpenOut - volatile target machine state

(e.g. level deviation) elaborated by the on- board computer, transmitted to the MCS

Designed - target state (e.g. thickness) as defined in the mission

< Pos - machine position elaborated by the positioning component

< Manual - parameter values may be over- ridden manually by the operator

< Default - for many parameters, e.g. Temperature or Speed sensible default values can be defined here, and used in case of

lack of sensors < Process-specific groups, e.g. Material, CES

(Compaction Expert System), CM (Cooling

Model)

In the Osyris implementation there is only one Osyris OPC server, which allows reading

and writing clients (no arbitration for writing is guaranteed at the OPC level). The Osyris implementation uses the OPC concept not only for client-device communication, but additionally

(which is an extension to the OPC standard) as a storage for the current machine state. Also

clients which perform parameter estimation

(soft sensors) can write into current state. Writing to the device (in this case MCS) is allowed only in the CanOpenOut group.

412
In addition to the standard OPC, a concept

of the 'unquaHfied items' has been introduced.

As already mentioned, there can exist more

than one value for a parameter. If the client component is interested in the 'best' value, it subscribes to the unqualified item (without

specifying the group) and the server decides

which one it is, based on the priority list and

current qualities, (see Fig. 5.)

connect to: Name Quality

Speed Manual.Speed ^

return:

Pos. Speed )^

CanOpen.Speed /

CanOpen. Speed DefaultSpeed /

Figure 5. Example of Osyris OPC connection using an unqualified item name.

Further extension of the OPC standard is the meta-information contained in the "Events' OPC group. This concept is used to notify the

client that the best source of data has changed.

In this way a fallback mechanism is implemented.

The OPC standard includes also a timereferenced interface to the past data, so called

historical OPC. Unfortunately it caimot be employed in the CIRC context, as space reference

is missing. OPC can be also accessed remotely

via DCOM. It is not used directly by the Osyris

framework, but can be advantageous for debugging, scripting or Web clients.

4.3. Ribbon database

As described in [1], ribbons (Fig. 6.) can be

used as a permanent storage for design, mission

and achieved work.

For each machine the tool geometry (defined in mission or measured) is a machine

ribbon generator. There exist one dynamic rib- bon for each machine, containing data gathered

in real time (for more complex tool geometries

multiple ribbons are foreseen). The recorded

position is represented by a ribbon diagonal,

with the parameters assigned to it.

Ribbons provide following services: Map visualisation of the parameters

< Storage for cooling model and other algorithms

Geometrical searching and iteration Parameter interpolation, e.g. elevation,

thickness interpolation

Curvilinear transformation.

diagonals

Figure 6. Sample ribbons in geographic coordinates representing: a - road axis, b - road

edge, c - road surface and d - machine path

4.4. XML interfaces

The interfaces between the on-board and the Office components are based on the XML stan- dard. XML standard is wide spread in Internet applications and many tools are available. A

concept central to XML is the separation of the information contents and format. The information contents of the geometry-based Osyris

XML files is based on ribbon concept.

At the beginning of work the on-board must

be supplied with mission information (worksite

geometry, designed values of the work pa- rameters like speed, fleet configuration). At the end of the work the achieved information has to be exported. There is also a request-response

schema, allowing the transfer of the current work state at any time. The detailed schema has

been defined for each exchange file format.

5. DISTRIBUTED OPERATION

5.1. Wireless communication

Wireless communication between machines

is based on a reliable multicast implemented

upon Internet datagram (UDP) protocol. Typi413
cally WaveLANs are used as physical transport. Ribbons with parameters are automatically synchronised among the machines. This

property can be used to implement distributed

algorithms (see the following subchapters).

5.2. Distributed pass counting

One of the most valuable information con- ceming the quality of compaction comes from

the pass counting. Given the past position of

the compactor, the number of the done passes can be calculated for each point of the surface,

resulting e.g. in a compaction coverage map.

On the most worksites at least two compactors

are working together. The coverage map is only

then useful if it contains passes from all the machines, and this is guaranteed by the wireless

communication algorithm.

5.3. Cooling model

Another important parameter to take into account during the asphalt laying is the temperature of the asphalt layer. Attempts to measure the surface temperature of the asphalt at the compactor using infrared sensors are umeliable

due to the high influence of the wind speed on

the surface temperature.

CANopen Sensors Paver

OPC Server Cafculation

Ribbon DB

A

Wireless

Transmission

R&bon DB^1 ^ Presentaticm

OPC Sever Compactor

Figure 7. Cooling model as an example of a

distributed application in the OSYRIS system

To calculate the evolution of the temperature inside an asphalt layer, a mathematical

model has been used. The model parameters

like layer thickness and asphalt temperature at

laying can only be measured at the time of

paving on the paver, but the results of the core temperature calculation are most interesting for the compactor operator, giving him the very

valuable information about the time left to fin- ish the compaction (Fig. 7.).

6. CONCLUSIONS

The presented on-board structure is universal: all the relevant process parameters are rep- resented in uniform and coherent way and can be transparently accessed on all the levels of

the system. Pre-existing standards have been

used as a base for the Osyris interfaces. The presented solution grants the required

flexibility and enables advanced, distributed

functions, for example distributed pass count- ing and real-time simulation of the asphalt

cooling (cooling model).

Validation of the proposed framework on

the worksite is planned for Autumn 2002. The

specifications of the interfaces will be published at the end of the project.

Acknowledgements

The work described in the paper was carried out in the framework of the European Project

OSYRIS: Open System for Road Information

Support (Growth No. GRDl-1 999-108 15),

2000-2003 [5].

7. REFERENCES

[1] J. Jurasz, Universal digital environment

model for computer integrated road construction. Proc. 18* ISARC 31-36, Cracow

2001

[2] A. Ligier, J. Fliedner, J. Kajanen. F. Peyret,

Open System For Road Information Support. Proc. 18* ISARC, Cracow 2001

[3] F. Peyret, J. Jurasz, A. Carrel, E. Zekri, B. Gorham: The Computer Integrated Road

Construction project. Automation in Construction 9 (5-6) (2000) pp. 447-461.

[4] OPC Foundation at http ://vAvw. opcfoundati on. org

[5] Osyris Website at http:// www.osvris.org

414
OFFLINE PATH PLANNING OF COOPERATIVE MANIPULATORS USING

CO-EVOLUTIONARY GENETIC ALGORITHM

by

M.S.Ajmal Deen Ali\ N. Ramesh Babu* and Koshy Varghese^

^Dept. ofMechanical Engg., I.I.T. Madras, India, email: nrbabu@iitm.ac.in

^Dept. of Civil Engg., I.I.T Madras, India, email: Koshy.Varghese@asu.edu

( Currently on Sabbatical as Visiting Eminent Scholar at Del E. Webb

School of Construction Arizona State University, Tempe, AZ)

ABSTRACT: This paper presents a new path planning approach using

Coevolutionary genetic algorithm (CGA) for automating the path planning of two

Cooperative construction manipulators. A methodology based on the concept of

configuration space (C-space) technique in conjunction with the Coevolutionary

genetic search is used for generating the path. The paper proposes a method for

finding the minimum distance and collision free path using CGA. It uses an

interference detection algorithm that runs in parallel with CGA to check collision

between obstacle and cooperative cranes during path planning. The effectiveness of

CGA is compared with other search approaches like A* and Genetic Algorithms GA.

KEYWORDS: Cooperative manipulators. Path planning, Coevolutionary genetic

algorithm

1. INTRODUCTION

Cooperative manipulators are being widely

employed in construction and assembly for

handling medium to heavy objects. Path

planning of cooperative manipulators is quite

different from path planning of a single

manipulator. When the object to be lifted is too heavy or large for a single manipulator, options

such as specially assembled equipment such as jacking systems and cooperative use of multiple

medium capacity manipulators can be a suitable

alternative.

Path planning techniques are classified based on

the criteria such as dimension of space, mobility

of manipulator and obstacles, representation of

space and nature of information gathering [1-6].

Trajectory planning of two manipulators,

cooperating to manipulate the same object, was

solved using genetic algorithm (GA) [7]. Evolutionary algorithm has been used to find

time-optimal trajectories of two coordinating

manipulators sharing the same work space [8]. Customized genetic operators such as analogous

crossover, which suits certain problem

situations, was also designed [9]. Recent efforts include the development of natural systems that can capture key features such as Co-evolution

and Life Time Fitness Evaluation, for solving

path-planning issues [10].

Earlier attempts for path planning include Hill climbing search. A* search and Genetic

Algorithm (GA) search [11, 12]. These

approaches have certain disadvantages like excessive computational time, memory

requirement and non-optimal paths. Recent

works utilize the concepts of co-evolutionary

genetic algorithm (CGA). Two populations

constantly interact and co evolve in case of

CGA.

A 2-D path-planning problem using CGA was

attempted [10]. This paper presents a new

approach to solve the 3-D path-planning

problem of cooperative manipulators using

CGA.

2. PROBLEM STATEMENT

415
This section presents the details of a pathplanning problem involving two spatial

cooperative manipulators, each of 3 DOF with

hinged base. Two important considerations of

cooperative manipulators path planning are:

(a) Ensuring cooperation between the two

manipulators during lifting.

(b) Handling the computational complexity

of the problem based on the DOF of the

cooperative manipulator system and its movement in obstacle clustered

environment.

a) Ensuring cooperation between the

two manipulators during lifting

Cooperation between the two manipulators is ensured by (i) Nature of movement of

cooperative manipulators, (ii) Spatial distance

between the hook ends of the manipulators

during cooperative lift, (iii) Altitude difference

between the hook ends of the manipulators and

(iv) Hoist limit evaluation for both manipulators.

Nature of movement represents the movement

between the two arms, which can be either

synchronous or asynchronous. A synchronous

movement refers to the identical movement of

different joints of cooperative cranes between

two steps. In case of asynchronous movement,

the movement between the two successive steps

will not be the same.

The spatial distance between the boom tips of

the manipulators is kept within object length ± 2

units. When the spatial distance between the

boom tips of both manipulators is different from

the object length, the sloping of load line occurs. This can be computed by (Figure 1).

|3 = tan-^ rp_"1 H)

where 'HL' - hoisting length of the hook and 'D'

- Off-lead i.e. displacement of the hook from

boom tip. Let 'W be the vertical component of

the load transferred from the object to the

manipulator and 'Wa' the actual load acting

along the load line of the crane. 'Wa' is calculated by

Wa = W / Cos P (2)

(W - Wa) is the additional load transferred to the crane due to the slope '(3' of the load line. This results in additional load transformation to the manipulators.

If the altitude difference (H1-H2), as shown in

figure 2, exists, different loads will be acting on

the hook ends. This results in more payload

acting on a particular manipulator. In order to limit the extra load on the crane, an altitude

difference of '3' units is considered.

Hoist limit evaluation represents the safety to be

considered in hoisting the rope in either

direction i.e. up or down from the ground level. Minimum limit is considered as '0' unit i.e. at ground level and maximum position is boom tip

position, considered above ground level, which

keeps on varying depending on the luffing angle.

b) Handling the computational complexity of

the problem based on the DOF of the

cooperative manipulator system and its movement in obstacle clustered environment

Collision of the cooperative manipulator system

in the obstacle-clustered environment can occur due to (i) manipulator- 1 colliding with obstacles,

(ii) manipulator-2 colliding with obstacles, (iii) object colliding with obstacles and (iv)

manipulator- 1 colliding with manipulator-2.

The feasible movement of the manipulators in the obstacle-clustered environment is ensured by means of interference detection algorithm that assesses the different configurations of the

manipulator for collision. The collision checking

is done by means of interference checking

algorithm that performs interference check

between line and plane segments. For this purpose, the obstacle is represented by many

plane segments and cooperative manipulator

system is represented by many line segments.

A test problem considers two spatial cooperative

manipulators performing asynchronous

416
movement. Both manipulators are identical in size and shape. Table 1 shows the configuration

of different arms. The upper and lower bound

movement for different arms are shown in Table

2.

3. SEARCH METHODOLOGY

This section covers the details of modeling and

implementation for 2x3 cooperative manipulator

system using A*, GA and CGA.

3.1 A* search in open C-space

A* search is a free search in the open C-space

with on-line feasibility check [12]. The main

advantage of this search is that it has the ability to go back to any node which was visited earlier. The step size values of swinging, luffing and

hoisting for generating neighbors are 5, 5 and 1.

3.2 GA search in open C-space

GA search is a free search in the open C-space

with on-line feasibility check [11]. The

population consists of 250 strings. Each string in GA represents movements of the manipulator

from pick to place location. A typical string with

fifteen intermediate configurations between pick

and place location is shown in figure 3.

3.3 CGA

In this approach, two populations known as solution population and test population

continuously interact with each other to evolve

an optimal solution.

a) Solution population: Path representation as a string

The solution population consists of 200 strings.

Each string represents the movement of

manipulator from pick to place location (Figure

3). The number of steps between pick and place

location is taken as fifteen.

b) Test Population

The test population consists of test conditions

known a priori (Figure 1 and Figure 2). It consists of (1) spatial distance between the hook

ends of the manipulators i.e. object length ± 2

i.e. 15-1-2 and 15-2, (2) altitude difference

between the hook ends of the manipulator i.e. (H1-H2) = '3' units, (3) hoist limit evaluation

varies according to boom luffing angle and (4)

collision of the cooperative manipulator system

with the environment that consists of (i) manipulator- 1 colliding with obstacles, (ii) manipulator-2 colliding with obstacles, (iii) object colliding with obstacles and (iv)

manipulator- 1 colliding with manipulator-2.

c) Encountering

In CGA encountering is the process in which

one string from solution population and

randomly chosen test conditions from test population interact with each other to produce a

better offspring. It consists of three stages.

STAGE 1

Fitness is found for all the individuals in both

the populations by subjecting them to encounter

'3' randomly selected individuals from the other

population. A solution receives a payoff of one

if it satisfies the test. Otherwise, it receives a

zero. The opposite is true for test. It gets a payoff of one if the solution encountered does

not satisfy a test. Each individual - test or

solution - has a history, which stores the payoff

resulting from such an encounter. The fitness of an individual in solution population is estimated

by

Fs = P(x)[l+(l/H,)] (3)

where P (x) is the objective function and Hj is the total payoff for that individual. The objective

function is defined as the sum of square of

absolute differences of identical joint angles

between successive configurations for all the

joints of the manipulators as the cooperative

manipulator system moves from pick to place

location. It is estimated by

n-1 m

417
p(x) = i. I |0i,,,|-e,j|- (4)

i=i j=i

where 'n' represents the number of

configuration sets and 'm' represents the number

of joint parameters required to define a unique

position of the cooperative manipulator system

and '6

i, is the value of joint angle of j"' link in

i'*' configuration set. The fitness of an individual

in the test population is estimated by

F = Ht. (5)

where Ht is the total payoff for that individual.

An individual according to their fitness value i.e. minimum distance and payoff for first population and only payoff for second

population, is arranged in descending order in their respective population

STAGE 2

In this stage, one fittest string from the first population and three randomly selected test conditions from the test population are subjected

to encounter. The selection of this string and test conditions are biased towards highly ranked

individuals i.e. the fittest individuals are more

likely to be selected. The result of such an

encounter is T if any test is satisfied (or) '0' in case of violation. The fitness (or) maximum payoff for this string is calculated. According to its fitness value, it is ranked in descending order in the first population. A similar operation is performed on the test population also. Since

both the populations are sorted based on their fitness values, an individual might move up and

down in its population as a result of the update

of its fitness.

STAGES

In this stage, the conventional GA process is followed. Two strings from the first population

are selected based on their fitness. An offspring

is created by the process of adaptive crossover. Adaptive crossover is illustrated in figure 4, i.e. the same intermediate configurations on both

parent 1 and parent 2 will be checked for their payoff value. The particular configurations, with

highest payoff, will be inserted in to the same

configuration in the offspring. This cycle is repeated for the remaining configurations until

all the configurations in the offspring are filled.

Mutation is applied in an adaptive manner with a probability of 'O.T. Adaptive mutation is implemented in order to reduce the angular

displacement between adjacent configurations as well as to bring the cooperation between

manipulator 1 and manipulator 2. All the joint

angle positions are subjected to this probability.

If they are satisfied, they will undergo adaptive

mutation as shown in Figure 5. For example, the

swing position as marked by arrow '1" is to be

subjected to adaptive mutation (assumed to be

the j"' position) then the j-6"^ (arrow 2) and j+3'^'' position (arrow 3), both are swing positions, will

be considered. A random number will be

generated between the swing positions

considered. Similarly if luffing position is considered as j"^ position, then the j-6''^ and j+3'^'' positions i.e. luff position, will be considered for mutation. A random number will be generated

between these points. The value generated is inserted in the j''^ position. This process is applied to all the joint angle positions, which

satisfy the mutation probability condition.

Figure 6 shows the methodology adopted for

finding a feasible coUision free string with CGA.

The fitness of offspring is estimated as the sum

of payoff received from encounter with three- selected test conditions. The offspring is then

inserted into the solution population based on

their fitness values. To accommodate this new

offspring, the lower fitness value string in the

solution population is deleted. The procedure

adopted in STAGE 2 and STAGE 3 is continued

until the fitness of string in the solution

population remains almost the same in ten consecutive generations.

4. RESULTS AND DISCUSSIONS

The manipulators shown in the section 2 are considered for cooperative path planning with

the proposed CGA approach. In order to asses

the effectiveness of this approach, two different

approaches such as A* and GA for path

planning were also considered and these

approaches were developed using C-i~»-

418
programming language and implemented on the same platform, i.e. 333 MHz Pentium II processor PC with 128 MB RAM with Windows

NT operating system. The computation time for

finding the feasible path from pick to place

location using different approaches like A"*", GA

and CGA, depends on the lift path and position

of the pick and place location in the obstacle

clustered environment i.e. lifting an object

vertically up may be simpler to compute than

another path. For path planning of cooperative

manipulators, C-space approach was adopted for representing the position of the manipulators.

Performance of A*, GA and CGA for path

planning of 2x3 cooperative manipulators is assessed and the results are presented in Table 3.

4.1. A*search

The minimum incremental movements of

different joints of manipulator are shown in Table 4. A* search could determine the feasible

path from pick to place location in 30

intermediate steps. The time taken for finding

the feasible path is 320 minutes. The minimum

distance, in terms of linear movements, from

pick to place location is 73 units. If A* is allowed to search the C-space exhaustively i.e. with 1 degree increment, the time taken will be more than 2000 minutes. The disadvantage with

this step angle increment is that pick and place

angle has to lie within the increment angle of

search; otherwise the search will never give a

feasible solution.

4.2. GA search

Total number of joint angles to represent a unique configuration is 6; Range for different

joint angles swing: 0-360 degrees: luffing: 30-

80 degrees: hoist: 0-39 units; Number of

configuration sets representing a string

excluding pick and place location: 15.

For generating the path with GA, the number of

intermediate configurations between pick and

place location is fixed as fifteen. The time for computation of feasible path with GA is 183

minutes. The minimum distance in terms of

linear movements from pick to place location is 79 units. GA computes the collision for all the

configurations in the population, due to which a considerable time was spent.

4.3. CGA search

Total number of joint angles to represent a unique configuration: 6; the arm configurations

and its lower and upper bound values are shown

in Table 3 and Table 4. Number of configuration

sets representing a string excluding pick and

place location: 15.

The computation time for finding a feasible path

is 20 minutes. The minimum distance, in terms

of linear movements, from pick to place location

is 58 units. CGA subjects only two strings i.e. one fittest string and one offspring for collision

computation in the successive generations

except the initial fitness ranking generation, thus

saving a large amount of time.

The pictorial view showing the object position at intermediate locations for A*, GA and CGA are shown in figure 7, figure 8 and figure 9. These

discrete object positions are drawn by

converting the intermediate configuration angles

of the cooperative manipulator system in Cspace to the Cartesian Space.

From the figure 7, it is observed that the discrete

object positions are placed in a zigzag position

in A*. This is due to the move taken by the

search for adjacent feasible configuration when

it encounters one. In the Figure 8, it is observed

that discrete object positions computed with GA

are not located at equal intervals. Since the

entire population undergoes cross over and

mutation at the same time, the possibility of a

larger random joint angle movement exists. In the Figure 9, it is observed that discrete object

positions computed with CGA are almost

located at equal intervals. Two populations i.e. highly biased individuals from string population

undergo adaptive cross over and parameter

based mutation, which results in the possibility

of smooth movement of joints with equal

interval of displacement.

5. CONCLUSIONS

419
This paper presents a new approach using CGA

for automated path planning of 2x3 cooperative

manipulator system. The suitability of CGA for

offline path planning in comparison with other

techniques was demonstrated. From the results presented in this paper, the following

conclusions can be made:

1. CGA in conjunction with C-space

technique proves to be an effective

approach to solve path planning

problems of cooperative construction

manipulators in complex environment

2. Search using CGA is found to be

effective approach in terms of

computation time, when compared to other search techniques like A* search

and GA search.

3. CGA was found to be efficient in generating the shortest path from pick to place location, when compared to other

search techniques like A* and GA.

The future work attempts to investigate the

suitability of this approach for more complex

cooperative manipulator applications like 2x4

i.e. two manipulators each with 4 DOF.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the

Department of Science and Technology (DST),

New Delhi, India, for the financial support given

to this research work vide Grant No. III. 5(23)/2000-ET.

6. REFERENCES

[1] Latombe, J.C. (1991) Robot Motion

Planning, Kluwer Academic Publishers,

Norwell, Massachusetts.

[2] Schwartz, J.T. and Sharir, M. (1988) A

Survey of Motion Planning and Related

Geometric Algorithms, Artificial Intelligence,

37, 157-169.

[3] Udupa, S. (1977) Collision Detection and

Avoidance in Computer Controlled

Manipulators, Ph.D. Dissertation, Department of

Electrical Engineering, California Institute of

Technology, California.

[4] Lozano-Perez, T. (1983) Spatial Planning: A

Configuration Space Approach, IEEE

Transactions on Computers, C-32(2), 108-120.

[5] Khatib, O. (1986). ''Real-Time Obstacle

Avoidance for Manipulators and Mobile

Robots,'" International journal of Robotics

Research, Vol. 5, no. 1, pp. 90-98

[6] Schilling, R. J. (1990). Fundamentals of

Robotics: Analysis and control, Prentice-Hall,

Englewood Cliffs, New Jersey

[7] Sun, S., Morris, A.S. and Zalzala, A.M.S.

(1996) Trajectory Planning of Multiple

Coordinating Robots using Genetic Algorithms,

Robotica, 14, 227-234.

[8] Rana, A.S. and Zalzala, A.M.S. (1996) Near

Time Optimal Collision Free Motion Planning

of Robotic Manipulators using an Evolutionary

Algorithm, Robotica, 14, 621-632.

[9] Davidor, Y. (1991) Genetic Algorithms and

Robotics: A Heuristic Study for Optimization,

World Scientific Publishing Company.

[10] Paredis, J., Westra, R., (1997) Coevolutionary Computation for path planning.

Proceedings 5"^ European Congress on

Intelligent and Soft Computing (EUFTT 97), H.-J Zimmermann(ed.), Verlag Mainz, Aachen.

[11] Sivakumar, PL., Varghese, K. and Ramesh

Babu, N. (1999) Path Planning of Construction

Manipulators using Genetic Algorithms,

Proceedings of the 16'*' International Symposium

on Automation and Robotics in Construction,

Madrid, Spain, 555-560.

[12] Sivakumar, PL., (2001) Automated Path

Planning of cooperative crane lifts using

Genetic and heuristic searches, M.S. Thesis,

Department of civil engineering, Indian institute of technology Madras.

420
Figure 1 Increase in Load Transferred to the manipulators due to slope of the load line

Boom

Base

Counter

weight

Boom TipBoom

Base

Counter

weight

Figure 2 Difference in load shared by hook ends of the manipulators

Table 1 . Manipulator arm configurations

Arm

configurations

Length Breadth Height

Base 10 8 2.5 Boom 40 3 3

Hoisting Rope 39 unit

Table 2. Upper and lower bounds for the

Arm Base Boom Hoisting

Rope

Lower 0° 30° Ounit

Upper 360*^ 80° 39 unit

421
Configuration of

Robot 1 Robot 2

Configuration of

Robot 1 Robot 2

e, 6: 63 64 65 e6 1 2 3

1 13 14 15 e, 02 63 64 66

(Pick location) (Intermediate location) (Place location)

e, 6: 03 04 O5 06

Figure 3. A typical string with fifteen intermediate configurations of 2x3 cooperative manipulators

between pick and place location

Parent string 1

Parent string 2

Pick 1 2 3 13 14 15 Place

Pick 1 2 3 13 14 15 Place

Pick 1 2 3 .

1 13 14 15 Place

Offspring

Figure 4. Adaptive cross over

Pick

Place

320 70 2 320 70 2 260 60 3 300 50 5 290 56 6 280 60 3 . . A 2 1 i ^ 3

I Insertion point

Random number generation between 320 and 300

Figure 5. Adaptive mutation

422
Start

Input: Pick and Place

Probability of Cross over and Mutation Max Generations, Convergence Criteria, Population Size, Number of Intermediate Configurations

Find the fitness for all the strings in the initial population and

arrange for them in the descending encounter between a string from the solution population, and the three-test condition from

the test population. Store their fitness in their history

Enter the siring and test condition in their appropriate rank position in the solution population and test population according to their fitness

YES

Print the details of the best solution NO 1 Generation = Generation + I 0:0

Reproduction: Part sum method (according to descending order of fitness) Create an offspring through crossover (adaptive cross over) Apply adaptive Mutation Operator

Compute fitness for this offspring by subjecting it for encounter with three random conditions from the other population

Enter the offspring (string) and test condition in their appropriate rank position

in the solution population and test population according to their fitness

Is the Best Solution of the Present Generation better than what is already stored?

NO

YES

Replace the best solution already

stored by the best solution of

the present generation

Figure 6: CGA methodology for finding feasible collision-free string

423
Table 3. Performance comparison of A*, GA and CGA for 2x3 cooperative manipulator path planning

Method Earlier approach [11,12] Current approach

A* GA CGA

Pick location

Place location

Number or generation

CPU time (minutes)

Distance in terms of linear

movements (units)

[320,70,2][320,70,2]

[270,40,2] [270,40,2]

320

73

[320,70,2] [320,70,2]

[270,40,2] [270,40,2]

540

183

79

[320,70,2] [320,70,2]

[270,40,2] [270,40,2]

750

20

58

Table 4. Incremental angle between adjacent moves of manipulator

Arm Base Boom Hoisting

Rope

Lower 0' 30° 0 unit

Upper 360° 80° 39 unit

Increment 5° 5° 1 unit

Figure 7. Pictorial view showing the path

generated by A* for cooperative manipulators

Figure 8. Pictorial view showing the path

generated by GA for cooperative manipulators

Figure 9. Pictorial view showing the path

generated by CGA for cooperative manipulator

424
MODEL FOR AUTOMATED ROAD-CONSTRUCTION CONTROL

by

R. Navoni , Y. Shpatnitsky^ and E. Goldschmidt^

ABSTRACT: A survey of current practices revealed that very little control is normally done in earthmoving management. A model to control road construction projects was developed. The model is based on the concept of automatically

measuring performance, by measuring locations at regular time intervals, and

converting them into controlled parameters. According to this concept, control

algorithms convert the measured locations to produce two types of real-time control data: progress and productivity. Locations are measured with a Global

Positioning System (GPS). Field experiments conducted with the prototype of

the GPS measurement system prove its suitability as a Location Measurement

Module.

KEYWORDS: Automated Data Collection; Benchmarking; Control;

Earthmoving; GPS; Monitoring; Road Construction.

1. INTRODUCTION

A major obstacle for automated project perform- ance control is measuring the various project per- formance indicators such as cost, schedule, labor

productivity, materials consumption or waste, etc. Advanced technologies, which can be used for on-site measurement and control of project indicators, are emerging and their costs are declining.

The work presented here is part of the Technion's

initiative called Automated Project Performance

Control (APPC). This area broadly refers to the

activities taken by the project (or company) management in order to ascertain that the performance of the project is as close as possible to the

desirable one. The performance is measured in

terms of Project Performance Indicators (PPI).

Current efforts focus on automated-data-collection based project performance control, both in building and in earthmoving operations.

The present paper uses a concept of automatically evaluating performance, by measuring indirect

parameters and converting them to the controlled

variable. The system described herewith will measure the locations, as function of time, of all members of a fleet of earthmoving equipment

and convert them to produce real-time control

data. The locations will be measured with a Global Positioning System (GPS).

2. INFRASTRUCTURE-CONSTRUCTION

CONTROL - STATE-OF-THE-ART

The extent of controlling PPI in infrastructure

construction projects is still limited. Current

' Assoc. Prof. - Head. Construction Engineering and Management; Head. Construction Automation Laboratory - Faculty of

Civil Engineering, National Building Research Institute, Technion City, 32000 Haifa, Israel, ronie@tx.technion.ac.il,

http://tx.technion.ac.il/~ronie ^ M.Sc. Candidate - cvyaniv@tx.technion.ac.il. ^ Ph.D. Candidate - cveytan@tx.technion.ac.il.

425
methods normally use manual data collection.

The area where Automated Data Collection

(ADC) is used for real-time monitoring is quality

control and methods that provide data to the

equipment's operator, making its manipulation

easier.

2.1 Manual Control of Infrastructure Projects

Current practices of project management control

in Israel were surveyed in 12 leading construction companies whose main line of business is infrastructure, road construction and earthmoving. The survey was done to assess the state-of- the-art of project management control and the

need for it. Most of the surveyed companies

admitted that they were not doing any control,

but they agreed that if such tools were to exist

they would be very willing to use them.

Some of the companies control progress by fol- lowing up the flow of materials to the site. The

bills-of lading are collected and sent to the main

office where the quantities are plotted as functions of time and compared to the planned val- ues. The users of this method are generally dissatisfied, reporting that this procedure is inaccurate, error prone (because of the manual data

input), and labor intensive. One of the reasons for

the inaccuracy is that the planned material con- sumption assumes theoretical cross-sections,

ignoring the difference between the design and

the actual physical measurements of the road

structure.

2.2 Real-Time Control in Earthmoving

Projects

Most previous attempts to automate earthmoving

operations are surveyingoriented, yielding impressive results in quantity

and quality control. Another aspect of heavy

equipment automation is monitoring the operation of the equipment, making its manipulation

by the operator easier [e.g. Lee et. al 1997,

Peyret et. al 2000, Kannan and Vorster 2000,

Bouvet et. al 2001]. The present paper presents

the first attempt to automate the control of earthmoving project management.

Lee et al. [1997] proposed a real-time control

system to improve the productivity and the quality of asphalt paving operations. The system has

four modules using RTK (Real Time Kinematic)

GPS. Another model that uses the same technology is called IMPACT [Tsemg and Russell 1997].

The model was developed for planning and controlling earthmoving equipment to improve its productivity and safety. The productivity

improvement can be achieved by better planning,

using simulation. The safety can be enhanced by

position measurement, using RTK GPS and controlling the movement to avoid collision.

Recently several other applications of GPS for

earth moving equipment control were introduced

- most of them with RTK GPS. Peyret et al. [2000] describe a 'Computer Integrated Road

Construction' (CIRC) project, aiming at introducing a control and monitoring tool for road pavements construction. The new tools were designed

to bring to the sites significant improvements by

creating a digital link between the design office

and the job site.

Krishnamurthy et al. [1998] describe an automated paving system for asphalt pavement compaction operations. A semi-automated path-planning real-time guidance system that aims towards

automating the paving operation was developed.

This system accepts relevant paving project

inputs, generates appropriate path plans for the

compactor, performs a graphical visualization of

the generated path plan and offers real-time guid- ance capabilities using GPS technology.

3. AUTOMATED CONTROL MODEL FOR

ROAD CONSTRUCTION

The development of the concept of automatically

monitoring performance, by measuring indirect

parameters and converting them, was developed

in recent years at the Technion [Goldschmidt and

Navon 1996 and Navon and Goldschmidt 1999].

This Section sets the theoretical framework of the

model and describes the model.

426
3.1 Conceptual Framework

The system will measure the locations of all members of the fleet of the earthmoving equipment at constant time intervals. An algorithm,

described below, will convert these locations to produce two types of real-time control data: progress and productivity. The location will be

measured with GPS. The system will use these

locations together with data extracted from a Project Model (PM)"^ to determine the activity

the equipment is engaged in. its progress, and its productivity. The result will be compared with

the planned progress and productivity to give an

early warning on deviations as they occur, and

will enable the analysis of the causes.

3.2 Model

The model (Fig. 1 ) compares between the

planned and the actual values of progress and

productivity variables. The model has two main

sources of data: ( 1 ) The Project Model, containing the planned schedule, the productivity, and all the data regarding the physical design of the road

(layout, cross-sections, etc.). (2) The Location

Measurement Module (LMM), using GPS. This

module measures the location for each member

of the fleet at regular time intervals. The module

records the time of measurement, the identification of the equipment and its location.

The model includes four interfaces, which extract

all the relevant data from the PM. These inter- faces are: Schedule Interface (SI), Geometry

Interface (GI), Quantity Interface (QI) and

Productivity Interface (PI). The SI begins the

process by extracting all the pending activities - these are all the activities whose predecessors are completed, which means that they can be active on the given day.

Specific Work Envelopes (WE)^ are calculated

for each pending activity, based on information in

the Knowledge Base, which includes a typical

work envelope database, and on the geometrical

information extracted by the GI interface from

the PM. The WEs correspond with planned work

sections, as represented in the schedule. Next, a geometrical calculation associates each of the

locations to these specific work envelopes, by

checking if the measured location is included

within the WE. This, together with Decision

Rules from the KB^, enables the model to deter- mine which activities are actually being per- formed. Once the model identifies that a new

activity has started, it also determines which of

the activities are completed. The cycle ends by

determining the actual time spent performing

each activity, and the productivity, which is based on this time and the completed quantities,

extracted by the QI. These data serves as a basis

for the output of the model.

The output of the model compares the actual per- formance, as measured and calculated by the

model, to the planned one. It includes:

• A comparison between the actual productivity

and the planned one, extracted from the PM by

the PI.

• A comparison between the actual progress and

the planned one according to the updated schedule extracted by the SI.

The output of the model serves a variety of managerial functions, such as monitoring and taking

corrective measures.

4 The Project Model includes a physical

description of the road and a description of the

activities needed to construct it.

5 A work envelope is defined to assist the association of the equipment's location to a pending

activity, as follows: an area, or volume, where a

piece of equipment, working on the road, could

be located. The shape and type of a work envelope depends on the nature of the activity, on the

construction method, or technology, and the type

of equipment.

^ The decision rules are designed to (1 ) help

associating locations not included in a work

envelope, or included in more than one envelope.

(2) Determine completed activities.

427
4. CONCLUDING REMARKS

The first stage of the development was to ascertain that there were no technological barriers. Consequently, a feasibility test of the LMM was

carried out. The experiment was planned to check

the suitability of GPS, and the pertinent software.

The feasibility test is not described here due to space limitations. The experiments confirm that GPS is suitable for the purpose of controlling

progress and productivity of earthmoving operations.

The Technion's Automated Project Performance

Control (APPC) group is currently engaged in a number of research projects relating to Automated Data Collection. The most notable

direction of the group is that of measuring locations at regular time intervals, or other indirect

parameters, and using them to automatically control productivity and progress.

5. REFERENCES

Bouvet, D., Froumentin, M., Garcia, G,. (2001).

"A Real-Time Localization System for

Compactors" Automation in Construction, 10(4):

417-428.

Lee, H., Russell, S, H., Schmitt, R, L,. Tsemg, H,

R, Hanna, A, S., Bahia, H, U., (1997), "Computer

Integrated Methodologies for Real Time Control

of Asphalt Paving Operations". Proceeding of the

1 4th International Symposium on Automation

and Robotics in Construction (ISARC), 8-11

June, Pittsburgh Pennsylvania: 423-431.

Navon, R. and Goldschmidt, E. (1999).

"Automated Labor Control." Proceedings of the

Joint Triennial Symposium (CIB Commissions

W55 & W65 with the participation of W92)

Customer satisfaction: A focus for research &

practice, CD-ROM. Cape Town (South Africa),

University of Cape Town.

Peyret, F., Jurasz, J., Carrel, A., Zekri, E., Gorham, B. (2000). "The Computer Integrated

Road Construction Project" Automation in

Construction. 9(5-6): 447-461.

Tsemg, H.R and Russell, J.S., (1997), "Instantaneous Motion Planning and Controlling

Tool )IMPACT) for Construction Equipment".

Construction Congress Proceedings - ASCE,

New York, USA: 1020- 1029.

Goldschmidt, E. and Navon, R. (1996).

"Automated Real-Time Manpower Productivity

Control". The 8th International Symposium on

Organization and Management of Construction.

Glasgow (UK): 199-205.

Kannan, G, Vorster, M. (2000). "Development of

an Experience Database for Truck Loading

Opertions." Journal of Construction Engineering

and Management, ASCE, 126(3): 201-209.

Krishnamurthy B. K., Tsemg H. R, Schmitt R.

L., Russell J. S., Bahia H. U. and Hanna A. S. (1998). "AutoPave: Towards an Automated

Paving System for Asphalt Pavement

Compaction Operations". Automation in

Construction, 8(2): 165-180.

428
SI, GI, QI, PI

Intetfaces

Detenrnne "^ATE

Associate

Location to "WE

LMM

Determine:

Actual Activity

Completed Activities

Actual Duration per Activity

%

im.i Jn.1 ^.-l

Actual vs. PI anned Progress

Actual vs. Planned

Productivity

Figure 1 : Model Architecture

429

FORCE SENSOR BY DRIVING HYDRAULIC CYLINDERS:

IDENTIFICATION OF INERTIAL PARAMETERS AND TESTS

F. Malaguti, S. Zaghi

Abstract: Force feedback sensors are useful for the planning of robotic digging

trajectories. In particular, when combined with force-control algorithms it becomes

possible to sense buried objects and to determine the weight of excavated materials. The

proposed force sensor system makes use of hydraulic cylinder pressure and thereby measures machine force indirectly. Successful implementation of such an approach will elimmate the need for expensive, direct-force sensors. Measurements of pressures in candidate cylinders were compared with laboratory-measured stroke and force. To

measure force in every position and during the motion of a backhoe, kinematic, static and

dynamic inertial parameters of the bucket, arm and other links have to be considered.

From these data a friction model of the hydraulic cylinders can be developed. The present

work involves the determination of these friction parameters for an excavator arm using

position measures of the bucket and boom, cylinder pressures and the attitude of the excavator boom. Combined, these represent the "dynamic tare" of system. The work

includes a practical approach to filtering regression matrix to do not measure accelerations. The methods allows one to carry out inertial parameters for a full machine, in order to verified design and drawning of costruction machine or to use as input for simulation of

machine dynamics.

Keywords; digging robot, force sensor, identification, inertial parameters

Introduction

In previous studies [1,2] static and dynamic

analyses of force sensors for digging robots and

on-board force-sensing systems for construction

machines were presented. The force sensor is based on measurement of pressures in two

hydraulic cylinders and angular positions of

two links, e.g. with an excavator, the driving

cylinders and position of bucket and boom

respectively, were measured about an absolute

inertial reference point.

Using two cylinders it is possible to compute variable pairs, e.g. force/force-position

or force/force-direction, by considering the

CNR-CEMOTER, via Canal Bianco 28, 44044

Ferrara, haly, email: malaguti@cemoter.bo.cnr.it

planar movement of two links. This concept is applicable to many types of construction

machines having two or more hydraulic

cylinders.

The continuous measurement of soil-bucket

interaction force is required to predict

interaction force or for real-time planning of

bucket trajectories.

Our method of force measurement does not

require any additional sensors; it makes use of

sensors already available on most construction

machinery. It does, however, require new static and inertial parameters for the mechanism links and their respective accelerations and velocities. Errors in the determination of hydraulic

cylinder force by using cylinder pressure measurements are introduced because of the presence of static and viscous frictions. The

431
proposed new method includes the

determination of these parameters.

We use Newton-Euler notation to describe

the parameters affecting the dynamic equations

of the excavator arm. The parameters are arranged in regression matrix form (eq 1), while

the introduction of a linear filter and

convolution theorem allowed us to transform

the regression matrix into a new system

independent of acceleration of the link. This

independence avoids the requirement for

measuring accelerations of the links (bucket,

stick, etc.). The present work is focused on

experimental implementation of this approach,

considering practical integration of sensors and

software. Tests and experiments were made

using a small size excavator (Figure 1) which was modified to use proportional servovalves

and was powered by an electric motor.

Parameter identification was done off-line using

general purpose PC hardare and computing

software.

1. Dynamic Analysis and Filtering

Dynamic analysis of the excavator arm

shown in Figure 1 was undertaken using

Newton-Euler notation.

Figure 1 shows the arm of small size excavator modified to fit transducers

The following calculations consider the

dynamics of a system comprised of a bucket

and stick, without considering the contribution

of the boom to the overall excavator dynamics.

Considering the angular positions of the

bucket and stick, respectively ft and 6j with

reference to the horizontal, and the torques

trasmitteed by their driving cylinders T2 and T/, the Newton-Euler dynamics of these links is shown with the system.

In e, +

1 22. ^2, C22

'In "F, cos a/

+

^2 1 ^22 m2g_ }2X I22. 7x sin a.

where

/n = /j -1-/722^2/1 cos(02 +a2)+m2li +mir^

112 = ^2 ^2 ^2^1 cos(62 + a2 )+ ^2/2^

I21 = m2r2li cos(02 +CL2)

/22=/2+^2^2^

/zji = rj cos(0j +cXi)

/2j2 = ^2 COs(0i -1-02 +012)+ A cos 01

/Z2i=0

^22 = ^2 COs(0i -I- ©2 + a2 ) Cii =m2r2li sin(02+a2)

C12 = m2r2l\ sin(02 + 0X2

)

C21 = ^2^2/1 sin(02 +0.2)

C22 =0

/ii =/i sin0^

/22 =h cosQ,+l,

hi = h

and / is the inertia matrix, h is the gravity

matrix, is the interaction force on the bucket.

This system was arranged in matrix

regression form as:

At = w(0,0,0)i> (2)

where Ax = [T2 Xi — X2 ]^ , and the inertial parameters are defined as (3).

432
<D =

2 /i +m2/i +mjrf

W2r2 cos a

2

^2/2 sin a2

m2/i + mjrj cos(ai

)

miTj sin(ai

)

(3)

represents the relationship between the angles ^

and the rod extensions L, The friction of the hydraulic cylinder is difficult to model and compute, because it depends on many factors, for example the types

of seal and load pressure. However the same

method of identification of inertial parameters

allows for the contribution of friction too.

To solve equation system (2) without the

measurement of angular accelerations of links, we had to filter equation (1) linearly. By

convolution, the filtered torques become

Xf=f*h + f{0)h-M0) + f''8

were / is the linear stable filter, * is the sign of

convolution.

at ^ = -/(e)e+c(e,e)e+G(e)

In this way a filtered regression form of the arm dynamics can be written as:

Ai^ =W^(e,e)D (4)

where the vector of parameters 0 does not change, since the filter is linear.

Until now we have used the "torque" term,

but it is produced by the cylinder force and

crank length. The torques are related to hydraulic pressures of the cylinder by the

following equation

Figure 2: Typical example of mechanism driven by

hydraulic cylinder, where r is the variable length of

cylinder, L and f the fixed lengths.

From traditional Coulomb friction theory

Ff =/,sgn(v)+/,v (6)

where v is the velocity of the rod, we have two

friction coefficients, the fc Coulomb friction coefficient and the fy viscous friction coefficient. Remembering that xdd = Fdl , the

previous coefficients form the vector of friction parameters :

^f=[fc2 fv2 fcl /vlF (7)

T = FLsin arctan

/sine'

L- f cos 6'

(5)

where L is the crank length, / the distance

between the link and cylinder pins, and 9' is the

angle between those two. This relationship

shows that the torque depends on the angle 0'

(fig.2), which is related to the 6, angles of

links.However, it is also possible to use a polynomial approximation of dQjdL^ , which

2. Inplementation

To filter the regression matrix a simple

stable first order filter was used, having the

simple transfer function f{s)=\ls + \ and the

following impulse response in the time domain

The regression matrix was convolved by

this filter, obtaining the filtered regression

matrix, independent of accelerations.

433
In practice we chose the following transfer

function:

F{s) = ajs + a

,

with a cutting frequency of 20 Hz, a sample

frequency of 100 Hz and a = 125 rad/s . The identification process was based on

Least Square Methods considering the

measured noise of torque, £, only.

At^ =W^(0,0)a) + e

Moreover, the components of the torque

vector

At = - Y

are decoupled, so every link or equation can

be considerd as a single input, single output

system to estimate.

The measurement hardware consisted of

traditional strain gauges and high pressure

transducers. These were used to measure

hydraulic pressure in both chambers of the

cylinders, two resistive angular position

trasducers and a tilt sensor. One position sensor was placed on the

stick-boom pin, the other one was placed on the

pin of the crankshaft that transformed the linear

motion of rod into angular motion (see fig.l).

The angular position sensor location was

chosen for practical reasons, so that the

relationship between the force produced by the

cylinder and the angular position of the bucket was known, based on the kinematics of the

bucket mechanism.

The tilt sensor (Accustar) placed on the

boom of our small excavator provided the

absolute inertial reference to measure the

angular positions of links. Additionally it allowed the determination of the boom angular

position and velocity.

The signals were acquired by a standard

multifunction National Instrument I/O board for PCs and processed using Matlab-Simulink. The

same software was used for off-line system

identification routines.

As discussed previously, the solution to filter dynamic system and its regression form was

chosen to avoid the use of acceleration sensors

or the noisy and inaccurate double time

derivative of angular displacement. However

the regression form needs to measure or estimate angular velocity.

Because the simple method of backward

differencing does not yield good performance,

the angular velocities were estimated using the

Savitzky-Golay filter. In practice this filter, performing a least squares linear regression fit, is a mobile

window of 2nw+l number of samples of

angular position that is fitted with an m-order

polynomial.

^(t)=p,r+pr~'-^-+Pm

The time derivative or angular velocity is derived at the same time. To avoid high-order

calculus the filter parameters were chosen as: nW=3 and m=2. The velocity is thus given as:

v = 2p,t + p{2) .

Also in this case the filtering was done offline.First, static inertial parameters were

determined in the static configuration;

afterward the fitting of all static, dynamic and

friction parameters was conducted during

dynamic conditions, that is, by moving the arm

of the excavator.

In the first case we used the normal

regression matrix because the static conditions

do not depend on accelerations, while under

dynamic conditions the filtered regression

matrix was used.

Many references on identification of

dynamic parameters of industrial robots suggest

the use of specified trajectories to minimize the

conditioning of the data, but in our case it was

impossible to plan suitable trajectories that properly simulate a digging cycle under manual

control.

434
3. Results of estimation The final ersults are shown in Table 2:

The tests to estimate parameters of the

excavator arm can be divided in two parts:

inertial static parameters in static condions, and

all inertial and friction parameters in dynamic

conditions.

3.1 Static estimation

Static estimation was carried out by putting

the excavator arm, and in particular the stick

and bucket, in various positions, where angular

position and torques for each joint was

measured with acceleration and velocity of the

links equal zero. This set of measurements was repeated for a number about 150 samples (positions), to have

small variation in the results. We avoided those

positions corresponding or close to the endstop

of the rods.

In this fu-st part we chose to not include the

static friction parameters in the estimation,

because the static friction depends on many

factors including the characteristics of the

hydraulic fluid, the type of seal, and the time

that the rod remains in the same position,

making difficult to have a reliable model of

friction. The results of the static estimation are summarized in Table 1

,

i (t), [kgm] a, [kgm]

SI 6.17 2.95

S2 12.05 4.45

S3 103.31 23.67

S4 22.78 7.08

Table 1 : Parameter estimation of static conditions

where 0, and G, are the vectors of static parameters and their standard deviations

respectively.

3.2 Dynamic estimation

For the estimation of all parameters in dynamic conditions, the signals were sampled

at 100 Hz for 40 seconds, converted and

processed, to be estimated off-line as described

previously.

parameters Estimated Standard

value deviation

(t)Dl 100.32 kgm- 25.7 kgm-

<t)D-> 186.73 kgm' 33.4 kgm'

3.50 kgm 1.54 kgm

13.71 kgm 3.28 kgm

(1)S4 71.81 kgm 10.07 kgm

(t>S4 35.56 kgm 5.68 kgm

(l)fl 52.23 kgm/s' 25.5 kgm/s'

<^f2 31444.87 kg/s 1257 km/s

(t>f3 35.67 kgm/s" 20.6 kgm/s'

^fA 30167 kg/s 1320 kg/s

Table 2: Parameter estimation in dynamic conditions

One way to value the quality of estimation is to compare the measured and estimated torque

data. Figure 3 shows the measured and

estimated torques related to the bucket, while

Figure 4 shows a comparison of stick torques.

By analyzing the residual vector, the difference

between measured and predicted torques were

computed. The mean square error and

percentage error are given in Table 3.

torque Mean square Percentage error

error 43.12 Nm 26.7 %

Xi 73.54 Nm 18 %

Table 3: Mean Square and percentage eerors of

stick torques.

BUCKET

Figura 3 Comparison between measured (full line)

and estimated (dashed) torques of bucket

435
STICK

0 5 10 15 20 2 5 30 35 40

Figura 4 Comparison between measured (full line)

and estimated (dashed) torques of stick

As we can note, the torque of the bucket

shows a larger error with respect to the stick

torque. This is probably caused by many

factors: the bucket motion needs only small

forces and low pressures, so the influence of the

joint and rod seal frictions will have more

uncertain values and the variation is therefore

higher; second, the angular position is measured

indirectly. Also, the full scale range of the

pressure sensors utilized was high in comparison to the pressures needed to actuate

the bucket.

4. Conclusions

This work purses two fundamental

objectives: first to develop an economical force sensor for contruction machinery; and second,

to develop a method to measure the masses, moments of inertia, and friction of parts, when

it is not easy to compute these parameters, or to validate models by running mechanical

dynamic simulation software.

To achieve these objectives, a small

excavator, powered by electric motor and

controlled by servo valves, was equiped with a

suitable sensor suite. For machine dynamics, a

filtered regression approach was studied. In these fu-st tests we can see that the

parameters indentified in dynamic conditions

and considering cylinder friction are more

accurate with respect to static conditions.

We can note that the estimated torques

follow the trend of measured torques, but it is

evident that the errors on the torque related to the bucket are large with respect to the error of

stick torque.

We were unable during the course of the

research to find the reasons for these

discrepancies. These parameter values depend

on a number of things, from selecting the

appropriate pressure sensor range to software

routines, hydraulic system configuration, and

signal processing techniques.

This complexity requires an accurate

calibration of all these factors, and that takes

time. The initial results suggest that with

further work this technique can be made to work, thus providing an economical sensor approach for control of machinery.

REFERENCES

[1] F. Malaguti, "Development of On-board

Weighting and Force Sensor System for

Construction Machines: Static Analysis",

Proceedings of 14"" ISARC, Pittsburgh,

USA, June 8-11, 1997.

[2] F. Malaguti, "Force Sensor for Construction Machines by They Driving

Hydraulic Cylinders", Proceedings of 17"^ ISARC, Taipei, Taiwan, 18-20 September,

2000.

[3] A.I. Koivo, "Fundamentals for Control of

Robotic Manipulators", J. Wiley & Sons.,

1989

[4] F.L. Lewis, C.T. Abdallah, D.M. Dawson,

"Control of Robot Manipulators"

Macmillan, New York, 1993.

[5] S. Tafazoli, P.D. Lawrence, S.E. Salcudean, D. Chan, S. Bachmann, C:W.

De silva, "Parameter Estimation and

Actuator Friction Analysis for Mini

Excavator"

[6] S. Tafazoli, P.D. Lawrence, S.E. Salcudean

"Identification of Inertial and Friction

Parameters for Excavator Arm", IEEE

Trans, on Robotics and Automation, vol.

15, no. 5, October 1999.

436
INTELLIGENT DRIVING CONTROL SYSTEM

-Automated Driving Management and Control System Using Optimum Control TheoryTeruhisa AWATA (awata@ansl.ntt.co.jp)

Koichi YOSHIDA (yoshida@ansl.ntt.co.jp)

Hidenori HINO (hino@ansl.ntt.co.jp)

NIPPON TELEGRAPH AND TELEPHONE CORPORATION

Access Network Service Systems Laboratories

1-7-1 Hanabatake, Tsukuba-city, Ibaraki, 305-0805, JAPAN

Abstract: To realize the all NO-DIG (trenchless method) operation of conduit installation,

NTT developed the microtunneling method "ACEMOLE" allowing long-distance and

curved installations and promoted use of this method. NO-DIG method is not widespread in construction works because its construction cost is not economically compared with opencut method. We developed new ACEMOLE to solve these problems drastically and reaUze NO-DIG entirely. Especially position-detection system using fiber-optic gyroscope and

inteUigent driving control system using optimum control theory make possible to control microtunneUng machines accurately without operators skills and to disseminate NO-DIG

technology smoothly.

Keywords: NO-DIG(trenchless method), microtunneling robot, fiber optic gyroscope,

directional control, Kalman filter

1 Introduction

NTT has independently developed and

promoted the microtunneling robot

'ACEMOLE' as a technology for laying

electronic communications conduits. The

application of the ACEMOLE has expanded to take in other pipe and conduit-laying

operations, such as water and sewage pipes

and electric power cables. This technology has

now laid 677 km of conduit, but costs are high, numerous technological problems have been

encountered and the level of NO-DIG

operations have reached their limit. Cost

reduction is the major prerequisite for increasing the application of this NO-DIG

method. Another important agenda is the

improvement of microtunneling machine

position detection and control technology, to enable flexible response to varying road

shapes, operation in areas with a high

concentration of underground facilities and

high-accuracy long-distance and curved route

driving. Accurate control of the

microtunneling machine requires a system

which accurately monitors the position and

posture of the machine, predicts changes in driving status and machine behavior with

changes in external conditions, and determines

control guidelines on the basis of an overall

judgment of status. However, depending on the

form of the route being driven and the driving

distance, there are certain restrictions on

present position detection technologies.

Problems may occur with the accuracy and

continuity of measurements, or measurements

may not be able to be taken in real time. In

addition, human error on the part of the

operator or the application of control with an

inaccurate understanding of changes in external conditions can cause trouble, and this trouble can spread without being corrected. It

is necessary to prevent or reduce the occurrence of trouble originating in human

error and external factors to achieve the

smooth spread of NO-DIG method.

NTT has therefore developed continuous highprecision position detection system to enable

real time position detection without restrictions over the entire driving course and driving

distance using optic fiber gyroscopes. In addition, to further prevent the occurrence of

437
trouble and enable higher-accuracy execution, an Auto-navigation system has also been

developed. The introduction of these

technologies enables inexperienced operators

to control the microtunneling machine at the same level as experienced operators, prevents

the occurrence of various types of trouble

which have occurred in execution up to the

present, and has improved the accuracy and

efficiency of driving operations. This paper

will give an outline of the overall makeup of

the ACEMOLE system, and will then discuss

the high-precision continuous position

detection system. After this, the makeup and

component technologies of the Autonavigation system will be discussed. The paper

will conclude with a discussion of the results of test operations.

2 Auto-navigation System

2.1 Outline of ACEMOLE System

Fig. 1 shows the entire system configuration of

the microtunneling ACEMOLE robot

controlled by the system described in this paper. The ACEMOLE system shown here uses dynamic press-insertion, in which

vibration of the front of the microtunneling

machine liquefies the surrounding soil face to reduce face resistance and the machine

advances under thrust provided by jacking

machine. This system lays pipes of a fixed

length in succession. The machine's driving

direction is controlled by an inbuilt hydraulic

jack, which moves the front of the machine

head up and down and left and right.

Vibration Cqnlrpl Control

lieod joint jock

Joint

Conduit

Front Hilli Jacking Modiine

Figure IrSchematic of a microtunneling robot

2.2 Position Detection System

Fig. 2 shows the horizontal and vertical

position detection systems. Up to the present,

horizontal position detection has relied on a

laser target system: a laser beam produced by a

laser theodolite is detected by a light-sensitive

target in the microtunneling machine, and the

displacement of that beam from the base line (laser beam) is determined. An

Electromagnetic method is also used, in which

receivers above ground detect a magnetic field induced by a transmission coil built into the

microtunneling machine, enabling the

machine's absolute position to be determined.

However, the laser targeting method can only

be used over straight sections, and the

magnetic method used on curved routes

requires the operator to stop driving in order to take above ground measurements, resulting in discontinuous position data. The magnetic

method also cannot be used near magnetic

bodies, under riverbeds, etc. An optic fiber

gyroscope system was developed to provide a

solution to these problems. Vertical position is detected using a Hydraulic pressure differential

method enabling relative depth to be detected

in real time, using the difference between a standard liquid pressure and the pressure

detected by a pressure sensor in the

microtunneling machine.

Electromagnetic agnetlC methodD methOdU

^ Hydraulic pressure

Receixxj; "^^-Hifferential methodD

Planned line pressure sensour

] Laser taget system

Laser theodolite

Transmission coil y / fcjjrt^E^P^^^'^" Laser beam

Drivinp machme 'lMifc**!!^^^''^Light-sensitive target

Optic fiber gyroscope Optic fiber gyroscope system

Figure 2:. Position detecting system

2.3 Outline of Optic Fiber Gyroscape

System

Optic fiber gyroscopes have a broad range of

application, but are chiefly utilized in the

inertial measurement of direction and posture

in space and the measurement and control of

rotation. These gyroscopes were utilized in a newly developed system for microtunneling

machine position detection as a means of

solving the problems delineated above. Optic

fiber gyroscopes continuously detect the

angular velocity of a moving body, relative

change in the angle can be found by

integrating the angular velocity, and therefore

the horizontal position of the machine can be

continuously calculated from the driving

distance using the starting point of driving as a

base. Horizontal position y is found using the

438
following equation, where Q. is angular

velocity and x is driving distance:

y{x)= j^^Qdtdx (1)

Below is a simple discussion of the Sagnac

effect (the principle of measurement with optic

fiber gyroscopes). We will consider the optic

system shown in Fig. 3. The beam of light

produced by the light source is split into left and right beams by a beam splitter. These

beams then enter circular optic fiber loops.

After being propagated through these loops,

the beams are reintegrated at the same beam

splitter. If the loops have remained still, the left and right beams will have traveled a path of

exactly the same distance, and the time

required for the beams to arrive at the beam

splitter will be the same. However, if the optic

fiber loops are rotated in one direction at angular velocity Q , then the distance traveled

by the two beams will differ, and there will be

a difference in propagation times. This time

differential is expressed as

where L is the length of the fiber, r is the radius

of the fiber, and c is the speed of light.

(2) The time differential At for propagation of the

left and right beams is proportional to the

angular velocity of the rotation of the optic

fiber loops, Q . Calculation of angular velocity

utilizes the fact that the propagation time

differential for the left and right optic fiber

loops At found in equation (2) becomes AO , the phase difference between the left and right

beams, as shown in equation (3). AO =(0At = {lKl ?i)cAt

(3)

parameter is also used as important machine

posture data in the Auto-navigation system

described in the next section.

Right beam

Light source

Here, (D is the angular frequency of the light source.

Beam splitter

Figure 3:. Principle of Sagnac effect

2.4 Outline of Auto-navigation System

The Auto-navigation system detects the

machine's position and posture, predicts

behavior and provides control. Fig. 4 shows an image from the Auto-navigation system

screen. The screen shows 0 m for both

horizontal and vertical position. On the left (the negative side), we see data detected to present and values predicted on the basis of the machine behavior model (to be discussed in the next section). On the right (the positive

side), we see the optimum value of correction

of machine direction to be applied based on model parameters estimated to present, and

results of a simulation of machine

displacement in response to this correction.

Accurate detection of microtunneling machine

position and posture are essential for

directional control of the ACEMOLE. This is an important element in the application of

control and has an effect on driving accuracy. The optic fiber gyroscope system described in Section 2.3 is able to gather high-precision

position data in real time; conditions in the

machine behavior model can therefore be

accurately estimated online, and the optimal

value of control can be determined by

feedback of these conditions, enabling highaccuracy directional control.

Utilizing equation (3) to find phase difference

Ad enables the rotational angular velocity Q.

of the fiber optic loop to be determined. In addition to the use of angular velocity Q.

when calculating horizontal position, this

439
Controlled value

Ointrol value hv the svs'.em

'

Estimated value by the system

' Measured value

Figure 4:. Screen shot

2.5 Machine Behavior Model

Because horizontal and vertical motion is independent and mutual interference does not

occur, models of each direction have been

designed. Because the characteristics of the

machine's motion in the horizontal and vertical

directions can be expressed in identical

behavior models, this model will be explained

using Fig. 5, which defines machine position

and posture in relation to the microtunneling

machine base line. Changes in machine posture (A^) are defined

by the Unear sum of noise components which

are unrelated to past head angle (including

current head angle) and directional control. This can be expressed as follows:

nb-l e[k+i]=0[k]+Y, b. v{k+\- i\+ oik] (4)

/=o

Here, k is the positive increase in unit driving

length Lp for each length driven, ;/[/: + 1 — /] is Lp*i(m), value of past directional control

conducted before the present, is the

weighting factor for value of directional

control, and (O represents noise components.

If the angle of the rear of the microtunneling

machine as measured against the base line is taken as following the angle of the front of the

microtunneling machine at Lf{m) only, it can be expressed as the following:

e\k]=d[k-nd] (5)

where nd is Lf/Lp rounded to a whole number.

The change in displacement Xh of the section

of the microtunneling machine receiving

directional control for each driving length can

be expressed

X,[k + l]=X,[k]+Le[k] (6)

Until now, it has been impossible to directly

detect 6 in the horizontal direction and it has

been necessary to use a kalman filter adapted

to the machine posture model given as equation (4) and the position and posture

detection method being used to estimate Xh

and b- from equation (4). However, because

the optic fiber gyroscope system has enabled

direct detection, it has now become possible to construct a more accurate model.

Joint angle

Planned Urn

Joint position Control joint position Head position Figure 5:. Coordinate system for the driving

macliine

2.6 Optimum Feedback Control

We will now consider directional control

conducted using the equations described

above. Equations (4), (5) and (6) are used to newly define the posture vector X.

e[k]

d[k-\]

d[k'-nd\

rj[k -nb + ]\

nb in equation (7) is an integer greater than 2. Next, a feedback gain K which satisfies equation (8) is sought.

X[k] = (7)

77(^^ + 1]= jik]-KX[k] (8) K is designed on the basis of the principle of

harmonizing speed of convergence with value

of correction. This has made it possible to closely control the progress of the

microtunneling machine underground, and to rapidly correct deviations from the base line.

440
2.7 Auto-navigation System Flow

Fig. 6 shows the composition of the Autonavigation system. The utilization of a model

of microtunneling machine behavior (Fm)

which expresses the value of directional

control rj (k) and the motion characteristics of

the microtunneUng machine in response to changes in position and posture mean that current machine status can be estimated online.

Feedback of these estimates enables the

optimal directional correction controller (K) to calculate the value of correction T] (k+1) to be

apphed next. This online estimation enables

the appropriate value of control to be exerted

to maintain the microtunneling machine head on the planned line in response to current

position and posture, surrounding soil quality,

etc., and future machine status to be predicted.

Figure 6:. Composition of Auto-navigation system

3 Test Results

To verify the effectiveness of the system,

proving trials were conducted using an actual

machine. The machine was placed in a homogeneous stratum of 3 m in width and 40

m in length, and driving commenced from a depth of 2 m. Figs. 7 and 8 show actually

measured values and values estimated by the

system for horizontal and vertical directions

respectively. The horizontal axes show data

sampled at Lp = 10 cm.

Values predicted by the system are compared

with values measured in the horizontal

direction using the magnetic method (capable

of measuring absolute position in this direction) and in the vertical direction by the

liquid pressure differential method. The results of directional control conducted on the basis of

optimum values calculated by the system

showed less than ± 30mm difference between

values predicted by the system and actually

measured values, proving the effectiveness of

the model and the algorithm.

Figure 7:. Values estimated by the system and

measured values by electromagnetic method

3 4 1 MeV 7 8 , ¥n(nudl

Figure 8: Values estimated by the system and

measured values by Hydraulic differential

4 Conclusions

A high-accuracy Auto-navigation system has

been developed for conduit inicrotunneling

machines using the dynamic press-insertion

method. The system utilizes a machine

behavior model which displays motion

characteristics in response to correction of

microtunneling machine direction. This has

enabled optimal feedback control based on the

model and estimates of position and posture of

the microtunneling machine, both of which are

difficult to directly monitor. Use of an optic

fiber gyroscope for horizontal position and

posture detection has enabled estimates of

machine status to be made at a higher level of

accuracy. The introduction of this system has

increased the efficiency of execution

management and optimized driving control,

leading to the following benefits:

(1) Homogeneous and high-accuracy execution

is possible irrespective of the level of

experience and skill of the operator.

(2) Rapid and accurate driving control has

increased the level of driving efficiency

achieved to date.

(3) The problem of shortage of skilled

operators has been solved, and the period

441
and costs required to train operators have

been reduced.

(4) These results will aid in the diffusion of

NO-DIG method.

The results reported in this paper have

demonstrated the effectiveness of the newly

developed technology. To increase the spread

of NO-DIG method in the future, it will be

essential to continue to improve the technology

in this way. These technologies have been

developed for the ACEMOLE system, but the

broad applicability and potential for future

development of the system mean that we can

expect that it will be possible to construct

similar systems reflecting machine

characteristics for other driving methods.

5 REFFERENCES

(1) Ayukawa, M. Inoue, K., Miyatake, M., and

Tujimura, T., "The Future ACEMOLE

Realizes All No-Dig Operations with Conduit

Installation," NTT Review Vol. 13, No. 5, pp

69-77, 2001.

(2) Manabe, T., Sato, M., Awata, T., and

Matsumoto, M., "Automatic Direction Control

Technique for Press-in Type Small Diameter

Tunneling Machine, " ISTT International

Conference on No-Dig '98," pp. 83-92, 1998.

(3) Awata, T., "Intelligent Driving Control

System," No-Dig International, Vol. 12, No. 4,

pp 25-26, 2001.

(4) Maybeck, P., "Stochastic Models,

Estimation and Control," New York

Academic, 1982, Vol. 1.
AUTOMATIC STEERING SYSTEM FOR ROTARY SNOW REMOVERS

Hirofumi HIRASHITA, Takeshi ARAI, Tadashi YOSHIDA

Advanced Technology Research Team, Public Works Research Institute 1-6,Mlnamlhara, Tsukuba City, Ibarakl-Pref, Japan, 305-8516

Tel:+81 -298-79-6757 Fax:+81-298-79-6732

E-mall:hlraslta@pwrl. go.jp, arai0333@pwrl.go.jp, yoshlda@pwrl.go.jp

ABSTRACT: In cold and snowy parts of Japan, most snow is removed from roads by

mechanical snow removers, and to deal with roadside conditions and guarantee safe operation, these machines are normally operated by two people; an operator and an

assistant. Work is in progress to develop automatic steering systems for snow removers in order to lighten the burden on snow remover operating staff and to reduce future labor requirements. This report describes an automatic steering system that incorporates three technologies; the lane marker system that has been developed in recent years as an ITS technology, RTKGPS technology, and GIS technology. This steering system has been developed for rotary snow removers; the type of snow remover considered to be the most difficult to operate. The report also evaluates the three control methods based on the results of corroborative

testing done using actual snow removers and outlines problems with these control systems

that must be overcome to establish a working system. KEYWORDS: Rotary snow remover, automatic steering, ITS, lane marker, GIS, GPS

1. INTRODUCTION

In cold snowy parts of Japan, snow is removed

from roads by mechanical means to guarantee

smooth winter road traffic. To guarantee that mechanical snow removal is performed

appropriately according to the state of snow

accumulation on road surfaces, a carefully

planned attendance control method must be

established and the machinery must be

operated correctly.

The automatic steering system that has been

developed is intended for use on rotary snow

removers: a type with an operating method more complex than that of other types of snow

removers. It has been developed to reduce the burden on snow remover operators and to lower future labor requirements.

2. BACKGROUND TO THE

DEVELOPMENT

A rotary snow remover is operated by two

people: an operator who drives the remover

and an assistant who controls the ejection of

the snow. The operator drives the machine

along the curb on the shoulder of the road

443

while watching out for manholes or other level differences on its surface. The assistant ejects the snow while avoiding private property,

homes, and other areas where snow disposal is forbidden (Photo 1).

The goal is to automate part of the vehicle operating work now performed by the operators to allow them to control the snow

ejection now done by the assistants, permitting

the introduction of one-man operation in the

future.

This report introduces positioning technology

and control technology that form the foundation of the automatic steering system

that has been developed, and presents an

evaluation of the system based on the results of

corroborative

testing

performed with an actual snow

remover and

describes problems to be overcome to complete a working system.

Photograph 1 . Inside of

a Rotary Snow Remover
3. AUTOMATIC STEERING SYSTEM

The automatic steering system that has been

developed automates the rotary snow remover

steering operation that is one of the tasks of the

operator.

3.1 Steering control of a rotary snow

remover

The steering mechanism of a rotary snow

remover differs from normal vehicles in that the front and back parts are linked by pins and

articulating mechanisms are installed so that the vehicle can bend at the pins. The steering is controlled by the exact linearization method

and by time scale transformation that are

effective ways to control the course of a moving vehicle This control method is represented by an equation of motion subject

to non-holonomic constraint and is based on

non-linear control theory. But a snow remover

slides laterally, because as it removes snow, it

is subjected to lateral reaction force from the snow embankment

as shown by

Photograph 2. Sideways sliding is controlled by using

the integrated servo system described

below to treat this sliding as an

external distur- bance.

Photograph 2. Rotary Snow

Remover Removing Snow

( 1 ) Course tracking control Fig. 1 shows a model of the snow remover

steering mechanism. In this figure, the distances from the connecting pin of the snow

remover to the front wheels and to the rear wheels are represented by L. When the

steering angle is represented by 2 a , the course followed by the snow remover is an arc with

radius R = L/tan a . When the course tangent

direction speed vector at the center point P of

the front wheels is represented by V and the tangent direction angle by 9 , the equation of

motion of the point P can be written as follows.

X = vcosd y = vsin^

e = ^ = v R

Y

Figure 1 . Coordinate System

(Model of a Snow Remover)

If exact linearization and time scale transformation are done for equation (1) to perform status feedback control, the quantity

of steering of the snow remover that is 1/2 of

the steering angle a is defined by the following equation.

a = tan"' \f^y + fj tan 6)1 cos^ e\ (2)

In equation (2), lateral sliding is not considered.

In order to eliminate the steady-state deviation

caused by lateral sliding, if the integrated servo system is used, the quantity of steering a is represented by the following equation.

a = tan ' Icos^ 0|f3 ^(y -^ref Vcos6tlt + fjy + f2 tan^j

(3)

The symbol f is the control gain, and based on

equation (3), fi represents proportional gain, fj represents derivative gain, and fs represents

integral gain. PID control was used to construct the system.

Snow

remover

Lear*

fj

1

s

tana

(1) Figure 2. Integrated Servo System Control Block

Diagram

444
3.2 Positioning method

It is necessary to detect a vehicle's present

position and to have information that determines the direction to steer it in order to perform automatic steering.

The system that has been developed is equipped with two functions: the guidance

method that use lane marker sensors to detect

the vehicle's position and the steering method

that uses GPS and GIS to detect the vehicle's

position.

3.3 Lane marker sensor guidance method

A lane marker sensor is a basic technology of

the Advanced Cruise-Assist Highway System

(AHS) developed for use as part of the

Intelligent Transportation System (ITS). This

technology includes lane markers buried at intervals under a road surface and vehicle mounted sensors that detect signals transmitted by these lane markers to guide the vehicle

along the course formed by the markers. There

are two versions of this system: the radio wave

method and the magnetic method.

(1) Steering angle calculation logic

It is assumed that the distance between the lane markers will not be constant, but can be varied

according to the shape of the road and

demands of the sensor side. Therefore, this system is equipped with two rows of sensors

so that control can be performed even when

the lane marker installation interval is not known until the rotary snow remover passes over them (Fig. 3).

ITaiget couse I Taiget couise

Buhed maiker

Front part of the sixjw rennvCT

Front whed tires

Value prevouslydetected hy

the No 1 sensor

<ti.=-Bn-'\ (y.,-y.„)/2.0l ili„=-tKf'{ (y.,-Vrf)/IJnl y.=— ly.,—Lb" (y.|-y.u.)/2i)l X(x>s;(i. y„=— ly„|—Lox (y„-y^)Ajn| "-txa^l^

Loi-ljOW Lm:134[nO,LD:-10[iTil

To control steering

with a single row of

sensors (Fig. 3 on

the left), the lateral differential and the azimuthal

differential yn 0 m that necessary for control by the target courseand

are Photograph 3. Radio Wave Marker

coordinate system X(xy) require information

about the interval between the markers in addition to the sensor signal ymi that is measured by the front vehicle fixed coordinate

system 21f(xfyf). But with two rows of sensors

(Fig. 3 on the right), the system can calculate

the lateral differential and the azimuthal

differential yTM and 0 m of the target course

coordinate system X(xy) by having two

opposed sensors hold the two sensor signals

ymi and y„a measured by the front vehicle

fixed coordinate system 2]f(Xfyf) as it passed a marker until they pass the next marker, so that steering control can be performed even if the

interval between markers was unknown.

(2) Radio wave marker sensor positioning

method

With the radio wave method, an antenna inside the sensor on the vehicle transmits a 227.5 kHs

radio wave towards the road and when a radio wave marker (Photo 3) receives this transmission,

it returns a signal of double frequency of 455

kHz. A receiving antenna inside the sensor

receives this retum radio wave to detect the

vehicle's position (Fig. 6).

The system detects the locations of the markers

in the traveling direction by passing through

the peak value. It detects the position in the

lateral direction by calculating the distance between the antennas by the triangulation

method

based on the difference in the received

strength of

the return radio waves

sensed by

the two

receiving antennas

Photograph 4. Radio Wave Marker

Sensor

2)

Figure 3. Lane Marker Sensor Guidance Method

445
Photograph 5. Magnetic Marker

(3) Magnetic marker sensor positioning

method

With the magnetic

method, magnetic

markers

permanent ferrite magnets (Photo

5)—under the road

surface produce

magnetic fields and

a magnetic sensor

that detects magnetic field density installed on

the vehicle determines the position of the vehicle based on the strength of each magnetic

field.

The magnetic field distribution of the magnetic

marker shows the unimodality that treats the center of the marker as the maximum magnetic

field strength. The magnetic flux densities of

the vertical component (Bz) and the vehicle

width direction component (Bx) of this magnetic field are detected by the magnetic

sensor and the location of the marker is detected by calculating the distance between

the sensor and the marker based on the previously stipulated Bx/Bz relational equation

(Fig.4)^>.

J » -250 -200 -150 60 100 150 200 260 3 0

Lateral location

Figure 4. Bx/Bz Relationship

3.4 GPS/GIS position detection method

A system based on GPS/GIS positioning

detects the position of the vehicle to control its operation by comparing rotary snow remover

position coordinate data received fi-om a GPS

satelUte with position coordinates of linear data for the road provided in advance by road

GIS.

Figure 5. Road GIS Data

(1) Road GIS

Road GIS is a data base of

information

concerning

structures and

trafGc management

used for road

maintenance. To develop this system, rotary snow remover target course information was

created so that it can be handled as GIS data.

Operators of rotary snow removers remove snow to widen the bare road by driving their vehicles guided by the snow removal edge (Fig.

5) Because the snow removal edge is ofl;en the curb of the sidewalk along the sides of the road, the GIS data that was used is curb data.

(2) RTK-GPS

RTK-GPS, a system capable of high-precision

positioning (error radius between 2 and 3 cm),

consists of two GPS receiving antennae, one a

fixed station and one a mobile station (on the snow remover). The fixed station transmits

correction information based on GPS data it has received to the mobile station.

The system can perform almost real time

positioning, because the GPS data is corrected atarateof20Hz.

4. CORROBORATIVE TESTING

Corroborative testing planned to simulate snow

removal on a real road was carried out using a

rotary snow remover equipped with the

steering control system in Hokkaido in January

and February 2002.

The corroborative testing was performed in order

to evaluate the apphcabiUty and practicality of

each automatic steering method under the behavior characteristic of a snow remover on an

actual road (low speed, lateral sUding).

4.1 Outline of the corroborative testing

( 1

) The rotary snow remover The body of the rotary snow remover was the medium size model (2.2 m wide) used most

fi-equently on national highways, and the body

constructed according to normal specifications was partially modified (Fig. 6).

446

I
Fig. 6 Rotary Snow Remover Equipped with an Automatic Steering Support Function

(2) Corroborative test cotirse The corroborative test course consisted of

straight sections, curves, (R 30 m), and

intersections (R 12 ra) so that it reproduced

conditions on national highways. Its lane marker intervals were 2.0 m and 1.5 m.

The rotary snow remover work conditions were

identical to those of actual work, with the work

done at two speeds, 4 km/h and 0.5 km/h '^K Snow

banks were prepared to provide the work load and

lateral sUding that occur when a remover is used

to widen the cleared part of a road.

Figure 7. Layout of the Test Course

4.2 Results of the corroborative testing

The testing corroborated the lane marker

sensing (radio wave and magnetic) guidance

methods and the GPS/GIS positioning method.

Because the steering control system developed

is a system that follows a preset target course,

its control performance was evaluated as the quantity of deviation of the snow remover from its target course (quantity of lateral deviation). Table 1 shows the quantities of

lateral deviation from the test results organized

by method.

Table 1 . Lateral Discrepancy for Each System

(Example)

Stand-alone operation (working speed 4 km/h, quaility of deviation of front sensor) Unitm

Road alignment

Straight

section

Curve

to the

left

Curve

to the

right

Straight

section

Inter- section

Radio wave type

Max. value 0.25 0.41 0.28 0.39 0.76 Min. value -0.23( - .49( - .38 0.02 0.26 Average value -0.05 0.06 -0.13 0.16 0.51 Standard

differential

0.12 0.23 0.19 0.12 0.16

Magnetic

type

Max. value 0.06 0.35 0.37 0.42 0.91 Min. value -0.1 8( - .371 - .53 0.11 0.29 Average value -0.04 0.08 -0.25 0.27 0.61 Standard

difTerential

0.06 0.21 0.24 0.10 0.22

GPS

s

Max. value 0.04 0.04 0.25 0.24 0.17 Min. value -0.03( - .321 - .26 0.00 -0.24 Average value 0.00 -0.08( - .04 0.07 -0.02

tandard

difTerential

0.02 0.11 0.10 0.08 0.09

This table shows that overall, the quantity of

deviation and the standard deviation were both

small on the straight sections, but both were

higher on curves and at intersections. This

difference is presumably a result of the fact

that in sections with a small radius of curvature, a larger quantity of steering is performed and

the snow removal load is more likely to cause

lateral sliding.

By method, the GPS/GIS method is superior to the lane marker method. Because the former

method achieves almost real time positioning

and steering control of almost 20Hz, it can

respond instantly to lateral sliding to reduce

the quantity of deviation. With the latter, steering is delayed because the system cannot

detect lateral sliding where there are no signals

between lane markers, resulting in a large

quantity of lateral deviation. Therefore, testing was done by, in addition to correcting lateral sliding with the sensor, providing the coordinates of the next marker (course

information) as the sensors passed the markers.

The resulting lateral sliding distribution reveals

that as shovm in Fig. 8, ±2 a ( a : standard

differential) at this time was ± 57 cm without

course information, and it was ± 31 cm with

course information: a big improvement that brings its precision extremely close to that of

the GPS/GIS method.

No gap in performance between the speeds 4

km/h and 0.5/h was observed.

447
60.0

50.0

40.0

30.0

20.0

10.0

0.0

I % [ MM QuandtyoflatCTa] deviation: with course information

-80 -70 -60 -50 -40 -30 -20 -10 10 20 X 40 50 60 70 BO

SI'"

Quantity of lateral deviation: without

course information

I

-80 -70 -60 -50 -40 -30 -20 -10 10 20 30 40 50 60 70 80

Figure 8. Lateral Deviation With and Without

Course Information (Radio Wave Method)

5. CONCLUSIONS AND FUTURE

CHALLENGES

It has been confirmed that automatic steering

systems using lane markers or GPS, GIS, etc. can achieve a generally practical level of

control of normal snow removal work by

rotary snow removers. But in order to establish

practical working systems, the following

challenges must be resolved.

(1) Testing of the GPS/GIS method showed

that its detection precision temporarily fell even in open spaces. It is assumed that this happened when the GPS sateUites were

concentrated in a narrow range. And during

testing of the radio wave marker method,

unpredictable behavior thought to be an effect of the high output transmitter on the vehicle was observed. It is necessary to provide a

function that automatically stops operation

without the intervention of the operator when

such abnormal operating signals are produced.

(2) And as in the GPS/GIS case, it is necessary

to improve the precision of control by the lane marker method by entering the lane marker

coordinates to the snow remover system in advance to provide it with course information.

It is also essential to record passage over each

marker each time the system passes over the markers.

(3) And to further improve control precision

(reduce the quantity of deviation), it is 'necessary to strive to quantify disturbance such

as lateral sliding and the snow removal load

etc. of the snow remover and to perform

simulations after increasing the degree of

detail of the model of snow removal work by a

rotary snow remover.

6. CONCLUSION

.In recent years, various organizations have

attempted to apply information technology (IT)

to improve construction machinery. As seen in those cases, the information handled in this case cannot be applied to other systems unless

its use is premised on standardization. Because

the rotary snow remover developed by this project requires new road infrastructure such

as lane markers, road GIS data, and

communication systems and its communication standards must be standardized,

its development has been harmonized with

communication technologies in the ITS field. The authors hope that this research and

development will contribute to introducing it as a working system.

In conclusion, the authors wish to express their deep gratitude to the Hokuriku Regional

Development Bureau and the Hokkaido

Regional Development Bureau of the Ministry

of Land, Infrastructure, and Transport whose

members helped with the corroborative testing

and to everyone who helped with the

fabrication of the system and the testing work.

REFERENCES

1) Sanpei M. Ito T.: Path planning and path

tracking control of wheeled vehicles using

nonlinear system theory—parking control using forward and backward movement.

Collected Reports of the Institute of Systems,

Control, and Information Engineers, Vol. 6, No. l,pp. 37 to 47, 1993

2) Handa S., Nakazuka A., Tanji Y.: Lane

marker system, Matsushita Technical Journal, pp. 45-49, October 2001

3) H. Suzuki: Development of Lane Marker

System in AHSRA, 6* World Congress on

Intelligent Transport Systems, November 1999.

4) Fourth edition of the Road Snow Removal

Handbook: edited by the Japan Constniction

Mechanization Association, pp. 131

448
ADAPTIVE CONTROL OF A CONSTRUCTION MANIPULATOR

by

V. Gradetsky \ M. Rachkov ^ M. Pushkin "

" Institute for Problems in Mechanics, Russian Academy ofSciences, Vernadsky ave. 101

Moscow 117526, Russia, Phone: -v?-095-4344149, gradet@ipmnet.ru

^Moscow State Industrial University, ul. Avtozavodskaya 16, Moscow, 109280, Russia,

Phone: +7-095-3684883, rachk-v@mail.msiu.ru

ABSTRACTI The paper describes an advanced control technique that uses a self-adjusting

controller. The technique allows changing control parameters of the manipulator according

to different technological forces and disturbances acting to the end-effector of the manipulator while performing surface treatment construction operations such as cleaning

and polishing. The system is asymptotically stable for the phase error and can be

implemented on a base of existed industrial robots. KEYWORDS: adaptive control; construction manipulator, parametrical error; reference model; self-adjusting controller.

1. INTRODUCTION

Automation of some surface U^eatment

construction operations such as cleaning and

polishing by means of manipulators demands

adaptive control that allows keeping required

technological forces of a tool at any disturbances

from surface unevenness.

There is a program that allow for efficient management of relevant operational parameters

related to surface finish quality [1]. This program

is intended for on-board computers in graders or

pavers.

One of approaches in manipulator control is based on a calculation method by incomplete

information about external parameters [2]. However, the known algorithm of control is characterized by complexity of calculadons and

is usually used for manipulators with two or three

degrees of freedom.

Optimal positioning of a pneumatic manipulator

with minimum control energy consumption is solved in [3]. This system can place a tool with

high accuracy taking into account information

about current position of the manipulator but some disturbances can act to the tool from treated

surface unevenness while operating.

The proposed technique solves a task of

qualitative control of the manipulator tool with a reference model where a wide range of possible

dynamic properties can be changed. The

technique allows changing control parameters of

the manipulator according to different

technological forces and disturbances acting to the end-effector of the manipulator while

performing surface treatment construction

operations such as cleaning and polishing by means of a self-adjusting manipulator controller.

2. SYSTEM WITH A REFERENCE MODEL

Let's consider the approach based on the self- adjusting system with a reference model on the

basis of information about object parameters

that is received while funcdoning. The active

change of regulator parameters should be

carried out on a base of this information.

449
The self-adjusting system with the reference

model can be described by the block diagram

presented in Figure 1

.

The system motion is described by the linear n- order differential equation with constant beforehand-unknown factors, which can vary in a wide range scale

A =

(4)

0 1 0 ... 0

0 0 0 ... 1

/"\t) + Y,[a.+Aa.+Sa.(t)U"-'\t) =

i=l = fit),

(1)

where Aa- - constant beforehand-unknown

factors, S a- (t) - factors, generated by the self- adjusting circuit.

The reference model is described by the

equation:

AA - real constant matrix with beforehandunknown factors depending on the control

object, SA{t,x,y) - matrix of parameters

changed by the self-adjustment circuit. The

matrixes AA and S A can be expressed as

AA

0 ... 0

0 ... 0

(2)

where y(t) - output signal of the reference

model, fit) - control signal. It is supposed that the reference model is asymptotically steady.

The purpose the system with the reference

model is to design such a self-adjustment

circuit, at which xit)^ y{t), t^<^ by

generated Sa-{t). The equations of the object

and the reference model in the matrix form are

(5)

SA(t,x,y)

0 ... 0

0 ... 0

Sa,... 8a.

The control vector is f^ it) = (0,...,0, /„(?)),

where the top index hereinafter means a transpose operation. For an error vector £ (t) = xit) - y{t) , subtracting equations (3)

from (2), we have

x(t) = Ax(t) + [AA + S A{t,x,y)]x{t)+

+ fit), x{t^) = x^,

(2)

y(t)=Mt)+fit), yito) = yo, (3)

where x(t), y{t)e R" - phase coordinate

vectors of the object and the reference model,

A - a real constant matrix (Gurvitz matrix) that can be written as

£it) = A£it) + [AA + S A{t,x,y)]xit),

£it,) = £o

(6)

or in more convenient form

450
£(t) = Ae(t) + X(t)a{t,x,t),

(7)

where Xit) - matrix, at which the last row

coincides with the vector (t) , and

CC (t, X, y) - vector of a parametrical error

a^(t,x,y) =

= {Aa^+S a, (t, X, y),..., A<3„ +Sa^ (t, x, y))

The Lyapunov's second theorem is used for a

synthesis of the self-adjustment circuit. Let's choose Lyapunov's function as the square-law

form

V(t,£,a)=£^ re +a^a,

(8)

where the positively certain matrix F satisfies to the matrix equation

A^r + rA=-CE.

The equation of the self-adjustment circuit is

a{t)=eit,£,x,y).

A derivative of the V function by this equation

should be not positive, i.e. —dV

<0.

dt

The derivative of the function (8) by system (7)

is equal

V =-C\£\' +a''x''r£ +£^rXa +

+d^a +a^d =-C|£-| "<0

(9)

if the self-adjustment circuit is described by the

following equation

d(t)=-x^{t)r£(t). (10)

The algorithm (10) covers the majority of

known algorithms of adaptation. If vectors

x{t), yit), £(t) are measurable, the algorithm

(10) can be implemented. Thus, the system (7),

(10) is stable for £(t) and a{t)

3. DEnNITION OF THE SELFADJUSTMENT CIRCUIT VECTOR

In practice, there are objects, in which the

matrix of factors depends on some number of

parameters. Let the object is described by the

equation

x(t) = Aiq)x(t) + SZ(t) + f{t), xeR",

(11)

and the reference model is described by the

equation

y(t)=Mq')y(t)+f(t), yeR\

(12)

where qG R"' - the vector of parameters, from

which a matrix of object is depended, A(q^)-

Gurvitz matrix, 5Z{t)- vector generated by

the self-adjustment circuit. The task consists in definition of structure and algorithm of change

of the vector SZ{t) to have

£{t) = x(t) -y(t) -^0, t -^oo. The vector of a phase error £ (t) satisfies to the equation

451
£(t) = A{q')£ +[A{q)-A{q'')\x{t) +

+ SZ(t)

(13)

£(t) =A(^")£(0 + XA (0-^-^(0

/3,(t)=Aq.+Sq.{n.

(17)

Decomposing A(q) in a row, we have

A(^)-A(^'^) = X^^<^+H^^|)'

1^ oq.

q-q^=Aq, Aqe R'"

,

(14)

where values of derivatives in (13) are calculated for q = q^ .

Let's enter the vector dZ{t) , generated by the

self-adjustment circuit, as

The further synthesis of the self-adjustment

circuit uses Lyapunov's function. It can be

chosen as

V{t,£,j3) = £^r£ +

mY^pfit), r>o, r = r''

i=l (18)

where the matrix function /"generally looks

like r = rit,x,y).

A complete derivative of this function, taking

into account equations (17), is

SZ(t) = Y,Sq^(t)B^(t),

i=i

B,{t) =

(15)

dA{q)

dq. q=qoX(t)

Here S q- (?) - scalar functions that is determined below.

Taking into account expressions (14) and (15),

equation (13) is possible to write as

£ (t) = A(q°)£(t) +

+ y( A^, + ^ q. ) —x(t) + 0(\Aq\) x(t).

(16)

Let's assume, that the matrix A(q) depends on

the parameter q linearly. Then, last member in the equation (16) is absent and it will have a form

dV

dt = £ ^(A''iq'^)r+rA{q'^) + r)£ +

Y^/3,{t){Bfr£+£'rB,+2$,(t))

(19)

Since a matrix F is symmetrical, we have

BJ r£ =£^ FB-. Let's consider the following

algorithm of adjustment of parameters d q- (t)

(Sq,(t)) = 0,(t) = -B!F£=

dt

F£

/3,(0) = Aq,, Sq^(0) = 0

(20)

Let matrix F(t, x, y) satisfies to conditions

452
c,\p\- <p''^{t,x,y)<c^\p\-

pUA^ r + rA+ F) < -c^\p\\ .

(21)

in which A = A(q^), the matrix A(q) linearly

depends on parameters, A{q^)- Gurvitz

matrix. Then it is possible to show, that the

system (17), (20) is stable for eU) and /?, (r),

and also is asymptotically stable for the phase

error. If the matrix A{q) depends on

parameters not linearly, the system may be not

stable.

However, described self-adjustment circuit has

the following property. If the control signal is restricted, the phase error is also limited, and

the error can be so small as desired, if the

parametrical error between the object and the

reference model is small enough. It results from

general stability theorems.

4. CONCLUSIONS

The advanced control technique that uses the

self-adjusting controller is developed. The

technique allows changing control parameters

of the manipulator according to different

technological forces and disturbances acting to the end-effector of the manipulator while

performing surface treatment construction

operations such as cleaning and polishing.

The system is asymptotically stable for the

phase error in a linear case. In non-linear case, the phase error is also limited, and the error can be so small as desired, if the parametrical error between the object and the reference model is small enough.

The described control technique can be

implemented on a base of industrial robots RM01 or PUMA 560 that has six rotary joints and

can perform different construction operations

with complex trajectories of the tool.

5. REFERENCES

1. Skibniewski, M., Michalowski, S., Sobczyk, A.: "Predictive control systems in construction equipment", 18'*' ISARC

Proceedings, 2001, Krakow, Poland, pp. 277-282.

2. Fu, K.S., Gonsalez, R.C., Lee G.S.G.:

"Robotics: Control, Sensing, Vision and

Intelligence", McGraw-Hill Book Company,

New York, 1987, 624 p.

3. Rachkov, M., Marques, L., Almeida, A.T.: "Optimal Control of Pneumatic

Manipulators for Construction Application",

18"^ ISARC Proceedings, 2001, Krakow,

Poland, pp. 253-258.

y(t) Reference model

fit) Disturbances from a construction surface I

Manipulator

x(t)

453

JUST-IN-TIME CONTINUOUS FLIGHT AUGER PILES USING AN

INSTRUMENTED AUGER.

by

N. Mure\ J. N. Scott", D. W. Seward^ S. D. Quayle\ C. R. I. Clayton^

M. Rust^

ABSTRACT:

Continuous flight auger (CFA) piles are constructed by drilling a CFA auger into

the ground and, on reaching the required depth, pumping concrete down the hollow

stem as the auger is steadily withdrawn. Current practice to predict the bearing

capacity of CFA piles is to estimate the undrained shear strength-depth relationship

for the overall site, and use a total stress analysis to predict a general pile bearing

capacity. This analysis is often based on sparse site data collected from a location

remote from the pile. This paper investigates the exploitation of new technology to enable a new improved approach to the procurement, design and validation of

(CFA) bored piles. The ultimate target is that the final length of the piles will be

determined on site, as they are constructed, and will be optimised to suit the actual

local ground conditions.

KEYWORDS: data logging; instrumentation; pile foundations; process

optimisation.

1.0 INTRODUCTION:

CFA piles are formed by shearing the soil with

a continuous 'corkscrew' like auger, and then

replacing the soil with concrete as the auger is withdrawn in a controlled fashion. Finally

reinforcement is inserted. They offer a highly

efficient and cost-effective solution under

certain conditions, however there remains some variation in practice between piling

contractors, and in certain situations there is a need for improved confidence in final integrity

of the pile. Increased understanding of the data

collected on-board during the actual placing of

the pile could provide this increased

confidence and reduce risk, it would open the

way to a radical reform of the business

process, with significant changes to the

relationships between the bodies involved, and

the prospect of economic benefits to all parties

[1]. The ultimate target is that the final length

of the piles will be determined on site, as they

are constructed, and will be optimised to suit the actual local ground conditions.

2.0 CFA PILES:

At face value the installation of a CFA pile seems simple, a hollow stemmed auger is drilled into the soil and concrete is then

pumped into the ground through the stem as the auger is slowly withdrawn. However, the

action of drilling the pile is a complex one to

' Stent Foundations Limited, Birchwood Way, Cotes Park West, Somercotes, Derbyshire, DE55 4PY, U.K., Tel: +44 1256 763161, Email: norman.mure@stent.co.uk

- Stent Foundations Limited, Osbom Way, Hook, Ham.pshire, RG27 9HX, U.K., Tel: +44 1256 763161, Email:

Jason.Scott @ stent.co.uk

^ Engineering Department, Lancaster University, Lancaster, LAI 4YR, U.K., Tel: +44 1524 593010, Email:

d.seward@lancaster.ac.uk

* Engineering Department, Lancaster University, Lancaster, LAI 4YR, U.K., Tel: +44 1524 593095, Email:

s.quayle @lancaster.ac.uk

^ Department of Civil and Environmental Engineering, University of Southampton, Highfield, Southampton,

S017 IBJ, U.K., Tel: +44 23 8059 2841, Email: cric@soton.ac.uk

* Department of Civil and Environmental Engineering, University of Southampton, Highfield, Southampton,

son IBJ, U.K., Tel: +44 23 8059 3492, Email: m.rust@soton.ac.uk

455
model and understand. It is not always obvious

what affect the continuous flight auger has on

the ground.

With CFA, the process remains unseen and

there is no way of carrying out visual

inspections of the bore. We are therefore

forced to draw conclusions from past

experiences, as to the likely consequences of

installing certain piles in certain conditions.

The process of installing a CFA pile comprises

of three phases or parts. First there is the

boring of the pile, then concrete is pumped

into the system pre-charging the lines and

auger and finally the pile is concreted. The

nature of the rig, the ground conditions and the

augers all have an impact on each of these

phases.

2.1 Boring the Pile

As the auger is rotated into the ground material

from the auger tip is loaded onto the flights.

The auger is carrying out three distinct actions

- cutting, displacement and transportation of

soil.

Figure 1 demonstrates the auger being screwed

into the ground. As the auger moves downwards the surrounding soil has to be

displaced by the volume of the auger. This is typically 15-20% of the volume of the bore.

As the ground is excavated at the cutting head

it bulks and a ribbon of spoil moves up the

auger. Because of this bulking there is always

sufficient material available to fill the flights.

The full flights now support the bore, over the

length of the auger.

It would be ideal if CFA piles could be

completely installed in this way, with the auger

being continually screwed into the ground.

However, even the largest rigs do not have

sufficient power to overcome the frictional

forces that are generated by displacing the

auger volume into the surrounding soil.

Instead, it is necessary to restrain the auger

during the boring process. This allows some

soil to travel up the flights (transportation)

with no further material being loaded onto the

auger at the bottom. If the flights were allowed

to empty in this way then the auger could start to load from the sides of the pile bore, a phenomenon known as side loading.

Side loading would loosen the surrounding

soils which is detrimental to the skin friction of the finished pile. In fact many CFA piles

have been observed to have lower skin friction than expected from calculation. In addition on some sites skin friction has been observed to vary from one pile to another by as much as 100%, which illustrates just how critical the

boring of the pile is to its performance.

2.2 Pre-charging

This refers to the practice of pumping

sufficient concrete into the auger stem in order

to fill it before extraction of the auger begins.

Typically the required pre-charge volume is between 150 and 300 litres.

After boring and while pre-charging it is important that the auger is not excessively

rotated. In granular soils this action can have a detrimental affect not only on the shaft friction because of side loading, but also on the end

bearing capacity of the pile due to the material

at the base being loosened.

Prior to pre-charging it is common practice to

lift the auger slightly off the bottom of the bore

in order to allow the bung or "clack" at the

auger tip to open (to allow the concrete to flow

through). Experience shows that this lift should be kept to a minimum of 100mm.

2.3 Concreting

Once the auger has been pre-charged and the

bung is blown, extraction can begin. It is good

practice to rotate the auger during the initial stages of concreting in order to carry concrete and debris up onto the auger. Once this has

been done and concrete pressure is observed at the swan-neck then the auger can be

withdrawn, balancing the rate of extraction

with the amount of concrete pumped through

it.

The concrete supply pressure is usually

measured at the top of the auger stem at the swan neck. This means that for pressure to be

measured the auger string has to be full of

concrete. With a stem of 25m in length this translates to a pressure of about 500kN/m2 or

5 atmospheres at the auger tip.

Given that measuring pressure is not always

possible, concrete flow rate versus auger

extraction becomes the best guide to producing

456
sound piles. Over-break is that concrete used

over and above the net volume of the bore.

Oversupply should always be positive

including towards the pile top where the

ground is loosest, to ensure that concrete always flows up the flights. Otherwise

contamination is possible, particularly in wet

soils.

Over-break targets are critical for the correct construction of a CFA pile. In stiff soils pulling to high targets, say of 25% or more,

may be impossible as the bore cannot yield to take the oversupply. In this case concrete will

eventually escape to the ground surface or, more likely, the high pressure will lead to a blockage in the auger. Conversely, low targets

in loose or soft ground could lead to defective

piles, as the concrete will slump and leave the

bottom of the auger tip exposed. It is therefore

important that the over-break target is set for

each contract and modified throughout the job

as necessary.

3.0 STENT INTEGRATED RIG

INSTRUMENTATION SYSTEM (SIRIS):

SIRIS is first and foremost a system for

monitoring the construction of continuousflight-auger (CFA) piles. SIRIS has been

developed entirely by Stent and has been in service since about 1998. It is currently being

used on all rigs in the CFA fleet [2].

The purpose of SIRIS is to assist the rig driver

with constructing piles by providing him with

a detailed picture of various parameters during

the construction process. These parameters

include auger depth, rotation, concrete

pressure, concrete flow and over-supply.

In addition, SIRIS produces a complete record

of the construction process for each pile,

including the occurrence and cause of any

delays. This record or "pile log" is then used

for project management purposes and to produce a graphical record of each pile for

presentation to the client. These client plots can be provided on paper or in the form of an

electronic record along with the software

necessary to view them.

SIRIS is effectively made up of three parts:

1. A computer on each of the CFA piling

rigs and a number of sensors.

2. A database for storing, reviewing and

managing pile logs.

3. A viewer for use by engineers or

clients to review pile logs.

3.1 Rig Computer

Each piling rig is fitted with an industrial IBM

compatible PC running the Windows NT

operating system. This PC is connected to a

full-colour, touch-sensitive high-brightness screen through which the driver controls the

whole system. The screen is bright enough to be used in direct sunlight and the system is controlled via a user-friendly system of

coloured buttons.

This PC is also connected to a number of

sensors distributed about the piling rig as shown in Figure 2.

3.1.1 Concrete Pressure

A pressure sensor at the top of the auger, attached to what is referred to as the swanneck, is used to measure the pressure of

concrete pumped through the auger during the

concreting phase of piling.

3.1.2 Depth

Two sensors on the rotary table or at the cat- head (the top of the mast) are used to measure

vertical movement of the rotary table in order

to calculate auger depth.

3.1.3 Rotation

Another two sensors on the rotary table are used to measure the number of revolutions of

the auger and the direction in which it is rotating.

3.1.4 Concrete Flow

This is measured by a sensor in the line that detects the strokes of the concrete pump and

therefore allows the volume of concrete to be

calculated.

3.1.5 Torque

The pressure of the hydraulic fluid delivered to the rotary table is measured in order to give a rough indication of the torque being delivered

by the auger during boring.

457
During the piling process SIRIS interrogates

these sensors fifty times per second and uses

the data to present the driver with a clear

picture of what is happening. The sensor

values are also used to create a detailed log of

the whole process. Information is recorded for

every 0. 1 metres of the pile during both boring

and extraction. In addition delays are also

recorded, along with the cause of the delay as indicated by the driver from a pre-defined list.

3.2 The SIRIS Database

The pile logs recorded on the CFA rig

computers are downloaded on a daily basis,

either by floppy disk or (increasingly often) by

GSM modem. They are then copied onto the

SIRIS database which resides on a server on

the Stent internal network

As well as providing a mechanism, for storing,

retrieving and reviewing pile logs the database

generates a number of statistics which are used

to assist the management of piling contracts - such as rates of production and a breakdown of

the cause of delays. It also generates statistics on a historical basis which can then be used to improve the estimates for future jobs. It is because of this use of data for other internal

processes that SIRIS is referred to as an

integrated rig instrumentation system.

3.3 Pile Log Viewers

As well as the SIRIS database which is only

accessible on Stent's network, there are also

two other "stand alone" software packages that can be used for reviewing pile logs. One of

these is used by Stent's engineers when they do

not have access to the network. The other is a

simplified version of this software that is intended for use by clients for reviewing and

printing pile logs that have been passed to them electronically.

4.0 JUST-EV-TIME PILING:

In his 1984 Rankine lecture Wroth discussed

different in-situ tests in which the parameter

Undrained Shear Strength (Xu) is measured.

He showed how the tests were fundamentally

different and compared them to the

unconsolidated undrained triaxial test. Differences such as the directions and freedom

of rotation of the three principal stresses were

highlighted. He described the different test

results as a hierarchy of !„. He concluded, "it

is imperative for a designer to recognise this hierarchy, and to select a strength which is appropriate to the analysis or the design

procedure being used" [3]. For the specific case of Continuous Hight Auger (CFA) piles

the industry relies mostly on the

unconsolidated undrained triaxial and/or

standard penetration test to obtain a general

view of the with depth over a site. This is then used to predict the performance of all the

piles on a site using an undrained analysis. The

problems associated with this process are well

known in the field of geotechnical engineering

and will not be discussed in this paper. The

results of an Imperial college investigation

showing the inadequacy of current pile design

practices are not surprising given the current design methods. Sixteen entries from seven

countries were received for the prediction of

load capacity and displacement of a jet grouted

and a control pile. The predictions for the load

bearing capacity of both piles differed by

almost an order of magnitude [4].

4.1 "Smart" Auger

Sensors on the piling rig vehicle could obtain

much of the information required for JIT-pile,

such as auger torque, and this is the obvious

approach. However there are significant

probleins:

• Large piling rigs tend to be custom

manufactured and vary in details such as hydraulic pump performance. This means

that each individual rig would require

independent setting-up and calibration. • Time taken for setting-up, calibration and

maintenance of the sensors would reduce

the availability of a high-cost asset. • The use of variable displacement hydraulic

pumps and motors means that the

relationship between system pressure and

torque may not be that straightforward.

• Moving JIT-pile equipment from one rig to another becomes a major task.

The solution is to concentrate as much sensing

as possible on the auger itself. Augers contain

a short link that can be engineered into a focus

for data collection and communication. A link

has been prepared by the addition of strain gauges to measure both torque and axial force

in the auger. Calibration has been carried out

458
in the laboratory at Lancaster (Figure 3). The

information is then relayed to the rig

instrumentation system by radio link telemetry.

This is the so-called "Smart Auger" concept

and represents an important commercial spinoff from the research. Such systems can be

easily moved between rigs and serviced

independently of the expensive plant.

The adding of additional instrumentation and

sensors to the auger itself allows direct

measurement of torque and vertical load

information during the boring stage of pile

production. These readings can then be

interpreted and used to estimate the undrained

shear strength (Xu) of the surrounding soil.

4.2 Method

The auger is advanced one pitch every

revolution or "corkscrewed" into the soil for a

certain distance, to ensure the least possible

disturbance to the soil. The auger can do this under its own weight. The winch is then

applied to pull back on the auger stopping

penetration, while the auger is allowed to

rotate at a specified rate. The cylinder of soil penetrated by the auger is sheared. The torque

as well as the pullback force on the auger is measured and the shear stresses imposed by

these on the cylinder of soil being sheared is calculated. The resultant maximum shear stress

is then assumed to be related to the undrained

shear strength of the soil. Model tests at Southampton University have been used to test

this theory.

4.3 Results

Work is continuing to validate the lab based

model tests with the production of a full sized

auger section equipped with the necessary

sensors and instrumentation. A test rig capable

of applying the large forces has been

constructed to permit full calibration and

testing of the auger section with field trials due

to commence shortly.

5.0 CONCLUSIONS:

If the information gathered proves not to be

accurate enough for design purposes it still provides a useful amount of information for

validating every pile on site and picking up

anomalies in subsurface conditions.

Furthermore it could lead to the automation of

the drilling process, eliminating the influence

of the operator on performance of the pile.

To date, all the indications are that an

appropriate relationship between drilling

resistance and pile strength has been

established. Current testing work is underway

at Southampton to verify the results and the work will shortly progress to site testing and

verification.

The effective exploitation of 'difficult ground'

will increase in importance as old sites are redeveloped for new uses. This means that the

demand for piled foundations will increase,

and it is therefore timely to address the issue of

how new technology can improve the process.

6.0 ACKNOWLEDGEMENTS:

Throughout the grant period Stent Foundations

Limited, under their own resource, developed

their own rig instrumentation system known as SIRIS, and it was decided that both the

collection of additional data and the final JITpile system should be compatible with this. The JIT-Pile funding has been through the

UK's EPSRC - grant GR/M90450.

7.0 REFERENCES:

1. D. W. Seward, S.D. Quayle, N. Mure, J. N.

Scott "0« Site Pile Instrumentation and its Integration into the Management Process",

17th lAARC/IFAC/IEEE Int. Symp. on Automation and Robotics in Construction,

Tokyo, Japan, (2000)

2. J.N.Scott ''Integrating Piling Rig

Instrumentation with the Site and Project

Management Process", International

Symposium of Tunnel Construction &

Piling, 1999.

3. Wroth, CP. ''The interpretation of in situ soil tests" Geotechnique; 1984. Vol 34, No

4 pp 449-489.

4. New Civil Engineer. "Scattering

predictions" Dec 1999 pp 34.

459
Figure 2 - CFA rig based sensors

Figure 3 - Auger instrumentation testing at Lancaster University.

460
GPS-BASED WIRELESS COLLISION DETECTION

OF CONSTRUCTION EQUIPMENT

Amr A. Oloufa^ , Masaaki Ikeda^ & Hiroshi Oda^

1- Associate Professor & Director of Construction Engineering

Department of Civil & Environmental Engineering, University of Central Florida. P.O. Box 162450, Orlando, FL 32816-2450, USA.

Email: aoloufa ©mail.ucf.edu

2,3- Fujita Technical Center, Fujita Corporation

Ono 2025-1, Atugi, Kanagawa pref., Japan

Email: m-ikeda @fujita.co. id ' Oda@fuiita.co.ip^

Abstract: This paper reports on research related to avoiding collisions in construction sites using differential GPS technology. In this project, the researchers developed and

implemented a system where GPS technology was used in tracking a single vehicle and

relaying its information to a central server. Using another simulated vehicle, the server evaluated collision scenarios and sent cautionary messages to the roving vehicle if a colUsion is impending. The paper concludes with a summary of the application, along with a discussion of the hmitations of GPS technology and the required augmentation by other

technologies.

Keywords: GPS, colUsion detection, construction, robotics, automation

INTRODUCTION

Construction sites with regular and robotic

equipment suffer from the potential of

collisions between the various types of

equipment. Such collisions are extremely

costly in terms of their potential injury and

other related costs and wasted time. The

situation is further aggravated in sites with a

large number of robotic equipment that is remotely operated from relatively long

distances with the aid of cameras. In this situation, construction robotic equipment

operators are often limited in their viewing

fields due to insufficient cameras or bandwidth

and other transmission challenges. The aim of

this project is to detect and prevent impending

collisions through the application of the Global

Positing System (GPS) and wireless

communications.

COLLISION DETECTION TECHNOLOGY

Several technologies exist for collision

detection and avoidance. They differ in their

cost, size, response time, reliability, and

effective operational range. Ultrasonic

technologies rely on high frequency devices.

They have a low implementation cost, small

size, and have a fast response time. They are not reliable under some conditions, and their range is only a few feet. Infrared technologies

have been used for a while. They have a very

small implementation cost and are small in

size. However, they exhibit a high response

time, are not very reliable, and their range is also very short. Radar technologies are perhaps

the most effective for collision detection.

Improvements have led to size reductions and

high reliability. However, their cost is relatively high. Vision technologies have also

been used for collision detection. However,

their cost is extremely high due to heavy

computational requu^ements. They also suffer from low reliability in some lighting

conditions.

GPS technologies offer a multitude of benefits

and their costs have been continuously

decreasing. The major benefits of using GPS

are that these technologies are not dependent on line-of-sight issues (to other vehicles),

which is one of the major limitations of all the

technologies listed above.

461
GLOBAL POSITIONING SYSTEM

Global Positioning System (GPS) is a satellite based radio-navigation system. There are 24

GPS satellites orbiting the Earth and

transmitting radio signals. Based on measurements of the amount of time that the radio signals travel from a satellite to a

receiver, GPS receivers calculate the distance

and determine the locations in terms of

longitude, latitude, and altitude, with great accuracy. GPS was created, and is controlled by the U.S. Department of Defense (DOD) for military purpose, but is available to civilian users worldwide free of charge.

GPS can be used in various areas such as air, land, and sea navigation, mapping, surveying

and other applications where precise

positioning is required. The system inherently

has no limitation in speed or altitude, but U.S. DOD requires that commercial receivers be

limited to operate below about 900 knots and

60,000 feet (18,000 meters).

Accuracy of GPS is the degree of conformance

between the estimated or measured position,

time, and/or velocity of a GPS receiver and its true time, position, and/or velocity as compared with a constant standard. Radio

navigation system accuracy is usually

presented as a statistical measure of system

error and is characterized as predicable,

repeatable, and relative accuracy {Fundamentals of GPS, 1996).

The accuracy of GPS receiver is affected by

errors caused by natural phenomena,

mechanical failure of elements in the system,

or intentional disturbance.

For the purpose of collision detection, real- time high position accuracies (sub-meter) are required.

TELE-EARTHWORK SYSTEM

In 1994, Mount Fugen volcano, situated in southern Japan, erupted (see Figure 1). Lava

flows from the volcano flowed downhill

threatening the town of Shimabara. A project was developed to construct two canals to channel away future flows into the Sea of

Japan.

Since work of this nature is carried under the constant threat of lava flows, it was desirable

to use in construction, an automated tele- earthwork system, remotely controlled from a

safe distance (See Figure 2).

The Fujita Corporation, a large Japanese

Consfruction conglomerate, developed and

implemented a Tele-earthwork system. This

system consists of dozers, backhoes, trucks,

and other ancillary vehicles and equipment.

The system is designed to be remotely

operated and has been used in several projects

as shown in Figure 3.

Figure 1 : Mount Fugen Volcano Site

462
1994: 1 St trial at Mt. Fugen

(Excavating and transporting earth and sand) 6,500m3

1 994 2nd trial at Mt. Fugen

(Excavating and transporting earth and sand) 16,000m3

1994-1 9950 3rd trial at Mt. Fugen

(Excavating and transporting earth and sand) 100,000m3

1997: Recovery from disaster of a slope collapse at Kumamoto

1997: Recovery from disaster of a slope collapse at Nagano

1997: 1 St trial of unmanned constructing dam at Mt. Fugen

1998: Recovery from disaster of a slope collapse at Akita

1998: 2nd trial of unmanned constructing dam at Mt. Fugen

1999: 2nd trial of unmanned constructing dam at Mt. Fugen

COLLISION-RELATED ISSUES

In automated construction applications,

especially in the case of remote operation, the

lack of true visual and depth perception

increases the likelihood of collisions between

equipment involved in the operation.

And while the literature is full of work related

to optimum path selection for robotic and

automated equipment, the implementation of

these algorithms, especially in earthmoving

sites with their constantly changing topology

and large number of equipment, have proven

to be impractical.

The mostly widely used technology for

collision detection is radar-based. And while

this technology is excellent for avoiding

outright collisions, it is ill-suited for applications that involve work in dirty

environments, with large objects or terrain obscuring other vehicles that are not detected

by radar. Here GPS technology comes to the

rescue.

Because the technology does not rely on line of sight to other monitored vehicles, the researchers developed an architecture for sensing and warning vehicles of impending

collisions as shown in Figure 4.

463
System Architecture

Server Vehicle

Figure 5 shows the schematic of an advanced

technology construction system developed by

Fujita Corp. All of the construction equipment

at the site operates without on-board drivers. The vibrating roller moves autonomously,

aided by GPS. Another backhoe, bulldozer,

and two dump trucks are remotely controlled,

each by a different operator.

While operating the equipment, each remote

operator had to be watching several screens showing images from a camera on the vehicle,

and another remotely controlled camera at the

site. This denies operators the improved

capability of controlling equipment in reference to "true" 3D perspectives. To avoid

collisions, this architecture required increased

vigilance by operators, and frequent verbal

warnings among operators.

In this project, the proposed collision detection

system would have substantially improved

construction efficiency, and reduced operator

overload. HARDWARE ARCHITECTURE

The hardware is comprised of two subsystems, a server subsystem, and a mobile (rover)

subsystem. The server subsystem consists of a PC-based server connected to a radio. The

rover (equipment side) consists of a

differential GPS system receiver, GPS, a

laptop, and a radio.

Figure 5: Arrangement of equipment in site

SOFTWARE ARCHITECTURE

The software architecture is shown in Figure 6.

The software consists of:

1) Vehicle Software

This software receives the DGPS message and

then sends it to the server. The position is formatted according to the RMC sentence.

464
GRS Mos33ge Decode

Stopping Distance Oalculatlon

"CAUTION" Message Broadcast

Map Server

GPS Acquisition "CAUTION" Massage Decode

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2) Server Software

This software receives position information

from the construction equipment, and

calculates potential collision scenarios with the simulated vehicle. If a potential collision is detected, the equipment operator is alerted with the speed and direction of the simulated

vehicle (see Figure 7). The operator can also view construction equipment position, and

track on a an aerial view of the construction

site, as shown in Figure 8.

465
vectors representing two moving vehicles.

Each vector is defined by a point And a

direction. In this case. The GPS position of the

vehicle (i.e. vehicle location), and the vehicle

bearing (also from GPS input) define each

vector.

After the intersection point is computed, and

knowing the vehicles' speeds from GPS, the

program calculates the distance from the

potential collision point to each vehicle

location. The program also calculates the

braking distance required for each vehicle in

its operational scenario. If the braking

distance required approaches the distances

above (within a specified tolerance value), the server then issues potential collision alerts to the vehicles in question transmitting an alert message, along with the direction and distance

of the vehicle in question.

CONCLUSION

This paper presents research aimed at utilizing

GPS technology and wireless communications

for collision detection on construction

websites. The technology can be applied in both automated as well as traditional

construction sites.

The technology presented here seems to have a

lot of promise, however, several areas such as optimum system architecture, signal reliability,

GPS accuracy, and potential differential signal

latency and communications issues have to be

evaluated.

ACKNOWLEDGMENTS

The authors wish to thank the Center for Advanced Transportation Simulation Systems

(CATSS) of the University of Central Florida,

and the Fujita Corporation for sponsoring this research.

REFERENCES

Dana, P. H. Global Positioning System

Overview TX, 1995.

Do, W. S., A. Oloufa and H. Thomas.

Evaluation of GPS devices for a Quality

Control System for Compaction Operations.

Transportation Research Record # 1675 pp. 67-74, 1999.

Fundamentals of GPS. Arlington: VA,

Navtech Seminars, Inc., 1996.

GLONASS Group, ''About GLONASS", MIT

Lincoln Laboratory, http: //satnav.atc.ll.mit.

edu/glonass/about^lonass.html, December

1997.

Hum, J. Differential GPS Explained.

Sunnyvale: CA, Trimble Navigation, Ltd.,

1993.

Kennedy, M. The Global Positioning System

and GIS: An Introduction. Chelsea: MI, Ann

Arbor Press, Inc., 1996.

Li, C. Development of A Tracking System for

Pavement Compaction, Master of Science

Thesis, Department of Civil Engineering, Penn

State University, 1995

Oloufa, A. A. "A GPS-based System

Architecture for the Quality Control ofAsphalt

Compaction'. IEEE Robotics and Automation

Magazine. March 2002. Vol. 9, No.l, pages

29-35.

Van Diggelen, Frank, ''GPS and

GPS+GLONASS RTK\ New Product

Descriptions Session, lON-GPS 97, Kansas

City, MO, 16-19 September 1 997.

Y.F. Ho, H. Masuda, H. Oda, L. W. Stark

"Distributed Control for Tele-Operations".

Advanced Intelligent Mechatronics. 1999.

466
PROTOTYPE IMPLEMENTATION OF AN AUTOMATED

STRUCTURAL STEEL TRACKING SYSTEM*

by

Karen M. Furlani-, DeWitt T. Latimer IV^ David E. Gilsinn^ and Alan

M. Lytle^

ABSTRACT: This paper discusses the prototype implementation of a system developed by researchers

at the National Institute of Standards and Technology (NIST) for the transfer of real-time on-site metrology and metrology-based data for tracking steel frame construction. The purpose of the implementation is to demonstrate the feasibihty of automatically transferring information from the construction site to project management databases and associated appHcations, specifically for the

identification and tracking of structural steel subsystems. The successful integration and

implementation of the on-site field data collection system with a project information management

system enables a field worker to identify and track a steel member's final position and orientation on

the job site. KEYWORDS: construction automation, 3-D coordinate measurement systems, project informadon

management systems, communication protocols, coordinate frame transforms, posifion and orientation determination, steel tracking

1.0 INTRODUCTION

Many existing technologies that aid in the

automation of construction component

tracking systems are limited in their use by a

lack of construction industry standards

supporting interoperability between various

hardware and software systems. In addition, to achieve the precise positioning of components

to a level of accuracy sufficient for the

placement of structural steel, standard methods

are needed for the registration and calibration

of 3-D coordinate measurement systems and

for the determination of part position and

orientation. To assist the construction industry

in overcoming these obstacles and achieve a

fully integrated and automated environment,

the National Institute of Standards and

Technology (NIST) has on-going research in several related areas. Researchers in the

Construction Metrology and Automation

Group (CMAG) are involved in the

fundamental research and development of

position/orientation tracking systems, sensor

interface protocols for construction data

telemetry and construction site simulation.

The Computer Integrated Construction (CIC)

group is doing research on the visual

representation and simulation of construction

and building related models, activities, and

processes. CMAG and CIC have collaborated on a joint

implementation to demonstrate the feasibility

of transferring information from the job site to project management databases and associated

applications in a real-time and automated

fashion. The purpose of the combined systems

is to enable a field operator to identify, register

and spatially visualize the final position and

orientation of select structural steel members at the job site. Prior to the implementation, the

Component Tracking (Comp-TRAK) system

functioned independently of the Project

' Certain conmiercial equipment, instruments, or materials are identified in this report in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement

by the National Institute of Standards and Technology, nor is it intended to imply that the materials or equipment

identified are necessarily the best available for the purpose. Former member of the NIST Construction Metrology & Automation Group (CMAG). Current address: 1201

Cutter Lane. Boulder, CO 80302, (303) 440-8433, karen@furlani.com

^ Former NIST CMAG member. Current address: 4902 Forbes Ave, Box 114, Pittsburgh, PA 15213,

(412) 901-0549, dl4s@andrew.cmu.edu

Optimization and Computational Geometry Group member, NIST, 100 Bureau Dr., Gaithersburg, MD 20899,

(301 ) 975-3491, david.gilsinn@nist.gov

^CMAG member, NIST, 100 Bureau Dr., Gaithersburg, MD 20899, (301) 975-6078, alan.lytle@nist.gov

467
Information Management System (PIMS),

relying on post-processing to achieve

automated tracking of steel members at the

construction site. Utilizing standard interface

protocols to integrate the Comp-TRAK system

with the PIMS enables seamless

communication between the various system

components.

2.0 SCOPE

In earlier work, CMAG proposed an overall

system architecture [1] and developed a prototype system that experimentally

demonstrated 3-D spatial tracking of discrete

components in real-time and under controlled

conditions to viewers at a remote location [2]. The prototype field data collection system was

field tested at the Building 205 Emission

Control System (ECS) Addition - a US$6

million project on the NIST, Gaithersburg

campus [3].

Previous work in communications research

investigated the applicability of IEEE 1278 as a protocol for exchanging information about

changes to the construction site [4]. Since the

IEEE 1278 standard is written for distributed

interactive simulation, it does not contain all the features necessary to describe the results of

building a world model from sensors. Earlier

work focused on answering the data pedagogy

questions, specifically, the "who, what, where,

and when" criteria for the types of data to be

communicated [5]. These previous projects

cumulated in small prototypes that lead up to

this project.

This paper discusses advances in the field data

collection system, site registration method,

coordinate transform routine, part locator

routine and the project information

management system, as well as the underlying

communications that enable the various

systems to function in a seamless fashion. The

prototype implementation was limited to capturing the "as-built" status of structural

steel members during the construction of the

Tower #2 Wind Frame Assembly at the

Building 205 ECS Addition.

3.0 SYSTEM ARCHITECTURE

Overviews of the system architecture and the

flow of operations are provided in Figures 1

and 2, respectively. The following sections

describe the function of the sub-systems.

3.1 Part Tracking Overview

Structural steel members scheduled for arrival on the Bldg. 205 ECS construction site are each tagged with a bar code at the galvanizing

plant prior to shipment. Reference data for

each tagged part is concurrently pre-loaded

into the PIMS database. Steel member

identification data are directly scanned into a rugged, wearable computer with wireless access to the PIMS database hosted on a remote server. A database query following the scan provides additional part-related

information as well as a 3-D VRML (Virtual

Reality Modeling Language) model of the steel member. User-friendly Web browsing

software then guides the field worker through

the process of measuring the position of key

fiducial points with a long-range, laser-based

3-D coordinate measurement system. These

fiducial points are pre-specified measurement

locations defined at readily identifiable

features of interest such as comers. Three

fiducial points, of which two must be noncollinear, provide a sufficient set of locations

to establish the position and orientation of the

member in 3-D space. The measured points

are transformed from the local coordinate

frame to a globally referenced site coordinate

system. In this implementation, the member's

site frame position and orientation (pose) is calculated via a Part Locator Routine hosted

remotely. The steel member's identification

data and local fiducial measurements are wirelessly transmitted to this routine that updates the project database with the

member's site-frame pose. The same data are transmitted back to the field worker's wearable

computer to update the user's visual display.

3.2 Field Data Systems User Interface

All operations conducted on the field data

collection system employ a web-based

interface. This includes user I/O and remote

access to the part tracking routines and PIMS.

This interface format was chosen over a

proprietary application because it allowed

inherent cross-platform compatibility and

relatively simple page creation and

modification.

468
3.3 Project Information Management System

The Project Information Management System

(PIMS) allows information relating to structural steel members to be stored, accessed

and modified. There are four essential parts of

the PIMS system used during the

implementation: an object-oriented database, a JAVA-based database server, a Common

Object Request Broker Architecture (CORBA)

compliant trading service, and a database

administrative tool.

The database was developed based on a minimal physical schema derived from the

CIMSteel Integration Standard (CIS) CIS/2

logical schema [6]. For the implementation,

part definition data based on the CIS/2

representation of steel members was pre- loaded in the PIMS database via the

administrative tool. This information is used

to simulate structural steel parts in the ECS

Tower #2 sub-assembly in VRML. The

CORBA is used as the underlying

communications infrastructure, allowing users

to connect to the PIMS server and get

information to and from the database.

4.0 POSE DETERMINATION

4. 1 3-D Coordinate Measurement System

To successfully deploy the tracking system in the field, in-situ measurements of the steel frame members must be registered to a

globally referenced site coordinate system for part pose determination. The field tracking

system uses the Vulcan 3-D coordinate

measurement system by ArcSecond Inc. to measure the local frame position of each target

fiducial point on the part. This system uses two rotating laser transmitters and a receiving

wand to calculate wand tip position via

triangulation. The calibration method utilized for the implementation employs a proprietary

variation of standard photogrammetry bundle

techniques to calculate transmitter positions

using the optical center of the first transmitter

as the local origin. To register the coordinate

measurement system to a globally referenced

site frame, the locations of the transmitters

must be known in the site frame.

4.2 Coordinate Frames & Transform

Two coordinate frames exist - a local frame

defined by the location of the transmitters and

a globally-reference site frame. To register the

local frame to the site frame, the transmitters

are placed on benchmarks surveyed in the Maryland State Plane Coordinate System of

1983 (MD SPCS) using the North American

Datum 1983 (NAD83) as the horizontal datum

and the North American Vertical Datum 1988

(NAVD88) as the vertical datum.

A transform matrix was developed to translate (move a point in space a finite distance along a given vector direction) and rotate the Cartesian

points measured in the local frame to the

Geodetic-Latitude-Longitude-Ellipsoid height

of the site frame. Five points known in both

the local and site frames are necessary to perform the transform: transmitter locations

and three additional reference points. Figure 3

shows the relative location of the five points

for a local frame, "Site Frame 1", established

for the implementation. K15 and K12 are used

to establish a local X coordinate axis with

positive direction from the origin transmitter

K15 to the reference transmitter K12. The Yaxis is established perpendicular to the X-axis

by using the right hand rule around the vertical Z-axis with positive direction upwards. Three

other non-collinear points identified by K13,

K16 and K19 serve as reference. These last three points must be non-collinear to provide a unique solution for the transform matrix.

Refer to Figure 4 for a visual guide of the vector transform used for the implementation.

4.3 Part Locator Routine

A part locator routine was developed to visualize the final part position and orientation

in the site frame. Developed in JAVA, the

simple, robust part locator algorithm runs on

the client-side and computes the part pose from

the three measured fiducial point locations in the site frame. The algorithm takes the three

inputs associated with a steel part from the

transform routine and fixes the first point in the site frame, uses the second point to define

the axis and the third point to define the plane.

While this is not a precise method for determining the part pose, it does serve the purpose of enabling the visualization of the

part within the site frame and for providing an

469
estimate of the as-built location of a part's

final pose.

5.0 INTEGRATION & COMMUNICATION

The key to successful development of the

prototype implementation resides in seamless

communication between the separate

components. Component tracking data from

both the ArcSecond measurement tool and the

bar code scanner is captured, reformatted, and

stored in the wearable computer's keyboard

buffer via NIST-generated utilities on the

wearable computer. These data are then

displayed through a series of web pages and

stateless CGI programs. The componenttracking library, linked through the CGI

programs, queries the remotely hosted PIMS

for related part information such as VRML

models. Finally, CORBA-compliant

communication routines provide the interface

between the component-tracking library and

the PIMS. Figure 5 illustrates the various

communication methods developed for the

implementation.

5.1 Wireless Communications

Running CAT-5 (Ethernet) cable across an

active construction site is impractical so it is necessary to setup a wireless network. This

allows users on the site to use untethered

computers to communicate with other

computers on or off the site. The Orinoco

wireless networking hub and PC cards by

Agere Systems were used to support TCP/IP

networking to connect the wearable computer

to the server.

6.0 CONCLUSIONS

The prototype implementation demonstrates

the successful integration of various subsystems and applications using standard

interface protocols for the automated tracking

of structural steel members at a job site. Enabling the transfer of real-time on-site

metrology and metrology-based data from the

job site to the appropriate applications and

users supports operations that are dependent

upon knowing and communicating the exact

location and orientation of objects on the

construction site.

Some areas for improvement and future work

relating to the prototype system are discussed

in the following two sections.

6. 1 Accuracy of Reported Pose

The accuracy of the measured 3-D coordinate

data supplied to the part locator routine should

be quantified to provide an accuracy metric

with the reported pose. This metric will enable

a more precise determination of the accuracy

of the reported pose for the part - a necessary

component for the tracking system to be truly

useful for operations such as the automated

placement of structural steel members to within standard tolerances.

6.2 Communication

While the system communicated the essential

information from the field to the project

information management system, there are several areas to expand for error handling,

error recovery, and extensions to the

communications infrastructure.

As this was a prototype system, error handling

and recovery were only minimally

implemented. However, in real systems, error handling will need to handle users errors such

as setup and registration of the coordinate

measurement system, incorrect matching of

field measurements to objects, and collection

of collinear fiducial points. These are places

where people interact with the system to provide information, and thus are potential sources of error that must be handled reliably.

The communication infrastructure, while

complete for the given application, needs to be

extended for future use. First, define a grammar for field measurements that can be

common to all programs that use field measurements. Second, establish a communication protocol for coordinate system

transforms since the exchange of the

transforms between systems is not handled

well in the prototype system. Third, express

the system in as neutral a format as possible, so as to be extensible to future communication

technologies.

470
7.0 REFERENCES

[1] Furlani, K.M., and Stone, W.C.,

"Architecture for Discrete Construction

Component Tracking," Proceedings, 16'*' lAARC/IFAC/IEEE International Symposium

on Automation and Robotics in Construction,

Madrid, Spain, September 22-24, 1999.

[2] Stone. W.C.. Furlani, K., and Pfeffer, L., "Automated Part Tracking on the Construction

Site," Proceedings, 4"' International

Conference on Robotics for Challenging

Situations and Environments (Robotics 2000),

Albuquerque, NM, Feb 27 - Mar 2, 2000.

[3] Furlani, K.M., and Pfeffer, L.E.,

"Automated Tracking of Structural Steel

Members at the Construction Site",

Proceedings, 17th lAARC/IFAC/IEEE

International Symposium on Automation and

Robotics in Construction, Taipei, Taiwan,

September 18-20, 2000.

[4] DeWitt Latimer IV, "Work Towards an

Application Protocol to Support

Interoperatbility of Sensors in Construction

Metrology (LiveView)", National Institute of

Technology Internal Report (NISTIR) 6867,

National Institute for Standards and

Technology, Gaithersburg, MD, USA, May 15,

2002.

[5] Pfeffer, L.E., and Latimer, D.T., "Toward

Open Network Data-Exchange Protocols for Construction Metrology and Automation:

LiveView," Proceedings, International

Conference on Automation and Robotics in Construction (ISARC-99), Madrid, Spain,

September 22-24, 1999.

[6] CIMSteel Integration Standards,

Release 2, URL: http://www.cis2.org, The

Steel Construction Institute, Ascot, Berkshire,

UK, URL: http//www. steel-sci.org.

ArcSecond

Spatial

Tracking

Wand

Bar code

reader

ArcSecond

Point Grabber

(C++)

Web

Browser

Belt- Wearable PC

A WIRELESS A

Network (CORBA)

ber/wire

HTML

CGI

(LiveView)

Web Server

Project Information Management

System (JAVA)

Object- Part Oriented Locator Database Routine (JAVA) (JAVA)

Figure 1. System architecture developed for the prototype implementation.

);

471
Field Server

Choose coordinate frame

set for current job

Scan bar code for part ID

Collect FP measurements

Designate if part is in final position

View updated model

Acknowledge

Acknowledge

User may begin new

session for next part or quit

Confirm correct part

Store coordinate frame set Request part ID

Store part ID Request part info

Return part info, VRML model &

descriptive information

Return VRML mode! with fiducial point locations

Store measured fiducial points Transform fiducial points from

local to site frame

Return VRML model with computed pose (to Field) Send final location (to PIMS)

Acknowledge

Pre-load part definition data

Return part info for VRML

visualization and fiducial point locations

Part Locator Routine

• Compute part pose

• Return part pose for VRML visualization

Store final location Acknowledge

Figure 2. Operational flow chart outlining steps between the Field, Server and PIMS

20 25 30 35 40 45 50 55

Site Frame - Relative East in Meters

Figure 3. The local frame graphed within the site frame.

472
Fiducial Point O - Origin Offset

in Site Frame L - Vector

Defining

Fiducial Point

in Local Frame R - Vector

Defining

Fiducial Point

in Site Frame L L_ - Vectors

* " Defining Local Frame 5 5, S. - Vectors

Defining Site Frame

Figure 4. A vector transform from the local frame to the site frame.

ArcSecond Sensor

Driver Bar Code ScannerDriver

Keyboard Buffer

Web Browser &

Input Fields HTTP I

HTTP & CGI

Web Server

CORBA Requests

Project Information Management System

Figure 5. Communication methods used between system modules

473

THE EFFICIENCY OF A 3-D BLADE CONTROL SYSTEM IN THE

CONSTRUCTION OF STRUCTURE LAYERS BY ROAD GRADER - AUTOMATED DESIGN-BUILD OF ROAD CONSTRUCTION IN

FINLAND

Rauno Heikkila

Dr. Tech., Senior Research Scientist, University of Oulu, Faculty of Technology,

Research of Construction Technology, Finland, h ttp://www. rate, oulu. fi, rauno. heikkila @oulu. fi

Mika Jaakkola

MSc. Tech., Research Scientist, University of Oulu, Faculty of Technology,

Research of Construction Technology, Finland, http://www. rate, oulu. fi, mika. jaakkola @oulu. fi

Abstract: The paper reports on the research work in the domain of automated road

construction. A new method and prototype of automated road grader has been developed in Finland. The working experiments show measurable influence and quality as well as economic profit to be achieved by the new technology.

Keywords: accuracy, automated construction, construction economics, design-build,

economic efficiency, road grader, 3-D machine control

Introduction

Fast progress of teleinformatics, positioning

technologies and 3-D-road design software has

enabled to develop new blade control systems

for road construction machinery. The major

expectations of these systems are to increase

productivity of the construction project and

prefer quality of the end product. The objective

is to build a complete digital link from design to layout. With the installation of centimeter

accuracy guidance on board the earthmoving

machines, the operator can fill and cut surfaces

in relation to the road design. The goal of this development project is very challenging but if work is successful and reach objectives,

economic benefit can be outstanding.

According to the publications of Finnish Road

administration the capacity of traditionally

controlled (without 3-D-machine control) motor

grader on road finishing work is in practice

about 7000 m"/shift. While grader is doing for both spreading and finishing work method

capacity is in normal road works about 2300

m3itd/shift (Work planning information for Road Construction 1-2, TVH).

Automatizing the total process of road

construction

Since late 1990 there has come several

internationally marketed motor grader 3-D

machine quidance and control applications

developed by such companies as Trimble, Leica

and Topcon with their partners. In these

applications, blade positioning needed is based on robot tacheometer or RTK-GPS. In Europe, some countries have also developed their own

systems for 3-D machine control. Detailed

research results about economic benefits and

other experiences have very little been

introduced and thus not available.

Total numerical working process of road

construction consists of four part-systems.

Helicopter laser scanning measuring system measures first terrain model. Measuring

helicopter is positioned with GPS technology.

Measuring data, terrain model which accuracy is 5-20 centimeters, is used for road structure design process. To produce steering data for the

blade of construction machine we need 3-D road

design software to produce 3-D design plan. In

addition, the design plan has to translate to actual machine control data. (Fig. 1).

475
In the construction machine there must be a "comparing-software" and blade controlling

system unit, which compares the real time

positioning data with the 3-D road-design and

calculates the steering data for the blade

controlling system. In the end of the cycle the

blade control system steers blade to right

elevation and slope. The construction machine

and the blade must fit on with the slope-sensors

to pinpoint the blade position in proportion to construction machine (picture). Controlling

system includes also real time quality control

system of as-built road structure. As-built height

and slope accuracy and efficiency on work

process is documented real time. Time and

money can be saved even 50 % by reducing

measuring costs and by more efficient grader at road construction site.

The object of our research and development

project "Intelligent road construction" is set to develop a new numerical operation process for road construction. Measurements will be

operated by advanced 3-D measurement

technologies and computer aided design by 3-D

CAD tools. 3-D design models will be control

directly without dela\' automated measuring and

construction machinery'. Finally, the quality

control will be executed through automated

quality control tools.

In this paper, the first result of the intelligent

road construction program - the automated road

grader and its working experiments are described. The construction of the mecathronics

of the road grader is solved by integrated total solution principle. Hence, the movement

possibilities of the different parts of the machine

are ver}' extensive.

A new integrated total solution principle and the

first practical implementation has been

developed in Finland. In this system the sensors and developed software algorithms control all of

the directions of blade's movements. Developed

system controls blade's height, slope and driving

line automatically but also gives the operator

possibility to control all blade movements

concurrently by one joystick. This function

gives to an operator a possibility to control real time the movements of gravels. Robotic total stations are used as a positioning system. When

operator opens the system it automatically starts to control robotic total station.

Furthermore the machine control system

contains integrated quality control system for

final height and slope of the road layer and also

graders capacity measuring features. The control

system is working in PC and thus the operator can utilize wireless data communication, which

is also included in system. Road models, quality

control and capacity data are carried forward by

email or in addition by data card.

The 3-D system has graphical interface from

where the operator can see blade position

compared to design. The digital design of the

road layer is created with Terra Street design

software. New company Roadsys Ltd has started

to market the 3-D blade control system. The

trade name is Robot Grader (Fig. 2).

Site tests

Two experiments were executed in two road

construction sites as parts of motorway

construction -projects in Tomio-Kemi and Salo

in Finland. 2000-2001.

Results

The detailed results of the work studies executed

are introduced in tables 1-5. In the tables, the

term "basic capacity" is determined to be

machines work achievement per basic working

time, which is the time when machine is all time

working. The term "method capacity" means

machine's work achievement per method

working time, which includes basic time and

other time used in efficient working for example

setting times of tacheometer, waitings of

truckers, etc.

According to the tests (table 1) the standard

deviation of the 3-D blade control system in unbound base course is about 17 mm in height

direction. According to the specifications of

Finnish Road Administration the tolerance for

that work phase and product part is ± 20 mm.

All of the slope measurements (table 2) fulfill the tolerance requirements. According to the work studies (tables 3-4) the economic benefits

grew best up more than 50 %. It is also essential

to notice that the needs for measurement crew as well as the costs are decreased.

Conclusion

The practical functionality of the operation

principle was x erified by the experiment results. 476
The adequacy of accuracy was proven to be

sufficient. Economic benefits by automation were observed.

The road and traffic design and construction

techniques are developing rapidly worldwide.

Teleinformatics and positioning technologies

play important part in this process. Finland is one of the countries in developing these new

technologies and also suitable operating

environment for testing them. Construction

industry should without prejudice start to use and take advantage of these new technologies.

Intelligent Road Construction Site IRCS is a Finnish research and development programme

been started in Finland. The programme consists

of several different research and development

projects. The entirety is scheduled 2001-2005

and it collects about twenty infra companies and

other parties of road construction process. The

total investment for research activities is about 2

M€.

ACKNOWLEDGEMENTS

The authors want to warmly thank VTT

Elektronics, Roadsys Oy, Terrasolid Oy,

Geotrim, Patria Vammas, Tieliikelaitos and

TEKES - the National Technology Agency in Finland. The project belongs as a part to the

Intelligent Road Site -research & development - programme executed in Finland.

REFERENCES

Heikkila, R. (1996) The Applicability of an

Electro-Optical Coordinate Measuring

Technique to the Dimensional Control of

Precast Concrete Facade Panel Production.

Oulu, Acta Universitatis Ouluensis, Technica C

86. Doctor's thesis. 87 p. -i- Appendixes.

Heikkila, R. & Jaakkola, M. (1999) New

Automation Possibilities for Road Construction

Methods. Kosice, the 3rd Scientific Conference

with International Participation "Building and

Energy" in Kosice, 8-9 September 1999.

Heikkila, R. & Jaakkola, M. (2000) Planning

Future Activities for Road Construction

Automation Purposes. Construction Economics

News, 1/2000, p. 6-9. Jaakkola, M. & Heikkila, R. (2000) Liikkuvan

tyokoneen ohjaus tienrakentamisessa. Tiehoylan

ja murskeenlevittimen CAD/CAM-jarjestelmat.

Tienrakennusautomaatio. (Controlling mobile

work machines in Road Construction.

477

CAD/CAM systems for road grader and mass

spreader. Automated Road Construction. Project

Report. Confidential. Oulu, University of Oulu.

Jaakkola, M. & Heikkila, R. (2001)

Automatizing a road grader for Finnish Road

Company - Development Phase I. Project

Report. Confidential. Oulu, University of Oulu.

TVH 733892 (1983). Tien tekemisen

tyonsuunnittelutiedot 1-2 (Work planning

information for Road Construction 1-2). Finnish

Road Administration.

SOURCES FOR PRODUCT INFORMATION

www.leica-geosvstems.com

www.topconlaser.com/MC Products

www.trimble.com/bladepro3-D.html

www.mikrofyn.com

www.precisesurvev.com

www.roadsys.fi

Figure. 1: The principle of the numerical

working process of road construction.

Robot Orsrtor system

Graphfcal jnterfaee PC

i-antenns

Figure. 2: Robot grader. A new 3-D blade

control system principle for road grader.
Figure. 3: The 3-D surface model created for the

tests. The model was designed by Terra Street CAD application and used directly to control the

blade of grader. Figure 6: The site tests of the 3-D blade control

system.

Figure 4: An example of 3-D surface model of

Tomio-Kemi motorway.

Figure 5: The user interface for the 3-D blade

control system with wireless data

communication system.

478
Table 1. Automated road grader experiments. The height results of Tornio-Kemi site tests.

Site

number

Average

[mmj

St.dev.

[mm]

Min

[mm]

Max

[mm]

Count

[number]

Accepted

[%] *)

E5R1 -23 19 -64 22 33 66

E5R3

Jakava

-31 19 -60 19 27 50

E5r4 -19 17 -53 22 48 81

E5R3

Kantava

-21 16 -59 10 36 61

MO plv

16860-

17780

-8 17 -50 41 146 87

MO plv

15620-

16240

-3 10 -30 10 90 99

) Road structures vertical position tolerances were ± 20 mm

Table 2. Automated road grader experiments. The slope results of Tomio-Kemi site tests.

Site

number

Average

[%]

St.dev.

[%]

Min[%] Max

[%]

Count

number

Accepted

%

E5R1 0,26 -0,4 0,4 15 100%

E5r4 0,56 -0,8 1,2 14 85 %

MO

16900-

17780

-3,07 0,25 -0,6 0,5 46 100%

Table 3: Automated road grader experiments. The capacity results in adjustment tasks.

Site

number

Basic [m2/h] Method [m2/h] Area of object [m2] Adjusted aggregate

[t] mo plv

18760-

19020

1282 803 3120

mo plv

18600-

18820

2258 1650 2860

E5r4 2444 2005 2240 18

E5R1 715 677 2100 71

479
Table 4: Automated road grader experiments. The capacity results in grade tasks.

Site

number

Basic [m2/h] Method [m2/h] Method of work [t/h] / [itdm3/h]

Adjusted aggregate

[t] E5R4 617 579 162/ 108 590

jakava

E5R3 368 308 238/ 159 1358

kantava

mo plv 550 491 217/145 989

17360-

17580

mo plv 1613 1366 747 / 498 1445

17200-

17460

mo plv 1678 1498 87/58 457

17920-

18600

480
OPTIMAL CONTROL OF AN EXCAVATOR BUCKET POSITIONING

by

E. Budny, M. Chiosta, W. Gutkowski " ABSTRACT.

Recently, there is an increasing interest in controlled excavation processes. However, the main attention, in research works, is paid to the bucket motion. This part of the process can be considered as a

quasi static, kinematically induces process [3]. It means that dynamic effects, by dropping accelerations terms can be neglected. This is not a case in the second part of the process consisting of: lifting

the bucket filled with the soil, swinging the whole excavator with respect to vertical axis, lowering the

bucket and discharging it. Next, the bucket is brought back to the excavation place again. Discussing

these motions, one has to taking in to account dynamic effects. It should be also noted that mentioned

motions are lasting approximately the same time as the digging process. It is then worthy to try to minimize the time needed for bringing the filled bucket to the discharge place, and back to the digging

site. It is then the aim of the paper to present an optimal control of such a minimum time process. The

paper deals with an optimum problem of positioning an excavator bucket along prescribed trajectory

using minimum time. The paper is illustrated with numerical results giving some optimal trajectories.

KEYWORDS: excavation, optimization, control.

L INTRODUCTION

A standard excavation process, on the construction side, can be seen as composed of two

parts. The first one is the process of digging

and filling the bucket with soil or other material. The second part of the operation consists

in lifting (L) the filled bucket, swinging (S) it with respect to a vertical axis, stopping (S) it at the place where it should be unloaded, and

discharged (D). The whole process is below

defined as LSSD.

Since about twenty years, many attention has

been paid to robotics application in the construction industry. However, most attention

has been paid to the digging processes. Relatively large number of works in this fields were presented at the International Symposia

on Robotics in Construction. Among others,

Budny et a/. [3] proposed an load-independent

control of excavation process along a pre- scribed trajectory. The idea of the paper was

to propose a control system free of a number

of sensors mounted on the excavator attach- ment.

The present study is dealing with the LSSD

process, namely with the problem of minimum

optimal positioning of excavator bucket from

the position where it is filled with the soil,

ending the digging, to the place where it

should be discharged. There are several important reasons to undertake this research.

They can be listed as follows:

(1) LSSD is taking often as much dme as digging process;

(2) automation of LSSD would decrease the

operator efforts, comparing with hand

controlled motion of the bucket;

(3) optimization of LSSD should decrease the

time and/or energy needed for its realization. (4) automation of LSSD should decrease the

probability of accidents, due to human errors.

It should be noted that available modem soft- ware and hardware, with their decreasing cost, make practical realizations of discussed positioning possible. The 3D visualization on the screen of a monitor would allow an operator to locate the bucket position. Then with a "push

button" command, supported by an appropriate

algorithm, would allow to automatic motion of

the bucket along prescribed trajectory to dis- charging place.

The positioning and optimal control, have

found also interest in pneumatic and hydraulic

systems applied in machines for construction

industry. Rachkov et al. are considering optimal control of a pneumatic manipulator with

performance index imposed on energy con-

" Institue of Mechanised Construction and Rock Mining, Poland, 02-673 Warsaw, ul.Racjonalizacji 6/8, e-mail: mch@imbigs.org.pl

481
sumption. Shih et al. propose to apply sliding

mode method, in positioning of a pneumatic

cylinder with high speed solenoid valves.

Starting this work, it was essential to assume

an appropriate algorithm based on a rigorous

mathematical back ground for proposed tra- jectory optimization (TO). The first theoretical

results in this field are due Pontryagin [5]. In

his famous mathematical theory of optimal

control the basic concepts of TO are presented.

An application of the Pontryagin principle to a two arm manipulator is the work by Avetisian

et al. [1]. Almost the same time with Pontryagin theory,

emerged the non-linear programming (NLP)

with its basic theorems by Kuhn-Tucker. Its development has been strongly dependent of

digital computers, and then gave very powerful

tool to solve many problems with discretized

variables. In a survey paper by Betts [2] application of NLP and of some other methods re- lated to TO are presented. Recently, Furukawa

[4]proposed a trajectory planning dicretizing

functions entering in the problem, into piecewise constant functions. Roh and Kim [6] are proposing an indirect, applying time FEM

method, combined with NLP. In the proposed

algorithm is taking some elements of the both,

last mentioned papers. The curve, joining initial and final bucket positions, is divided into a given number of equal elements. Unknowns in NLP problem are times needed to travel along

a segment with a constant velocity. The system

of equations and inequalities arising from NLP

problem are solved by successive approximations method. In the first step, some independent variables are assumed, and other solved

from state equations. Next, the remaining

equations are solved from state conditions

equations, giving values for next approximation. Some illustrative examples are presented

at the end of the study.

can rotate with respect to a vertical axis by an

angle (p. The latter motion is due a hydraulic

motor rotating the carriage.

The considered system is then of two degrees

of freedom. Its kinetic energy, a function of

two unknowns angular velocities CC and ^is

equal to:

T =—l{6r +<jr cos a) (1)

where:

1 = 4

' 3

- 1}

The kinetic energy reaches its value from work

V exerted by external forces:

where:

V =MgLsina (2)

From the second order Lagrange equations we

get the following equations of motion:

I\ cx +—<p' sinla \ = Q^-MgLcosa

2 ) (3)

l{^(pcos~ a-(pdsin2a^ =

The system is then transferred in to a set of

four equations of first order each, by assuming

the following variables

\_a,^,d,<p^=[xi,X2,x^,x^] (4)

2. KINEMATICS AND DYNAMICS

Consider a simplified model of an excavator

with a loaded bucket of mass Mi. Simplification consists in assumption that all three members of the excavator attachment constitute one

solid beam of length 2L and mass M2. The

arm, driven by a hydraulic actuator, can rotate with respect to a horizontal axis, by an angle a

(Fig. 3). Additionally the arm, with the bucket,

X2 x^

. __l

X3 -

^

1 o —Ix^ - MgLcos x^ + (5)

X. 2,X^X^tgX, -|- I COS~ X,

482
3. PRE-SHAPED INPUTS FOR MINIMUM TIME CONTROL

Our strategy now is related to minimum time

needed for the bucket to travel from an initial position Oo, (po to a final position Of, (pf .We are then discussing a pre-shaped function for control input, however this is related to an openloop control. Only after finding this function it would be possible to design a close loop sys- tem. The discussed problem is stated as follows:

Find torques Qj and Q2, driving the arm with

respect to the horizontal axis, and with respect

to vertical one, assuring the shortest time for

the bucket to move from the initial to the final position along a given curve. The problem can

be stated in terms of formulate in the form:

Find the minimum time

tj- -tQ—^ mm (6)

to move the bucket from initial point 0(q,(Pq

and initial velocity 6(^=^)^=0, to the final

position (Xj,(Pj, and final velocity

if the motion of the bucket is defined by state equations (5) and torques are Qi and Q2 are bounded as follows:

(7)

--Isin(lx,^)

+MgLcosx^j =g,

, / \ •*'/./+: ~ + X. I COS X. , +

(8)

-/ sin

[ 2x, . ) =

The following algorithm is proposed to solve

the discussed problem.

Stepl. Assume lower bound for /z: /z, =0. In

this case constraints (7) are not fulfilled as torques would be infinitely large.

Step 2. Assume upper bound for h: assuring

that torques found from state equations (8)

fulfil constraints (7).

. h+h

Step 3. Take h=-^ "-

.

2

Step 4. Solve torques Qi and Q2 from state equations (8) and verify (7).

If constraints (7) are fulfilled, substitute for = h. If constraints (7) are nor satisfied, substitute

h, = h. Step 5. If h^—hi>e, where e is assumed

admissible error, go to Step 3.

If h^-hi<e then STOP.

4. EXAMPLES

The equations (5), (6) and (7) represent a nonlinear optimization problem, which can be

solved numerically only. We start with discretization of variables entering into the problem.

The given trajectory between the starting

bucket position , (p^ and its final position

aJ

, (Pj is divided into elements. The traveling time tj: -fg is then divided in jo time

intervals of h= each.

Jo The state equations (5) after discretization take

the following form:

Assume the following data for values entering

into the problem:

M^=440[kg] M. =160[^g]

M =1040 [kg]

I =6500[kg-m-]

L = 1.500 [m]

-2000<<2, <2000[A^-m]

-6000<!22 <6000[A^ m]

For the data specified above, two distinct situations are considered.

483
Case l:The initial bucket position is Xj,o=-^0",

^2.0=0"

Its final position is xjf=60", X2.o=^20"

At both positions, the bucket velocity is equal

to zero. The assumed traveling curve, repre- sented by angles a and ^ are given in Fig. 4

and Fig. 5. The final result, showing relations

between torques Qi, Q2 and time are given in Fig. 6, Fig. 7. Case 2: The initial bucket position is the same

as in Case 1

.

The assumed traveling curve, represented by

angles a and cp are given in Fig. 8 and Fig. 9. The fmal results, showing relation between

torques Qi and Q2 and time are given in Fig.

10 and Fig. 11.

5. CONCLUSIONS

An optimization problem for minimum trav- eling time for an excavator bucket, between

along given trajectory is presented. Numerical

results show significant differences, which

may take place, between torques/time relations

for two different trajectories.

The problem extended to a real excavator with

three degrees of freedom, could be easily implemented into control of LSSD processes in

serial manufactured excavators.

6. ACKNOWLEDGEMENTS

The support of Polish State Committee for

Scientific Research, grant nr 8 T07A 035 20 is gratefully acknowledged.

7. REFERENCES

[l]Avetisian, V.V., Bolotnik, N.N., Cherneusko, F.L." Optimal Programmed Motion

of a Two Arm Manipulator" (in Russian),

Tech. Kibemetika, No.3, 1985

[2] Betts,J.T., "Survey of numerical methods for

trajectory optimization", J. of Guidance

,Control, and Dynamics,Vol.2 l,No2,

March-April, 1998.

[3] Budny E.,Chlosta M.,Gutkowski W. „Experiment on a stable motion of the backhoe

excavator bucket" Proceedings of the 18th ISARC Conference, Krakow, Poland.,2001

[4]Furukawa, T., "Time-Subminimal Trajectory Planning for Discrete Non-Linear

Systems", Eng. Opt. Vol. 34, No3, 2002,

[5] Pontryagin, L.S., Boltyanskii, V,

Gamkrelidze, R. and Mishchenko, E. "The

Mathematical Theory of Optimal Processes", Intersciences, 1962.

[6]Roh, W., Kim, Y. "Trajectory Optimization

for a Multi-Stage Launch Vehicle Using

Time Finite Element and Direct Collocation

Method". Eng. Opt. Vol. 34, No 1, 2002.

[7]Shih, M.C., Ma, M. A., „Position Control

of a Pneumatic Rodless Cylinder Using

Sliding Mode M-D-PWM Control the High

Speed Solenoid Valves", JSME International Journal, Series C. Vol. 41.

No 2., 1998

Fig. 1. Vertical projection of the excavator.

484
:

''

'^ig. 2. Horizontal projection of the excavator

Fig. 3. Dynamic model of the excavator in coordinate system

25

2-

row

1 5-

1

05-

D

C 05 1 1,5 2

tfsl

2,5 3

Fig. 4. Case 1 : cp vs traveling time t

485
1.2

T3

CO

0-5 1 15 2.5 3

1I§] Fig. 5. Case 1: a vs traveling time t

Fig. 6. Case 1: Vertical torque Qi vs traveling time t

Fig. 7. Case 1: Horizontal torque Q2 vs traveling time t

486
I t[s] Fig. 8. Case 2: cp vs traveling time t

X 10'

fi 0- ^ -05 6 -1 5

-2-

oonkiint on Q,

C 2 4 G

tfsl

10

Fig. 9. Case 2: horizontal torque Qi vs traveling time t

1

0«-

oe ^ 0.-

CO3

0-

-0 2

-0 4 >^

-0 6

' 0 2 4 6 8 10 12

t[s] Fig. 10. Case 2: a vs traveling time t

487
£

o"1 f

600O

4000

2O0O

0

2000

-4000 coratabtt on Qi

-6000

1 r 2 <l 6

t[s]

e 10

Fig. 11. Case 2: horizontal torque Q2 vs traveling time t

488
Automated Construction using Contour Crafting - Applications on Earth and Beyond

ABSTRACT: Although automation has advanced in manufacturing, the growth of

automation in construction has been slow. Conventional methods of manufacturing

automation do not lend themselves to construction of large structures with internal

features. This may explain the slow rate of growth in construction automation. Contour

Crafting (CC) is a recent layered fabrication technology that has a great potential in automated construction of whole structures as well as sub-components. Using this process, a single house or a colony of houses, each with possibly a different design, may

be automatically constructed in a single run, imbedded in each house all the conduits for

electrical, plumbing and air-conditioning. Our research also addresses the application of

CC in buildmg habitats on other planets. CC will most probably be one of the very few

feasible approaches for building structures on other planets, such as Moon and Mars,

which are being targeted for human colonization before the end of the new century.

KEYWORDS: Contour Crafting, housing construction, construction on other planets

industry is facing today (Warszawski and

Navon, 1998):

INTRODUCTION

Labor efficiency is alarmingly low,

Accident rate at construction sites is high,

« Work quality is low, and

Control of the construction site is

Since the early years of the twentieth century

automation has grown and prevailed in almost

all production domains other than construction

of civil structures. Implementation of

automation in the construction domain has been

slow due to: a) unsuitability of the available

automated fabrication technologies for large

scale products, b) conventional design

approaches that are not suitable for automation,

c) significantly smaller ratio of production

quantity/type of final products as compared with

other industries, d) limitations in the materials

that could be employed by an automated system,

e) economic unattractiveness of expensive

automated equipment, and f) managerial issues. On the other hand, the following are reported to be serious problems that the construction

Automation of various parts and products has

evolved considerably in the last two centuries

but construction remains largely as a manual

practice. This is because the various

conventional methods of manufacturing

automation do not lend themselves to construction of large structures. A promising

new automation approach is layered fabrication,

generally known as rapid prototyping. Although

several methods of rapid prototyping have been

developed in the last two decades (Pegna, 1 997),

and successful applications of these methods

have been reported in a large variety of domains

workforce is vanishing.

insufficient and difficult, and skilled

489
(including industrial tooling, medical, toy

making, etc.), currently Contour Crafting (CC)

seems to be the only layer fabrication

technology that is uniquely applicable to construction of large structures such as houses

(Khoshnevis, 2000).

CONTOUR CRAFTING

Contour Crafting (CC) is an additive fabrication

technology that uses computer control to exploit

the superior surface-forming capability of

troweling to create smooth and accurate planar

and free-form surfaces (Khoshnevis 1998,

Khoshnevis et al, 2001 -a; Khoshnevis et al, 200 1-b). Some of the important advantages of

CC compared with other layered fabrication

processes are better surface quality, higher

fabrication speed, and a wider choice of

materials.

The key feature of CC is the use of two trowels,

which in effect act as two solid planar surfaces,

to create surfaces on the object being fabricated

that are exceptionally smooth and accurate.

Artists and craftsmen have effectively used

simple tools such as trowels, blades, sculpturing

knives, and putty knives, shown in Figure 1, with one or two planar surfaces for forming

materials in paste form since ancient times.

Their versatility and effectiveness for fabricating

complex free-form as well as planar surfaces is evidenced by ancient ceramic containers and

sculptures with infricate or complex surface

geometries as well as detailed plaster work that have shapes as complicated as flowers, on the

Figure 1. Simple Historical Construction Tools

walls of rooms. Surface shaping knives are used

today for industrial model making (e.g., for building clay models of car bodies). However,

despite the progress in process mechanization

with computer numerical control and robotics,

the method of using these simple but powerful

tools is still manual, and their use is limited to model building and plaster work in construction.

In CC, computer confrol is used to take

advantage of the superior surface forming

capability of froweling to create smooth and

accurate, planar and free-form surfaces. The

layering approach enables the creation of

various surface shapes using fewer different

troweling tools than in traditional plaster

handwork and sculpting. It is a hybrid method

that combines an extrusion process for forming

the object surfaces and a filling process (pouring

or injection) to build the object core. As shown

in Figure 2, the extrusion nozzle has a top and a

side frowel. As the material is extruded, the

fraversal of the trowels creates smooth outer and

top surfaces on the layer. The side trowel can be

deflected to create non-orthogonal surfaces. The

extrusion process builds only the outside edges

(rims) of each layer of the object. After complete

extrusion of each closed section of a given layer,

if needed filler material such as concrete can be

poured to fill the area defined by the extruded

rims.

Material feed barrel ... Side trowel control Bh mechanism

Side

Figure 2. Contour Crafting Process

490
APPLICATION IN CONSTRUCTION

Aplication of CC in building construction is depicted in Figures 3 where a gantry system

carrying the nozzle moves on two parallel lanes

installed at the construction site. A single house

or a colony of houses, each with possibly a

different design, may be automatically

constructed in a single run. Conventional

structures can be built by integrating the CC

machine with a support beam picking and

positioning arm, and adobe structures, such the ones designed by CalEarth (www.calearth.org) and depicted in the Figure 4, may be built

without external support elements using shape

features such as domes and vaults. Following are some interesting aspects of this automated

construction concept:

Design Flexibility: The process allows

architects to design structures with functional

and exotic architectural geometries that are

difficult to realize using the current manual

construction practice.

Multiple Materials: Various materials for outside surfaces and as fillers between surfaces

may be used in CC. Also, multiple materials

that chemically react with one another may be

fed through the CC nozzle system and mixed in the nozzle barrel immediately before deposition.

The quantity of each material may be controlled

by computer and correlated to various regions of

the geometry of the structure being built. This

will make possible the construction of structures

that contain varying amounts of different

compounds m different regions.

Utility Conduits: As shown in Figure 5 utility

conduits may be built into the walls of a building

structure precisely as dictated by the CAD data. Sample sections made with CC and filled with

concrete as shown in Figure 8 demonstrate this possibility.

Paint-Ready Surfaces: The quality of surface

finish in CC is controlled by the trowel surface

and is independent of the size of the nozzle

orifice. Consequently, various additives such as sand, gravel, reinforcement fiber, and other

Figure 3. Construction ofconventional buildings using CC

Figure 4. Construction ofadobe buildings using CC

applicable materials available locally may be

mixed and extruded through the CC nozzle.

Regardless of the choice of materials, the

491
surface quality in CC is such that no further surface preparation would be needed for painting surfaces. Indeed an automated painting

system may be integrated with CC.

ii

Figure 5. Complex Wall Section

Smart Materials: Since deposition in CC is controlled by computer, accurate amounts of

selected construction materials, such as smart

concrete, may be deposited precisely in the

intended locations. This way the electric resistance, for example, of a carbon filled concrete may be accurately set as dictated by the

design. Elements such as strain sensors, floor

and wall heaters can be built into the structure in an integrated and fully automated manner.

Reinforcement: Modular imbedding of steel mesh reinforcement into each layer may be

devised, as shown in Figure 6. The two simple

modular components shown in this figure may

be delivered by an automated feeding system

that deposits and assembles them between the

two rims of each layer built by CC. Concrete

may then be poured between the rims of each

layer to contain the steel mesh. The mesh can

follow the geometry of the structure. Note that in

this configuration the CC nozzle, the steel feeder, and the concrete filler feeder are all on

the same gantry system. Such a system can

create shapes with smooth outer surfaces and

reinforced internal structure automatically and in one setup.

Figure 6. Steel reinforcement modules and progressively

constructed reinforcement mesh

As an alternative to traditional metal

reinforcement, other advanced materials can be

used, such as the fiber reinforced plastics (FRP).

Since the nozzle orifice in CC does not need to be very small, it is possible to feed glass or carbon fiber tows through the CC nozzle to form

continuous reinforcement consolidated with the

matrix materials to be deposited. In the proposed

study, deposition of the FRP reinforcement by a

parallel nozzle built into the CC nozzle assembly

will also be considered. Co-extrusion is further discussed in a later section.

Reinforcement can also be provided using the

post-tensioning system. Accurate ducts can be

generated by the CC process. Similar to posttensioned concrete construction, metal or FRP

wires can be fed through the ducts and then posttensioned to provide reinforcement.

STATE OF DEVELOPMENT AND

FUTURE PLAN

Several CC machines have been developed at use for research on fabrication with various

materials including thermoplastics, thermosets.

492
and various types of ceramics. These machine

include a XYZ gantry system, a nozzle assembly

with three motion control components

(extrusion, rotation, and trowel deflection) and a

six axis coordinated motion control system. The

machine developed for ceramics processing is capable of extruding a wide variety of materials

including clay and concrete. We have conducted extensive experiments to optimize the CC process to produce a variety of

2.5D and 3D parts with square, convex, and

concave features, some filled with concrete, as shown in Figures 7 and 8. The scale has been of

the samples made to date (the hand in Figure 7 is indicative of the scale. We are currently working

on the development of new nozzle assemblies

that are especially designed for construction

application. With the new nozzles we intend to

first fabricate full scale sections of various

building features such as sections of walls with

conduits built in, and supportless roofs and

perform various structural analysis and testing

using a wide variety of candidate materials.

We plan to consider the NIST RoboCrane

system as an alternative to a conventional XYZ

gantry which may encounter problems due to

rail alignment and structural rigidity.

We plan to explore the applicability of the CC

technology for building habitats on the Moon

and Mars, hi the recent years there has been

growing interest in the idea of using these

planets as platforms for solar power generation,

science, industrialization, exploration of our

Solar System and beyond, and for human

colonization, hi particular, the moon has been

suggested as the ideal location for solar power

Figure 7. CC in operation and representative 2.5D and

3D shapes

generation (and subsequent microwave

transmission to earth via satellite relay stations).

A conference on Space Solar Power sponsored

by NASA and NSF (and organized by USC

faculty) included several papers on this topic

( http://robotics.usc.edu/workshops/ssp2000/).

Construction of solar collectors may be possible

by using robots to assemble panels of

photovoltaic cells shipped fi^om earth. However,

the cost of shipping these panels may be

prohibitive, hi fact, the materials needed to manufacture phovoltaic cells are all present in the lunar regolith, so that it may be more

Figure 8. Sections with cavities made with CC andfdled with concrete (largest

dimension in thesefigures is 10")

493
practical to build a "factory", perhaps by

Contour Crafting technology, rather than

shipping panels from earth. Furthermore, once

solar power is available, it should be possible to adapt the current Contour Crafting technology to the lunar and other environments to use this power and in situ resources to build various

forms of infrastructures such as roads and

buildings. The lunar regolith, for example, may

be used as the construction material. Other

researchers have shown that lunar regolith can be sintered using microwave to produce

construction materials such as bricks. We

envision a Contour Crafting system that uses a limited amount of water to form a small batch of

the lunar material into paste form. Once

extruded and deposited in the desirable location,

the water could be extracted and recycled for the next batch of material. Microwave sintering

using solar power can be integrated into the

system and hence progressively cured structures of various complexities could be built.

One of the ultimate goals of the Human

Exploration and Development of Space (HEDS)

program of NASA is colonization, i.e., building

habitats for long term occupancy by humans.

We believe that the Contour Crafting technology

is the ideal method for such construction.

ACKNOWLEDGEMENT: This material is based upon work supported by the National

Science Foundation under Grants No. 9522982

and 9615690, and by a grant from Office of

Naval Research.

REFERENCES

Balaguer C, M. Abderrahim, S. Boudjabeur, P. Aromaa, K. Kahkonen, S. Slavenburg, D.

Seward, T. Bock, R. Wing, & B. Atkin (2002),

"FutureHome: An hitegrated Construction

Automation Approach," IEEE Robotics &

Automation Magazine, pp 55-66.

Khoshnevis, B. (1998), "Innovative rapid

prototyping process makes large sized, smooth

surfaced complex shapes in a wide variety of

materials". Materials Technology, Vol. 13, No.

2, pp. 52-63.

Khoshnevis, B., Russell, R., Kwon, H., &

Bukkapatnam, S. (2001 -a), "Contour Crafting - A Layered Fabrication Technique", Special

Issue of IEEE Robotics and Automation

Magazine, 8:3, pp 2i2)-Al.

Khoshnevis, B., Bukkapatnam, S., Kwon, H., &

Saito, J. (200 1-b), "Experimental Investigation

of Contour Crafting using Ceramics Materials",

Rapid Prototyping J., Vol. 7, No.l, pp. 32-41.

Kulkami, P., and Dutta, D. (1999), "Deposition

Strategies and Resulting Part Stiffriesses in Fused Deposition Modeling", Journal of

Manufacturing Science and Engineering,

ASME, No.l, pp. 93-103, February.

Pegna, J. (1997), "Explorary investigation of

solid freeform construction". Automation in construction. Vol. 5, No. 5, pp. 427-437.

Shrunk, D. Sharpe, B, Cooper, C, and

Thangavelu, M., (1999), The Moon: Resources,

Future Developments, and Colonization, WileyPraxis Series in Space Science and Tech., NY.

Warszawski, A., and Navon, R. (1998)

"Implementation of robotics in buildings: current status and future prospects," Journal of

Construction Engineering and Management,

Vol.124, No.l, pp. 31-41.

Zak, G., Sela, M. N., Park, C. B., and Benhabib,

B. (1999), "Layered-Manufacturing of FiberReinforced Composites", Journal of

Manufacturing Science and Engineering,

ASME, Vol. 121, pp. 448-455, August.

494
Rapid Human-Assisted Creation of Bounding Models for Obstacle Avoidance in

Construction

by

McLaughlin, J. \ Haas, C. ^, Liapi, K. ^ Sreenivasan, S.V. and Kwon, S.

^

ABSTRACT: State-of-the-art construction equipment control technology creates the

opportunity to implement automated and semi-automated object avoidance for improved

safety and efficiency during operation; however, methods for constructing models of local objects or volumes in real-time are required. A practical, interactive method for doing so is described here. The method: (1) exploits a human operator's ability to quickly recognize

significant objects or clusters of objects in a scene, (2) exploits the operator's ability to acquire sparse range point clouds of the objects quickly, and then (3) renders models, such as planes, boxes, and generalized convex hulls, to be displayed graphically as visual feedback

during equipment operation and/or for making proximity calculations in an obstacle detection

system. Experimental results indicate that bounding models can be created rapidly and with

sufficient accuracy for obstacle avoidance with the aid of human intelligence and that humanassisted modeling can be beneficial for real-time construction equipment control.

KEYWORDS: construction automation, workspace modeling, bounding box, convex hull,

obstacle avoidance, laser range finder

1. INTRODUCTION

Recent research indicates that several

applications such as earth moving, heavy lifting,

and material handling can benefit from the use

of graphical models of equipment and

workspace [1], [2], [3], [4]. Real-time

interference checking for obstacle avoidance is also possible using local area graphical models.

Laser range scanners are fast becoming popular

tools for collection of three-dimensional range

data for construction site modeling [5]. These

methods can produce very detailed models of the

scanned scene, which are useful for obtaining

as-built drawings of existing structures, however

the computational and data acquisition time

burdens preclude the methods from being used on site for the real-time decision-making.

Overall, modeling times for these laser range

scanners are on the order of hours or days. The

dynamics of a construction site require modeling

times on the order of seconds or minutes.

The dynamic nature of the

construction environment requires that a real- time local area modeling system be not only

rapid but also capable of handling the changing

and uncertain work environment. The approach

taken in this research relies on a human's

cognitive ability to recognize and classify

' Engineer, Los Alamos National Lab, NM,

jtmclau @sandia.gov

" Professor, Dept. of Civil Engrg., The University of

Texas, Austin, TX 78712, haas@mail.utexas.edu

^ Assist. Professor, Dept. of Civil Engrg., The

University of Texas, Austin, TX 78712,

kliapi@mail.utexas.edu

Assoc. Professor, Dept. of Mech. Engrg., The

University of Texas, Austin, TX 78712,

sv.sreeni@mail.utexas.edu

' Graduate Research Assistant, Dept. of Civil Engrg.

The University of Texas, Austin, TX 78712,

swkwon@mail.utexas.edu

495
objects in the workspace. Much research has

been conducted on automatic object recognition

for model generation, but these methods are neither robust nor efficient enough for real-time

modeling in construction. The goal here is to balance human discernment and efficient range

data acquisition with the proper exploitation of

the computer in the areas of model generation,

interference checking and avoidance control.

2. RAPID WORKSPACE MODELING

The following three sections describe

three modeling methods that were developed

and found to be useful for rapid workspace

modeling for obstacle avoidance: 2.1)

workspace partitioning, 2.2) convex hulls, and

2.3) tight-fitting bounding boxes. It should be

emphasized that all of the above methods were

developed for compliance in a local obstacle

detection system. Since high numbers of objects

in a workspace compounds the effects of slow

distance computations, because pair-wise

comparisons of all manipulator links to all objects must be made continuously, all the

modeling methods described below take

advantage of low numbers of range points for

fast data acquisition and modeling as well as planar surfaces for quick proximity calculations.

2.1 Workspace Partitioning

The first and simplest model described

is a finite plane (or infinitely thin wall) used for partitioning a workspace. Only three points in space are necessary to define a plane. However,

a least-squares approach using more than three

points is very useful to ensure that the plane is placed where the operator had intended it to be. The mathematics implemented are described in

[6]. Floors, walls, and ceilings (i.e., rooms) can be quickly modeled this way by picking just a few points.

2.2 Convex Hulls

In three-dimensional space, the convex

hull of a set of points is the smallest convex volume that contains the points. There are good

reasons for using convex hulls for rapid obstacle

avoidance modeling:

• Convex nature makes the hull inherently

conservative

• Any number of points can be picked,

anywhere

• The resulting hull consists of planar faces

for fast distance computation

The algorithm used in this research is an

incremental algorithm by Barber, Dobkin, and

Huhdanpaa that successively adds a point to the convex hull that was generated by using the

previously processed points [7]. The details of

the algorithm are not discussed here for the sake

of brevity.

2.3 Tight-Fitting Bounding Boxes

Much of the same benefits of convex

hulls also hold for bounding boxes. Like

generalized convex hulls, boxes are convex

polyhedrons. Boxes are useful for acting as a simple outer shell that can hide a more detailed

and precise model underneath. The primary

reason for doing this, relative to obstacle

avoidance, is so that at large distances, where

manipulator movements are small compared to the overall distance from the manipulator base to the object, the manipulator's detection system is not forced to deal with a complex model. As the

manipulator approaches the object, the object's

details become more relevant, so the outer box is removed. This multi-layered modeling approach

is useful in cluttered environments where high

numbers of complex models would stifle an

obstacle detection system. The algorithm

developed to create the tight-fitting bounding

box is described in [6].

3. EXPERIMENTS

Modeling experiments were conducted

to determine the applicability of the modeling

methods above. The actual mechanism used by

the operator for the point collection and the

interface issues therein were not the focus of this research. Rather, the human's ability to recognize the important features in a scene as well as the points needed to define models of

prescribed geometry of those features was the

focus. Twenty test subjects performed the

modeling experiments. The experiments aimed

to satisfy two sub-objectives as well. First, the

496
relation between speed and accuracy was sought.

While speed is obviously the driver, adequate

accuracy is essential to obstacle avoidance and

must not be abandoned for the sake of speed.

Second, test subjects were asked to repeat

certain tasks so that a learning curve could be

observed.

3.1 Experimental Setup

Figure 2 is a picture of the mock scene

that was set up in the construction automation

laboratory for this and other modeling

experiments. Referring to the figure, four

models were used in the experiments described

here:

1) A vertically constrained wall obtained by

picking points on each of the three orange

construction cones in the rear of the scene

2) Three convex hull/tight-fitting bounding box

combination models of the wood box, pipe

rack, and junk pile

The three construction cones were

placed somewhat linearly so that the resulting

vertical wall, as seen in the graphic display

window by the test subjects, would

unambiguously coincide with the cones. The

width of the wall was arbitrarily forced to equal

the distance between the two furthest cones and

the height was arbitrarily set to six feet to be

definitive. The wood box, pipe rack, and junk

pile were each used for the convex hull and

bounding box modeling. These three objects were chosen for their variations in geometry,

complexity, size and the number of points

required to define the convex hull. The junk pile was just a random assortment of pipes, boards,

and a pick ax. Data acquisition was accomplished

using a laser range finder mounted on a two

degree-of-freedom pan and tilt unit (PTU). The

laser was directed via a trackball controller and

the graphical models were displayed on the

computer screen using the Matlab"^"^ GUI

(Figure 3). For details on the retrieval of the

laser distances and pan and tilt angles as well as the forward kinematics of the system see [6].

3.2 Experimental Method

Prior to performing any of the modeling,

each test subject was given some motivation by

explaining the nature of the research project and

rapid world modeling in general. They were

asked to imagine themselves with the task of the

equipment operator who needs to quickly create a graphic model of the workspace scene by

picking various points on the objects using the

PTU-mounted laser range finder. The operator

as visual feedback would then use this graphic

model during the manipulation task as well as by

the obstacle detection system. Next, the test subject was introduced to the data acquisition

system (Figure 3). Once the subject felt comfortable with the system, modeling began.

Each model was displayed graphically using the

Matlab^'^ GUI immediately after it was modeled

so that the experimenter could see the results and the effects of the decisions that were made.

The graphic workspace model was updated with

each new model so that by the end of the last object model, the experimenter had a complete

local graphical workspace model of the scene. The time was recorded for each

modeling exercise and commenced on the

registration of the first distance measurement of

the laser and ended on the registration of the last distance measurement. Qualitative observations were made and recorded as each test subject

used the system. A means of quantifying the

accuracy or conservativeness with which a test subject could model an object or objects by

picking points to create a convex hull was also necessary. This was accomplished by

developing a ray-tracing algorithm. This

algorithm essentially compares the smallest convex volume that could encompass an object

with the convex hull created by the test subject.

It is detailed in [6].

3.3 Scoring Function

In addition to the ray-tracing algorithm,

which enabled quantification of the convex hull modeling accuracy, a means of quantifying the

overall convex hull modeling performance of

each of the test subjects was necessary. Four

related criteria emerged as the most significant

in determining the effectiveness of a convex hull modeler:

1) Accuracy - as discussed above

497
2) Time - total elapsed time acquiring points

per object

3) Efficiency - the number of convex hull points versus the total number of range

points per object

4) Number of Missed Points - the number of

missed points as detected by the ray-tracing

algorithm

A scoring function was formulated that combines these factors and is detailed in [6].

3.4 Experiment Results

Referring to the picture of the

workspace scene in Figure 2, Figure 4 is an example of the completely modeled scene done

by one of the test subjects of the first group.

Notice that each of the objects has been modeled

with the appropriate method (wall - planar fit, wood box/pipe rack/junk pile - convex

hull/bounding box). Modeling the pipe as a cylinder is described in [2], [6] and is not discussed here due to length restrictions. The learning curve was not monotonic

for about half of the subjects. In fact, it was

observed in most of these cases that as the

subject's understanding of the convex hull

modeling approach grew stronger and

enthusiasm for performing the experiment

diminished, the test subject would attempt to model the object with a minimum number of

points. This led to some missed points and

lower accuracies, which despite an improved

time, resulted in a lower score. This is apparent

in Table 1 , which shows the averages for each of

the four metrics and the resulting score for both

attempts of the second group. Notice that the

average number of missed points for the second

attempt at modeling the junk pile was actually

higher than the first attempt, despite an overall

improvement in score. The improvement in score was most dramatic for the pipe rack, which

makes sense since it was modeled first in the

sequence.

The most significant result, as shown in Table 1, is the average deviations of the

experimenter's convex hulls from the control

hulls. These average deviations were roughly an

inch after two attempts for both the pipe rack

and junk pile. Moreover, the median deviations were even smaller than the averages (0.92" for

the pipe rack and 0.80" for the junk pile).

Deviations this small are quite negligible with

respect to large construction manipulators where

the closest allowable distance from the

manipulator to an obstacle would be larger.

4. OBSTACLE AVOIDANCE

SIMULATION

An obstacle avoidance simulation was

performed to demonstrate the applicability of the

modeling methods to obstacle detection for the

purposes of equipment operator feedback and

control. Since construction equipment tends to be large and massive, inertia is an extremely

important factor to be m^onitored for safe

navigation. Thus, the simulation was designed

to monitor manipulator link velocities as well as positions. The simulation consisted of a three- dimensional, three degree-of-freedom robot

traversing over a box. Initial and final joint

angles and a total elapsed time were specified.

The joint paths were then forced to follow

smooth fifth-order curves. The Gilbert, Johnson,

and Keerthi algorithm for computing the

minimum distance between convex polyhedra in three-dimensional space was used as a fast method of proximity calculation [8]. The

velocity was accounted for by running a forward

dynamic sub-simulation at each control time

step (100 Hz) to see where the manipulator

would stop given its current joint angles and

velocities as initial conditions. The actual

positions as well as the projected positions from

the sub-simulation were put into an artificial potential function as feedback output [6]. The

simulation indicated that obstacle avoidance for a construction manipulator instrumented with

feedback control would be feasible in real-time

given the relatively simple models described in

this paper.

5. CONCLUSIONS

Three modeling methods were found to be useful for construction site modeling:

workspace partitioning, convex hulls, and

bounding boxes. The low deviation values

(about one inch), and the low modeling times

(about 2-3 minutes) in Table 1 indicate that a human-guided laser range finder can model

498
construction site objects significantly faster than

current methods and with sufficient accuracy. Li contrast to an autonomous scanner, the human

can quickly recognize the important features of

the scene and then direct the laser accordingly,

decreasing data acquisition time and,

consequently, computational time due to the

lower number of points.

6. REFERENCES

[1] Stentz, A., Bares, J., Singh, S., and Rowe, P., "A Robotic Excavator for Autonomous Truck

Loading," Autonomous Robots, Vol. 7, No. 2,

pp.175-186, September 1999

[2] Cho, Y. (2000), "Human-Assisted Rapid

Workspace Modeling for Construction

Equipment Operations," PhD Dissertation, The

University of Texas at Austin

[3] Kim, Y.S. and Haas, C. (2000) "A Model for Automation of Infrastructure Maintenance using

Representational Forms," Journal of Automation

m Construction, Vol.10, No.l.

[4] LeBlond, D., Owen, F., Gibson, G., Haas, C,

and Traver, A. (1998). "Performance Testing

and Characterization of Advanced Construction

Equipment," ASCE Journal of Construction

Engineering and Management, Vol. 124, No.4,

pp. 289-296.

[5] Cheok, G. S., Lipman, R. R., Witzgall, C,

Bemal, J., and Stone, W. C. (2000), "Field

Demonstration of Laser Scanning for Excavation

Measurement," Automation and Robotics in Construction XVII

[6] McLaughlin, J. T. (2002), "Rapid HumanAssisted Creation of Bounding Models for Obstacle Avoidance in Construction," Masters

Thesis, The University of Texas at Austin

[7] Barber, C, Dobkin, D., Huhdanpaa, H.

(1996), "The Quickhull Algorithm for Convex

Hulls," ACM Transactions on Mathematical

Software, Vol. 22, No. 4, pp. 469-483,

December 1996

[8] Gilbert, E. G., Johnson, D. W., Keerthi, S. S. (1998), "A Fast Procedure for Computing the

Distance between Complex Objects in ThreeDimensional Space," IEEE Journal of Robotics

and Automation, Vol. 4, No. 2

ACKNOWLEDGEMENTS

This paper is based on the research

funded by the National Science Foundation

(Grant#: CMS-0000137) and the National

Institute Standard and Technology (Project

NBR: NA1341-02-W-0742). The authors

gratefully acknowledge their financial support

and encouragement throughout this study.. The

authors gratefully acknowledge their financial

support and encouragement throughout this study.

SWRT

SlattvfechneCpersticn

Figure 1 . Overall Construction Equipment Operation

Modeling Process

Figure 2. The Scene for Experimental Modelmg

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Figure 3. Laser, PTU, Trackball Control, and Data Acquisition Software Interface

World Frame

Figure 4. Graphic Model of Workspace Scene (dimensions are inches)

Table 1 . Average Values for the First and Second Attempt at Modeling the Pipe Rack and Junk Pile Pipe Rack Junk Pile

Averages 1st 2nd 1st 2nd

Deviation (in) 2.42 1.16 1.12 0.97

Time (min) 5:51 2:33 3:30 2:17

# Range Points 26.3 14.6 16.6 13.1

# Hull Points 16.0 11.9 13.3 11.6

H/R Ratio 0.68 0.86 0.86 0.90

# Misses 1.0 0.1 0.4 0.7

Score 39 76 72 76

500
COMPUTER TECHNOLOGIES IN CONSTRUCTION ROBOTS CONTROL

Thomas Bock*, Dimitry Parshin**, Rudolf Neudorf**, Alexej Bulgakow*

^Technical University Munich, bulsakow@bri.arch.tu-muencheii.de ** Rostov State Building University, RUSSIA, pragma_plus@mail.ru

Abstract: Construction is of great interest for applying practical and theoretical results in the

field of robotics and computer technologies. The paper presents the composition and special features of kinematics and dynamic models of construction robots, control algorithms

synthesis in terms of synergetic approach, planning of robot's movements based on computer

techniques. Recommendations on computer technologies application, construction robots

control, control programmes development and operators teaching are given.

Keywords: automated control system, construction, computer technologies, kinematics,

dynamic, model, robot.

1. INTRODUCTION

Construction robotics is of great interest for practical

application of the results while performing

automation of mounting, finishing, placement of

concrete and other kinds of work. However robots

application in conditions of construction sites is connected with technological, operational and some

other characteristic properties. Successfijl solution of

the tasks dealing with construction operations

robotization requires not only the development of

special-purpose manipulators but the application of new approaches while solving such problems as

control, management and preparation of control programs. In connection with the mentioned above we suggest to use computer technologies in manipulation system control, trajectory path

planning, developing routes for handhng the parts, developing control programs in the teaching mode,

robots analytic programming, robots task-level programming and operators teaching for construction robots taking into account their specific

features.

2. MATHEMATICAL MODELS FOR ROBOTS

In the basis of a computer control technology lie mathematical techniques representing the set of

models of different levels: from the models of

decision making to particular models for carrying out controlled movements of some degrees of

fi-eedom. Control algorithms are constructed on the

basis of the obtained kinematics and dynamic

models. Kinematic models include equations

determining position and speeds of the system

elements and specifying transport, installation, transfer and orienting movements of construction

robots. The position of coordinate systems while

developing kinematic model must ensure

conventional representation of mechanisms location and simplify the process of coordinates

transformation. For self-mobile construction robots

the basic coordinate system X,„YmZm should be

connected with the manipulator rotation axis and the

axis X„ is directed along the self-propelled truck,

(fig.l). For the rotational degrees of freedom, axes

of which are perpendicular to the Unks (2" , 4 ,6

pairs) it is convenient to combine axes X, with

rotation axes and axes Z to be led along the link. For

the translational degree of freedom and the rotational one with the location of the axis along the hnk it is necessary to direct axes Zj along the axes of

movement and axes X, to combine with axes of

the previous degrees of freedom. Direction of

coordinate system axes X/F/Z/ of a gripper or a technological tool is defined by a robot. For mounting robots it is convenient to direct axis Z,

501
along the end link and axis X, - along the traverse of

the gripping device. In finishing robots we

recommend to direct axis K, along the end link and

axis Z, to the plane of the mechanism. In this case it

is expedient to construct kinematics model on the

basis of position Tr and orientation Tqr. Using these matrices we candefine the position and orientation of

the tool: T -T^ T , and on the basis of this

p F or matrix we get the system of equations to determine

coordinates of point P in the coordinate system of

the robot X„,Y„Zm:

(p^s(p^ + (/j + l^c(p^ )s(p^s{(p. +(p^) + (S^s(p._ +

Yp = s(PiS(p,s(P(^ + c(p^c((p, + (P4)c

(p^s(p^+{l^+l^s(p^)c(p^s{(p,+(p^) + {Sj,s(p, +

+ l^s{(p._+(p^))c(p^;

Zp=l^+ S^ccp, + • c{(p^^ + <?>4 ) + ih + kc(p(, )

where C(p. = cos((p, ) , S(p. = sin((p;) •

In general manipulator kinematics is represented as a system of equations being the functions of

generalized coordinates:

^p

f^P

To solve inverse kinematics problems we

recommend to use approximate relations based on

iteration methods. More exact values of generalized

coordinate for a construction robot ^<'^> on k-ih step

of the iteration cycle are determined through

approximate values onA:-l step:

where -^[l ^ partial derivative of

transformation matrix T, along the y-th generalized

coordinate.

When controlling the robot's movement the data about the speeds of the grip motions and the point defining the transport path of the movement

are necessary. At the given speeds of the manipulator links motions the projections of the tool linear speed are defined by the equations:

To simpUfy the development of kinematic models we suggest to use the method structure decomposition, the essence of which is in breaking

the architecture into elementary type structures. This

allows to have transformation matrices for each type

module that connect its input and output values. One of the effective methods of modelUng dynamic

characteristics of robot's effectors is dynamic models

construction. According to them we select control algorithms, form optimal laws of control and

determine control forces in degrees of freedom.

While developing mathematical model for a robot

there appears a question about the choice of

mathematical device. For construction robots it is convenient to apply motion equations in Lagrangian

form. In this case manipulator dynamics is described

by a set of interrelated non-linear differential second-order equations of the form:

' 6 6 5 6

;=1 /=1 /=1 j=i+l

< ;

6 6 5 6 ^

i=\ 1=1 /=1 j=i+\

where ai.j(nij,lj , q/)- functions characterizing

centropetal forces; bf.i{m-Jj,qj) and

C,.jj(mjjj,qj)- functions depending on

generalized coordinates and characterizing Coriolis and centrifugal forces; G, )

" potential

forces. Summary moments acting in degrees of freedom are generally determined by the sum Mf =M^f' -M'/' -Mj'K

where M^* —moments developed by a drive;

Mj^^ - movements of friction degrees of freedom;

M,**'' - movements of external forces. The moment

of a drive M^^ ' are defined by the moment of a

502
motor M,',f' < efficiency Tj'^' and transmission ratio of

the drive:

dt where J^^^ — moment of inertia of movable parts

connected with the motor shaft; 0^. - angular speed.

The load moment Mj'^^ for each drive is defined

by the weight of the working tool and depends on

links position:

A dynamic model developed on the basis of the described equations is added up by the control equations:

ja.dM;^^^,,, ^ _ , m m Do e k

where f^''^ — time constant of a motor anchor m

chain; ki^\k''^^ — coefficients of transformation

and self-induction.

3. ROBOTS CONTROL ALGORITHMS

They include the set of algorithms of motions

planning and formation of controls for manipulator

degrees of freedom. In performing this the parameters correction of the manipulator motions is carried out discretely in time interval A(t) and the planed trajectory and he laws of changing

generahzed coordinates provide continuity of the functions, their first and second derivatives. The new

values of the motion parameters are generated from

he periods of 1-10 ms. An effective principle of

developing control algorithms for robots with

complex dynamics is a synergetic approach. It is based on separation of motions in complex dynamic

systems and approximation of the main properties of

the controlled object with a simplified mathematical

model. Apphcation of these models with significant

non-linearity of the object is hmited by states space and time interval. At each interval linearization is permitted and asymptotically stable movement of

the system is provided. Such an interval- approximation control possesses robustness as at each control interval adaptation to the properties of

the object changing in time and space is ensured. To

perform interval-approximation control a dynamic

model of a robot as a controlled object is represented

by equations of the form

x{t) = F{t,l{t),u{t)),

where F is an allowing approximation vector- function; argument of which are vectors of state

x{t) and control actions U (t) . At about point

X-Q and UjQ of an integrated space of state and

input actions we find an approximating dependence

where Xj^ an evaluation vector of the object state with an approximating model in the i-th area of state under consideration. For the interval at the moment we determine x, - a vicinity of initial conditions of a

state vector = x{tj ) and v, - a vicinity of

current value of a control vector m,q=w^, (r,),

when evaluation error of its own and forced

variations of state X with of approximation model

Xi,(t) = F,^(i,x.Jt),u{t))

does not exceed some admissible value

||e.(0|| = ||l,«(0-I(0||<£,„-

This allows to find the values of maximal admissible

time interval T,E[?-,f-^j] at which the legitimacy of approximation is provided. In this case

at X < X and at exact estimation of the object

initial state the control law is calculated according to an approximating model: u(x, t) ~ u(i, J-^ ,t)

Control at an attributed interval x, providing stable system movement with the given quaUty is performed in terms of the methods of optimal model

control or methods of the system synthesis according

to the desired characteristics. Synthesized control laws u(i,x-^,t) at the whole temporal control range represent a piece function implementing the algorithm for forming control law with variable parameters. The apphcation of synergetic approach

to the motion control of construction robots made it possible to obtain algorithms providing the solution of the control tasks with minimum of calculation

operations. This allows to cut down the time for formulating the next vector of control actions, to reduce the interval of renewing control signals and

to increase the accuracy of control. The algorithms

applied make it possible to form control action according to the given differential equations

describing the object to be controlled and the standard transitional processes. The process of control algorithms development and

control program preparation for construction robots

is greatly simplified when computer technology is used. Applying methods of mathematical modeUng,

computer graphics we can perform the search for optimal trajectories of movements, carry out simulation of the processes of tool motion, provide

503
division of trajectories into sections and form data base of ponts of control. The robot motions planning

is based on non linear control algorithms and carried out with the account of limitations both for the

trajectory itself and the manipulator Unks

displacement. Correction of movements parameters

is carried out discretely at time interval A(/), and the planned trajectory provides continuity of the function. Values of movement parameters are generated at a period of 1-5 ms. As a result of robot motions planning the obtained laws of changing

internal coordinates [nT] are then transformed

into control actions fj ^ [nT] providing motion

stability relative to the chosen programmed

trajectory. Incorporation of the events processor into the system makes it possible to synchronize the robot's operation with other technological

equipment that is especially important for construction-mounting operations.

4. PARAMETERS, CONTROL, PROGRAMS

PREPARATION

Construction-mounting operations require constant

control of the equipment condition and the technological process parameters. The application of

computer technologies allows to obtain information

from the sensors about environment situations, means of control concerning the objects positions, to process input data, to display the data by the operator's request at the pre-set period. Visual

control of technological operations performance in

real time allows to simplify to the utmost the operator's work. Construction - mounting robots should have programs to control the main

parameters of movements: the position of each

degree of freedom, speed of Unks movement, gripper

(tool) coordinates and speeds of its motion.

According to the data read out of position sensors and tachometer generators of the manipulator

degrees of freedom tool actual coordinates and its orientation are calculated as well as a vector of tool motions speeds. The calculations are fulfilled on the basis of the algorithms of kinematic model.

Meanwhile by operator's request positioning errors can be formed and displayed graphically in the function of time or trajectory.

An important trend in computer technologies

appUcation in construction robotics is preparation of

control programs which can be carried out outside

the construction site on the model of a robot or robotic system. The application of information

technologies makes it possible to create a robot's

virtual model and a cross-system for preparing and

testing control programs and their translation into the codes of the robot control system. A virtual robot

which is displayed in 3-D graphics and moves in real time makes up the basis of such system for developing programs. The developed algorithms and

models are put into the basis of the integrated system

including the subsystem of 3-D modeling, the system of programming and separate modules for carrying out research and educational tasks. The

package of algorithms and programs allows to calculate automatically the positions of all robot's joints participating in performing the pre-set

movements, to form control actions and to test their performance on the robot's model. In the process of

fulfllhng the movements the violation of the introduced limitations for the gripper motion may

occur. The characteristic feature of the program

developments system is the opportunity of testing control algorithms in different modes with the convenience of imitating the processes of collecting data and control. The described models and

algorithms make up the basis of an integrated system

of software for civil engineering works. It has a multiwindow interface with functional, graphic and

table windows, which can be adjusted to the given

kinematic structure. Incorporation of 3-D objects

info the user interface makes it possible to simulate

visually the operations performed by the robot, to teach the operations.

5. CONCLUSION

The presented materiatl is the result of developments

in the field of automation and robotization of civil engineering works. On the basis of the described

approaches kinematic and dynamic models

construction-mounting and finishing robots have

been developed, control algorithms have been

synthesized according to synergetic approach to movements control. A software integrated system is of practical interest, it allows to control parameters,

visualize robot's work, task in a graphical or table form of movement trajectories, it also provides

preparation of programs and operators teaching.

6. REFERENCES

1 .V. Zagorodnjuc, D.Parchin, The Construction Robotica (Mockow,1990).

504
EQUIPMENT OPERATOR TRAINING IN THE AGE OF

INTERNET!

Leonhard E. Bernold, Associate Professor

Justin Lloyd, RA

Mladen Vouk, Professor

Construction Automation & Robotics Laboratory, Nortti Carolina State University,

Raleigti, NC, 27606

Abstract: Considering the established needs for operator training in the construction

industry and vastly improved data communication using Intemet2, the feasibihty of an

effective Internet based training system for backhoe operators is increasing. This paper

presents ongoing work on a prototype system designed with the idea that eventually any

electronically controlled backhoe can be adapted and connected to the Internet. Experimental tests have shown that 3-D, real time video in combination with force and

sound feedback provide a data-rich control environment for the trainee. This paper also discusses how the availabiUty of force and spatial position data can be used for running an onhne training program that provides the user with a series of structured tutorials and

practice sessions. System features of a Virtual Coach might include the haptic feedback

featured in the prototype system, depending on its demonstrated relevance to training

efficacy, as well as digitized verbal information, including instructions, commands and

real-time advice.

Keywords: training, skill assessment, information technology, motion control, construction

equipment

Introduction

Efficient on-the-job operator training is not only costly but is often not possible, requiring

specialized equipment and an on-the-job

trainer. However, only appropriate and

extensive training enables operators to control

large equipment safely and efficiently. Similar

to other industries, construction tries to take

advantage of computer simulators and virtual

reality as training vehicles. An apparent

problem with such tools is the lack of realism,

which is very costly to create. In addition,

research has shown that the key to acquiring

the necessary motor skills to control complex

systems, such as a backhoe excavator, is hands-on and coached training. (CuqlockKnoppetal., 1991)

The most common task of backhoe operators is to cut soil with a bucket and dump it on to a

pile or into a truck. Skilled operators

dexterously control the arm and bucket using

two joysticks, as shown in Fig. 1, by

monitoring the backhoe motion and the state of

the process. The skill itself, however, is difficult to assess and even skilled operators

can't describe their own "skillfulness".

The advent of Intemet2 opens the opportunity

to revolutionize training of large equipment

operators. The large bandwidth and high-speed

data transfer allows large amounts of data to be

"pumped" through the Internet. In particular,

live video can visually "connect" an Internet user with a remote site in near real time. In order to study the effectiveness of a distance

training & learning concept, an Internet-Based

Backhoe Operator Trainer (IBOT) was built and tested using the Internet as well as Internet!.

What is Skill?

How does one assess the skill of a backhoe

operator today? The commonly heard answer

is: "By watching him operate the equipment or measuring the time it takes him to load a

truck." It becomes apparent that these skill measures are rather crude considering some common definitions of skill or skilled performance.

Paul Fitts (1964), a prominent motor skill investigator before his untimely death, listed

505
four critical characteristics of skill: 1) goal

directed, 2) exhibiting highly integrated and

organized behavior, 3) acquired through

practice and training, and 4) applied with ease.

Fitts' definition of skill will be used as the

basis for establishing performance measures

that could be used to differentiate between an

excellent and a not-so-perfect backhoe

operator.

Measures of Operator Performance

Sage (1984) provides a definition of skilled

performance that can be utilized to assess a backhoe operator. He characterizes a skilled

performer as one who "can produce an output

of high quality (such as fast or accurate) with a good deal of consistency. Skilled performance

is also characterized by an appearance of ease, a smoothness of movement, an anticipation of

variations in the stimulus situation before they

arrive, and an ability to cope with these and

other disturbances without disrupting the

performance. Indeed, increasing skill involves

a widening of the range of possible

disturbances that can be coped with without

disturbing the performance." Considering

Sage's elaboration, we can establish the

following list of measures for performance

measurement: 1) quality of output, 2)

consistency of operation, 3) smoothness of

bucket motion, 4) proactive thinking, 5)

adaptability to changing environments, and 6)

capability for skill improvement. It is easy to recognize that these six traits are really based on earlier work by Fitts, who already had

established a useful framework for skill acquisition earlier.

An Internet-Based Backhoe Operator

Trainer

An Internet-based training system needs to provide the trainee a means to operate

equipment without being situated right next to

it, thus losing the ability to use his inherent senses as feedback channels. Figure 2 shows

the architecture of the first prototype EBOT

developed by the Construction Automation &

Robotics Laboratory (CARL). The main

components of the IBOT consist of: a)

computer-integrated-backhoe (CIB), b) one PC

running video communication software c) one computer for digital data communication, and

d) human-computer interface at a remote

location with joystick, audio, video, and data

display. NetMeeting was found convenient for

demonstrations but, because it is already old

technology, is not sufficiently dependable to allow experimental tests with IBOT. A

commercial force-feedback video game

joystick is used to control the excavator. The

remote control software utilized a combination

of Windows sockets, Windows GUI with the

WIN32 API and multi-threaded programming.

Here, a client and a server program work

together to convert un-calibrated joystick

signals originating from any computer with a Windows 98 operating system and standard

joystick port into a calibrated, useful signal

output from the analog digital (A/D)

conversion board in the control computer. The

client and server programs both engage

independently operating communication

threads which run in continuous loops, where

the server thread echoes all data received from

the client to maintain synchronization between

the programs, as well as to provide a channel

for feedback data, if necessary.

Figure 3 a) shows the programmable game

joystick with which the entire excavator can be

operated, while Figure 3 b) presents a view of

the operator control seat where the operator is replaced by a video camera. Two large soil boxes serve as mobile containers for digging

and dumping. Overhead cranes are able to pick them up and move them if desired. This

allows the rapid change from one type of soil to another.

Electronic Skill Measurement

The modeling of the joystick motions required

to move an excavator bucket through soil is a complicated problem, in as much as there exist

many ways of creating the same path. In the same vein, the forces that have to be created to cut through the soil not only depend on the

strength and density of the soil, but also on the

digging motion, which includes factors like velocity, acceleration and smoothness of the

bucket motion. Thus, it seems reasonable to expect that the forces that are created during

the operation could be used as one important measure of operator skill.

The learning of motor skills is special in that it concerns itself with the process that underlies

movement. Of critical importance is the fact

506
that motor skills cannot be measured directly,

but only inferred by observing behavior or performance. However, using performance

alone as the measure of skill is not sufficient

since other factors such as motivation, fatigue,

boredom, noise, and temperature also impact

performance. Anybody who has worked with

equipment operators can easily see that the

speed of skill acquisition depends upon a

variety of conditions, with practice being the

most important of them. In order to eliminate

the extraneous effects as much as possible,

trainees were assessed continuously, an act which provided data that could be plotted. The

resulting graphs are called learning curves or performance curves.

Preliminary experiments, where two test persons were asked to perform an identical

digging task, have shown that there is a

definite relationship between skill and sensory

feedback from the computer integrated

backhoe. Figure 4 presents the hypothesis that smoothness of motion, which is related to skill, can be translated into smoothness of force. As

shown, one should expect that a highly skilled

operator creates a fairly consistent force

pattern along the entire task while a poorly

skilled operator produces spikes.

In order to test the basic hypothesis, a set of

comparative experiments was executed. Two

distinctively different operators, an "Expert"

(E) and an "Apprentice" (A), were given the

task to dig in the soil box under similar

conditions.

Identification of Primary Skill Indicators

The tests conducted were based on the digging

scheme presented in Figure 4. In a first effort,

the research team attempted to verify the

assertion that there are, in fact, unique force

characteristics in each of the three cylinders: 1) boom, 2) stick, and 3) bucket. Fig. 5 presents

two force data sets collected during one dig

executed by two test subjects.

Force Pattern Reviewing the graphs, several differences can

be easily identified. For example E is filling

the bucket in approx. 11 seconds while A

needs almost 18 seconds to do the same. The

above hypothesis seems to hold by the force

data. E's maximum stick force during digging

is 2,700 kN, while A needs 7,600 kN to move

the stick through the soil. In addition, the

"Expert", exhibits a much smoother and more

uniform force distribution when compared to the "Apprentice."

Spatial Pattern A second set of sensory data output that was

analyzed resulted from the three angle

encoders mounted on the three joints of the arm. Figure 6 depicts the result of a kinematic

transformation, according to the DenavitHartenberg notation, converting the angles into

Cartesian coordinates representing the path of

the bucket.

While the path coordinates generated by E did

fit a cubic polynomial path function, A's path

shape only fits a cubic polynomial with a

rather large deviation error. This correlates

well with the stick-force data, since it also

showed a comparatively "rough" pattern.

Coached Backhoe Training

The important first job of a coach is to instill in the trainee's memory an appropriate idea of

how to execute a task. The two most

commonly used techniques are verbal

instruction and demonstration. A good coach

also motivates and reinforces learned skills. Furthermore, coached training should be

adaptive, in that the demands of the training

environment and the complexity of the task

"grows" with the skill level of the trainee. Thus, a coached training program is individualized and constantly monitored by the

coach to assess progress. This personalized

"looking over the shoulder" method of training

is hardly possible on an actual excavator. A

virtual trainer that is able to read and interpret

feedback data representing the performance of

the trainee may serve the role of an actual

coach.

The module of a telepresence excavator trainer

may be modeled as a closed-loop system. It is able to read measures representing the

trainee's performance as input to dependent

output coefficients, such as the difficulty of the

training task. Figure 7 presents the framework

of such a closed-loop training system for backhoe operators.

507
Towards a Virtual Coach

Considering the established needs for operator

training in the construction industry and the

versatile control and performance evaluation

characteristics of the IBOT, the development

of a "Virtual Coach" training system for

backhoe operators using the IBOT system is a

natural goal. System features of the Virtual

Coach might include the haptic feedback

featured in the IBOT, depending on its demonstrated relevance to training efficacy, as well as digitized verbal information, including

instructions, commands and real-time advice.

The primary advantage of a teleoperation

training system over a virtual reality training

system is the guaranteed realism it provides.

Complex and unpredictable processes, instead

of being mathematically modeled and

simplified, actually occur and present the

trainee with stimuli commensurate with real- world equipment operation. Indeed, this type

of "virtual" instruction would provide the

trainee with an experience nearly identical to an on-site training program with a human

instructor, saving the money and danger of

such training practices and simultaneously

providing more extensive performance

evaluation capabilities.

Studies indicate the reliable transfer of skills acquired through virtual training or telepresence to actual on-the-job tasks (Rose et

al., 2000), provided a high similarity between

the virtual and real environments. Employing

real-time, high-resolution stereoscopic visual

feedback, audio feedback, and joystick control,

the IBOT system generates the same intrinsic feedback provided by an on-site backhoe

training session, and creates a teleprescence

experience practically identical to an actual

backhoe system in operation. Thus, provided

an appropriate program design, the IBOT

system would undoubtedly enable the cost- effective remote training of backhoe operators.

Because of the range of extra evaluative tools and feedback features the IBOT offers, the

integration of automated training and Virtual

Coaching aspects into the IBOT system and

software presents a complex design problem,

requiring particular knowledge in the subjects

of motor learning, motor control and backhoe

operator skill. System features as

straightforward as performance feedback, user

instructions and feedback augmentation would

require careful planning and design, taking into

account the current knowledge base on the

efficacy of different types of supplemental aid

to motor learning. Motor learning research

(Cuqlock-Knopp et al., 1991) suggests a number of subtle but consistent dependencies

of long-term motor skill retention on knowledge of results (KR) scheduling,

performance feedback structure, augmented

feedback usage, task instructions and

attentional focus. The Virtual Coach system

will enable precise software control over each

of these aspects of motor skill instruction,

providing a means to not only train operators,

but to actually evaluate and refine the

techniques of the trainee

Summary

Retrofitting existing equipment with

ruggedized sensors and data-storage devices

has enabled the implementation of various

schemes for improving equipment life and

performance. By installing computerintegrated controls, a path for operating them

tele-robotically has been created. This paper

discusses still another opportunity for utilizing

such an electronic infrastructure, namely

electronic skill assessment and training. One

measure of good operator performance is the

smoothness of motion. Using experimental

data it is shown that there are, in fact,

distinctive differences between the forcepattern generated by an "Expert" and an

"Apprentice" backhoe operator. The extensive

amount of data that was collected using force sensors and angle-encoders allowed the

identification of unique features not only of

forces but of path and energy consumption as well. It is argued that it is possible to develop

a feature-based "pattern-language" enabling

the automatic characterization of individual

skill levels.

On-the job training with expensive equipment

is not an economical approach to training,

since it increases the chances of damage to the

equipment, possible accidents, and a

drastically reduced production. This paper

offers a new approach to the dilemma of cost

effective hands-on training. The discussed

alternative takes advantage of the Internet as a communication tool that allows a trainee to

508
practice with a stationary backhoe from his home. Named the Internet-Based Backhoe

Operator Trainer (IBOT), the system has been

tested using the Internet as well as Intemet2.

References

Cuqlock-Knopp, V.G., Wilkins, C.A. and

Torgerson, W.S. (1991). "Multiple Cue

Probability Learning and the Design of

Information Displays for Multiple Tasks." In D.L. Damos, Ed. Multiple-Task Performance,

pp. 139-152, Taylor&Francis, London

Fitts, P.M. (1964). "Perceptual-Motor Skill Learning." In A. W. Melton, Ed. Categories of

Human Learning, pp. 243-285, Academic

Press, New York, NY.

Rose, F; Attree, E.A.; Brooks, B.M. (2000)

"Training in Virtual Environments: Transfer to Real World Tasks and Equivalence to Real

Task Training." Ergonomics, v 43 no 4, Apr p. 494-511.

Sage, G. H. (1984). "Motor Learning and

Control: A Neuropsychological Approach."

Wm. Brown Publishers, Dubuque, Iowa.

Fig 1 . Computer Integrated Backhoe at CARL

a) Motion Control b) Visual Feedback (2D-3D)

Fig 3. Communication Hardware

Fig 4. Comparison of Hypothetical Forces

Force In Be jrce in Boom Cylinder

2000

-1000

•€000

-8000

10000

SOOO

0

-5000

I

4000

Boom

\ f

stick

2000

1000

Bucki t

8 10 12 14 Expert Apprentice

Fig 5. Measured Force Patterns

Real Digging Path Approximate Digging Path

y=-0.6930'x'+3.0766-x^-2.6279'x-i-a6122

Fig 6. Digging Path of "Apprentice" Operator

509
VIRTUAL COACH

> Skill Assessment

Data &

Information

1—

Environment

Equipment

Feedback

Channels

Soil/Tool

Interaction _ Coaching ~ Activity

Fig 7. Layout of a Coached Training System

Audio

Fig 2. Schematic of Intemet-Based-OperatorTraining System

510
Terrain Aided Localization of Autonomous Vehicles^

Raj Madhavan

Intelligent Systems Division

National Institute of Standard and Technology

Gaithersburg, MD 20899-8230, U.S.A.

E-mail: raj.madhavan@nist.gov, Fax: (301) 990-9688.

Abstract— This paper describes the development of a

terrain-added localization fremework for autonomous land ve- hicles operating at high speeds in unstructured, expansive and

harsh environments. The localization framework developed is sufficiently generic to be used on a variety of other autonomous

land vehicles and is demonstrated by its implementation using

field data collected from two different trials on two different vehicles. The resuits demonstrate the robustness of the proposed

localization algorithms in producing reliable and accurate position estimates for autonomous vehicles operating in a variety of unstructured domains. Keywords— Outdoor Localization, Map Building, Iterative Closest Point, Extended Kalman Filter, Entropy, Scale Space.

I. Introduction

THE research addressed in this paper is concerned

with the theoretical development and practical

implementation of reliable and robust localization algorithms for autonomous land vehicles operating at high

speeds in unstructured, expansive and harsh environments [1]. Localization is the ability of a vehicle to de- termine its position and orientation within an operating environment at any given time. The need for such a

localization system is motivated by the requirement of developing autonomous vehicles in applications such as mining, agriculture, cargo handling and construction. The main drivers in these applications are safety, ef- ficiency and productivity. The approach taken to the

localization problem in this paper guarantees that the

safety and reliability requirements imposed by such applications are achieved. The approach also aims to minimize the engineering or modification of the envi- ronment, such as adding artificial landmarks or other

infrastructure, a key driver in the practical implementation of a localization algorithm [2]. In pursuit of these objectives, this paper develops a unified localization framework that uses measure- ments from both artificial and natural landmarks, combined with dead-reckoning sensors, to deliver reliable vehicle position estimates. The proposed localization framework is sufficiently generic to be used on a variety of other autonomous land vehicle systems. This

^The research reported in this paper was performed at the Australian Centre for Field Rxjbotics, The University of Sydney,

Sydney, Australia. The author would like to acknowledge the

financial assistance provided towards his doctoral research by

the Centre for Mining Technology and Equipment, Brisbane,

Australia.

is demonstrated by its implementation using field data

collected from two different trials on two different vehicles. The first trial was carried out on a four-wheel

drive vehicle in an underground mine tunnel. The sec- ond trial was conducted on a Load-Haul-Dump (LHD)

truck in a test tunnel constructed to emulate an underground mine. The estimates of the proposed localiza- tion algorithms are compared to the ground truth pro- vided by an artificial landmark-based localization al- gorithm that uses bearing measurements from a laser. The paper is organized as follows: Section II de- velops an Iterative Closest Point - Extended Kalman

Filter (ICP-EKF) algorithm - a map-based iconic algorithm that utilizes measurements from a scanning laser rangefinder to achieve localization. The ICP-EKF al- gorithm entails the development of a map-building al- gorithm. The development and implementation of an

entropy-based metric to evaluate the information content of measurements and how this metric facilitates the augmentation of landmarks to the ICP-EKF al- gorithm guaranteeing reliable and robust localization

is the subject of Section III. Section IV details the

development and adaptation of a view- invariant Curvature Scale Space (CSS) landmark extraction algorithm. The algorithm is sufficiently robust to sensor

noise and is capable of reliably detecting and extracting landmarks that are naturally present in the envi- ronment from laser rangefinder scans. The integration of the information metric, the CSS and the ICP-EKF

algorithms to arrive at a minimal infrastructure local- ization framework is detailed in Section V. Finally,

Section VI summarizes the key results.

II. Map-Based Iconic Localization

A bearing-only laser was mounted on the roof of the

vehicles (for both the trials to be described in the fol- lowing sections) so that it could detect strategically

placed artificial landmarks (reflective stripes) in the

trial environment. The exact position of these land- marks were made available from surveying using a digital theodolite. When the laser mounted on the vehicle moves through the environment, it detects the presence of these landmarks. Thus as the vehicle tra- verses through the environment, a sequence of bearing

measurements to a number of fixed and known loca511
tions are made. Since the locations of these reflectors are known to the vehicle navigation system, the loca- tion of the vehicle can be computed from the bearing

measurements made. Utilizing bearing measurements

from a bearing-onlj' laser in combination with deadreckoning sensors (velocity and steering encoders and

rate of change of orientation information from an in- ertial measurement unit), an EKF was employed to obtain ground truth. The pose estimates obtained using the above artificial landmark algorithm were used to decouple the problems of map-building and map-aided pose estimation. Although it may not be appropriate to engineer

the environment with artificial landmarks, it is possible to use a slow moving vehicle and a small number of landmarks to build a sufficiently accurate initial map. The reflective stripes required for the artificial landmark algorithm can be removed and the generated

map can be used for vehicle localization. When the vehicle is stationary, it is easy to construct the vertices of a polyline that fit the data. When the vehicle starts moving, new range data obtained from the sensor needs

to be integrated into the polyline map. Towards this, an incremental algorithm was developed for obtaining

the optimal location of the vertices of the polyline in view of the new incoming data. Clearly as the vehicle moves, there will be observations that correspond to parts of the tunnel walls that were not seen before and

therefore are not represented by the existing polyline.

These observations were collected to expand the map

by attaching line segments to either end of the polyline

as the vehicle moves gradually along the tunnel. The

proposed map-building algorithm is specific to this application and is not intended for high level tasks such

as path planning where the required accuracy of the map would be higher. The polyline representation was

chosen because of its simplicity. The curved surfaces

of the environment can be represented using splines or a combination of line segments and arcs except for the fact that the additional complexity in such repre- sentations is not required for this application. As will be demonstrated, the maps obtained by the proposed

map-building algorithm for both the 4WD vehicle and

the LHD truck are adequate for localization. Once the map is available, the next step towards

achieving localization is map-registration. This stage is often referred to as the correspondence determination.

Here, the correspondence problem involves registering

the 2D laser range data to the 2D map. The Iterative Closest Point (ICP) algorithm [3] is employed to obtain

the correspondence. As the iconic ICP algorithm works

directly on sensed data, it does not require extraction

and registering of features. The crux of the Iterative Closest Point (ICP) algorithm is to iteratively match

points in one set to the closest points in another set,

given that the transformation (the translation and/or

rotation) between two sets is small. Here, the two point

sets are the map and the laser range data, respectively.

The shortcoming of the ICP algorithm is that it can

only deal with cases when the first set is a subset of the second set. Zhang [3] developed a similar idea for establishing the correspondence which will be hereafter

referred to as the ICP algorithm. The strength of this algorithm lies in the fact that it is capable of dealing

with gross outliers in the data, occlusion and appear- ance and disappearance in which points in one set do

not appear in the second set. With the ICP algorithm there is no definitive way

in which the uncertainty of the range data can be

taken into account. Although Zhang discusses partial

ways to accommodate the measurement uncertainty,

ICP alone does not provide sufficiently reliable and

accurate vehicle motion estimates. These shortcomings are overcome by combining the ICP with a postcorrespondence EKF. The laser observations that do

not correspond to any line segment of the map are dis- carded during the EKF update stage thus making it robust to errors in the map. Another attractive and

appealing feature of this combined ICP-EKF algorithm

is that observations from a variety of different sensors can be easily combined, since the changes are reflected only as additional observational states in the EKF [4],

[5]."The vehicle employed in the first trial was a four- wheel drive (4WD) Troop Carrier shown in Figure 1. The estimated path of the 4WD vehicle (solid line) provided by the ICP-EKF algorithm along with the

artificial landmark-based path (dotted line^) and the

generated map using the proposed map-building algorithm is shown in Figure 2(a). Note that the map

captures the geometry of the environment adequately.

The curved surfaces are sufficiently modeled by shorter

line segments in the polyline map. The vehicle travels a distance of 150 meters along the tunnel from right to

left. The orientation estimated by the ICP-EKF (solid

hne) and that obtained by the artificial landmark al- gorithm (dotted line) are shown in Figure 2(b). The

corresponding 2a confidence bounds for the absolute

error in x, y and d) are shown in Figure 3. It can be

seen that the errors are bounded and thus the pose

estimates are consistent. It is also clear that the es- timated path is in close agreement with the artificial landmark-based path.

The second vehicle that was considered for the veri- fication of the proposed algorithms is the LHD truck. LHDs are the work horses of the mining industry. The

vehicle has a front and a rear body which can rotate

^As the estimates and the their corresponding ground truth

are very close, extra effort is required on the part of the reader

to distinguish between the two.

512
Fig. 1. The 4WD trial vehicle used in the underground mine

trials. The location of the wheel and steering encoders, two

time-of-flight range and bearing lasers and the bearing-only

laser is shown.

relative to each other and the front and rear wheel

sets are fixed to remain parallel with the body of the

vehicle. Steering is achieved by driving the articula- tion joint located mid-way between the front and rear

axles. Both the front and rear wheel sets are driven

at the same speed through a single transmission. The

LHD and its sensor suite are shown in Figure 4. Unique variations in data sets are necessary to es- tablish an unambiguous correspondence with the map.

Whenever the uniqueness can not be guaranteed, the ICP-EKF algorithm can fail to produce reliable association. The ICP algorithm provides a single trans- formation for each registration. Given the data sets, a set of transformations satisfies the registration. In the case of long tunnels or circular regions, this is too

restrictive. For the tunnel, it is the set of transformations that align the walls independently of the position

along the wall. Essentially what this means is that the position of the vehicle will be uncertain along the

longitudinal direction of the tunnel. When using an EKF that combines range scan registration with deadreckoning uncertainty, the positional covariance (or the uncertainty ellipse) will be large along the directions that can not be locked down by range scan registration

alone. When the vehicle encounters a region that can be reliably recognized, the positional covariance can be reduced. When such regions are not encountered, some form of external aiding needs to be provided in regions where the ICP-EKF algorithm fails. For the LHD, the ICP fails to produce correct corre- spondences in certain regions of the tunnel when there are degeneracies in rigid transformations during registration. The proposed method of overcoming these

deficiencies is to incorporate landmarks that provide

aiding information to guarantee reliable localization. A strategy to augment the ICP-EKF algorithm with

40 50 60 70 60 90 100 110 120 130 140 X|m)

(a)

5.5

1,5' ' ' ' ' ' ' 1 1 ' 30 40 50 60 70 BO 90 100 110 120

(b)

Fig. 2. ICP-EKF estimated path (a) and orientation (b) of the 4WD vehicle (solid line) and the artificial landmark-based path and orientation (dotted line). In (a), the starting location of the

vehicle is at (133.3,-17.8) and the direction of travel is from

right to left.

a limited number of artificial landmarks is developed

in Section V. These landmarks are then detected by

the bearing-only laser to overcome limitations of the ICP-EKF algorithm.

Being an iterative algorithm, the initial pose esti- mate that is made available to the ICP is extremely

important as the resultant correspondences depend on

a good initial estimate. For the 4WD vehicle, the landmark augmentation procedure was not necessary

in spite of long, straight sections of the tunnel. The

reason for this is two fold. Firstly, the slippage the 4WD vehicle experiences due to the undulatory nature of the terrain is less than that of the LHD. In addition to the uneven nature of the terrain, the LHD

slips much more than the 4WD vehicle due to the ge- ometry of the tunnel and the kinematics of the truck

513
2a bounds for x, y and <!>

30 40 50 60 90 100 110 120

Fig. 3. The 2a confidence bounds are computed using the

covariance estimate for the error in x, y and (j> compared to the actual error computed with the corresponding artificial landmark-based estimates for the 4WD trial.

Fig. 4. The Load-Haul-Dump truck and its sensor suite. The

LHD was fitted with two two-dimensional time-of-flight range and bearing lasers. The bucket is in front of the vehicle. A

bearing-only laser scanner, as in the case of the 4WD trials, detects the presence of artificial landmarks. Encoders were used

to measure the vehicle velocity and the articulation (steering) angle.

fered by a particular landmark from a given vehicle pose. This method implicitly takes into account the

uncertainty in the vehicle pose estimate while computing the information content of the landmark. The

concept of entropy is employed to facilitate landmark

augmentation.

The entropy /i (

• ) is a measure of the average uncertainty of a random variable and thus represents the compactness of the probability distribution. Subsequently, it is a measure of the informativeness of the

distribution where information is defined as the negative of entropy. The entropy is minimum when infor- mation is maximum. It is conventional to seek minimal entropy when actually maximum information is sought. A mathematical expression for the entropy of a Gaussian distribution is to be developed. For an n- dimensional state vector conditioned on a stacked

observation vector denoted by = [zi,Z2, Zk] where 2i , Z2 , . .

. , z^ are individual sensor measurements, the posterior entropy can be derived to be [6]:

hk\k = h{p{yik I Zfc)) = E{-^np(xfc I Zfc)} = 0.5fn[(27rer|Pfc|fc|]

Thus for a Gaussian (normal) vector distribution all that is required to compute its entropy is its length, n

and covariance, P. The posterior and prior information metrics can then

be defined as:

imk\k = -h{p{xk I Zfc)) = -0.5 en [(27re)"

| k\k\

imk\k-i = -0.5 [(27re)" |Pfc|fc^i|]

The resultant information contribution, ic, from

measurements, is thus given by the relation:

itself. Secondly, the 4WD vehicle model produces good

prediction estimates enabling the ICP to provide accurate correspondences thus obviating the need for land- mark augmentation. For the articulated LHD, deadreckoning is not as good as that for the 4WD vehicle. Even explicitly taking into account wheel slippage with

the inclusion of the two slip variables, and /3„ [1], the dead-reckoning estimates that are the initial esti- mates to the ICP are poor and accordingly the corre- spondences are no longer accurate. For these reasons, external landmark aiding becomes necessary for the LHD.

III. Landmark Selection and Augmentation

The proposed method for the selection of a partic- ular landmark is based on localization information of-

^Cfc|fe irrikik - i'^fc|fc-i (1)

To overcome cases in which the ICP-EKF algorithm has insufficient information, the system is augmented

with a limited number of artificial landmarks along cer- tain sections of the tunnel. To reaUze this goal, the fol- lowing three questions need to be answered: 1) When

should a landmark or landmarks be added for external aiding? 2) How to select potential landmarks in order

to overcome the divergence of the ICP-EKF estimates?

Additionally, given a set of landmarks, how to select a landmark or landmarks that are optimal in the sense

of increasing the robustness of localization? 3) Given

a set of optimal landmark (s), how to incorporate these

external aiding measurement (s) from the landmark(s)

into the existing ICP-EKF framework?

514
The first two questions are answered in the following

paragraphs and the landmark augmentation methodology is detailed in Section V.

• Landmarks are introduced when the estimated pose covariances exceed a predefined bound. The

growth in covariance is a direct result of inaccurate

correspondences provided hy the ICP. Without additional landmarks, this would eventually lead to filter divergence.

The issue of computing a potential landmark set that can be employed to provide aiding measurements is addressed as follows: • Potential landmarks can be computed from a given

vehicle position since the artificial landmark locations are available as is the direction of vehicle travel. By

discarding landmarks that are farther than a predetermined distance (proportional to the range of the bearing-only laser when artificial landmarks are to be augmented or to that of the range and bearing

laser when natural landmarks are to be augmented),

a landmark set can be arrived at and denoted by:

Lp/:(Xip,,Yj^,). ipi = 1 : where Upi is the number of landmarks in the set. • From the current vehicle position, for all the land- marks in the set Lp/, the predicted bearing measure- ment (range and bearing measurements in the case of natmal landmarks) is computed and is checked to see

if this measm^ement is acceptable.

• For all axjceptable measurements, the individual in- formation contributions are computed according to Equation (1). Finally, the landmark that provides the maximum information from the potential set of land- marks is selected for augmentation.

IV. Multiscale Natural Landmark Extraction

Feature or natural landmark-based methods for au- tonomous locafization have become increasingly popular as they do not require infrastructure or other exter- nal information to be provided to the vehicle for operation. Feature-based localization methods require that natural landmarks can be robustly detected in sensor

data, that the localization algorithm can reliably as- sociate landmarks from one sensor observation to the

next, and that the method can overcome problems of

occlusion, ambiguity and noise inherent in measure- ment data. In indoor environments, features such as walls (Une-segments), corners (diffuse points) or doorways (range discontinuities) are used as landmarks. In outdoor environments however, similar simple features are sparse and infrequently observed. In unstructured

or natural outdoor environments a more general notion of a landmark or navigation feature is required.

Given a (laser) range scan of an environment, one natural measure of feature or landmark significance is the

local curvature in this range data. Rapidly changing

range data indicates either a significant physical dis- continuity or a prominent geoform. The use of local curvature as an interest measure is well known in the

computer vision community. Further, and most important for navigation, curvature extrema are well known

to be view-point invariant. Practically, this means that

points of maximum curvature can be used as robust

point landmarks in localization. Scale space filtering is a qualitative signal descrip- tion method that deals with the problem of scale by

treating the size of a smoothing kernel as a continuous

parameter [7] . The main idea of multiscale representation is to successively suppress fine scale information

and thus to progressively remove the high frequency

information which results in the signal becoming gradually smoother. The common way of constructing a

scale space is by convolution with a Gaussian kernel. The essential requirement here is that a signal at a

coarser (higher) scale level should contain less struc- ture than at a finer (lower) level of scale. In scale space methods, a qualitative description of the signal

is obtained by studying the behavior of the extrema

over the continuum of scales. Also the extrema that smvive over larger smoothing extents are considered

to be more significant than others. Attenuation of the

noise in the signal is realized by convolving the signal

with the Gaussian kernel. A Curvature Scale Space (CSS) algorithm was devel- oped to identify, extract and localize landmarks characterized by points of maximum curvature at successive geometric scales. The CSS algorithm can be used

to extract curvature extrema from laser scan data cor- responding to landmarks at diff'erent scales that are:

1) invariant to rotation and translation of the shape

(signal) under consideration 2) robust to noise and 3) reliably detected and localized. The basic principle

of the CSS algorithm to identify dominant points is: "Convolve a signal with a Gaussian kernel and impart

smoothing at difi^erent levels of scale (the scale being

proportional to the width of the kernel). From the re- sulting convolved signal, identify the dominant points

(curvature extrema)." For various degrees of smoothing of the curve (segmented range scan) , it is desired to

find the curvature extrema. A parametrization of the curve is necessary to compute the curvature at varying

levels of detail (for segmentation and parametrization

procedures see [8]). A parametrization is possible by

considering a path length variable along the curve and

expressing the curve in terms of two functions x{s) and

y{s) such that C = {x{s),y{s)] with s being a linear function of the path length ranging over the closed in- terval [0, 1]. The curvature, is given by:

n{s,a) = X{s,a)Y{s,a) - Y{s,a)X{s,a)

where {x{s,a),Y{s,cr)\ and {x{s,a),Y{s, a) > are

515
obtained, respectively, by convolving x(s) and y[s)

with the first and second derivatives of the Gaussian

kernel. The Gaussian kernel is given by: g{s,a) =

g-s-/2<T ^i^ere a is the width of the kernel. By

employing the CSS algorithm, dominant points are ex- tracted based on the persistence within a scan and over consecutive scans. Features that exist only at finer scales and disappear at higher scales do not correspond

to stable features and thus do not qualify as reliable candidates for subsequent detection and tracking during the vehicle localization stages. Persisting dominant

points enable the construction of a natural landmark

map based on which natural landmark-based localiza- tion is achieved.

V. Landmark Augmented Minimal

Infrastructure Localization

This section describes the localization of the LHD

using both artificial and natural landmarks. Natural

landmarks characterized by dominant points of curvature were ext,racted from laser rangefinder scans and

a natural landmark map was built using the curvature

scale space algorithm as detailed in Section IV. Such

a natural landmark map can then be used to augment

the ICP-EKF framework thereby reducing the number

of artificial landmarks that are required for reliable and

robust localization.

A. Natural Landmark Observation Model

The laser rangefinder provides both range and bearing to a landmark and accordingly an equation relating

both of them to the vehicle (laser) location is required.

The predicted range and bearing, respectively, for each

natural landmark j at discrete time-instant k is given

by the non-linear model:

C = tan-i

where {xl^^,y^^() is the cartesian location of landmark

j and {xL,yL) is the location of the laser rangefinder on the vehicle. The observation model for a natural landmark is thus given by:

+ (2)

where v^^^ and v^^^ refer to the uncertainty present in the range and bearing measurements and are modeled

as zero-mean uncorrelated Gaussian sequences with

constant variances, o-\^^ and cr^^^ , respectively.

B. Entropy-based Artificial Landmark

Selection and Augmentation

During the vehicle localization stage, for every range and bearing scan, natural landmarks are extracted and

are associated with those in the map. Details of natural landmark matching and discriminance procedures

are detailed in Section V-C. When the information

provided by these natural landmarks is not enough to

curtail the gro^vth of the pose covariances, the entropybased landmark selection and augmentation method

is adopted to select the required artificial landmarks.

Whenever it is determined that the ICP-EKF framework requires additional external aiding, all the land- marks that are visible from the current vehicle position are examined and the landmark that contributes the

maximum information is then selected.

C. Natural Landmark Matching and

Discriminance

Whenever a range and bearing scan becomes avail- able, there is the need to decide whether the scan should be used for a) Natural landmark-based local- ization or b) ICP-EKF based localization. The same

scan should not be used for both as this amounts to using the same information twice. To avoid such reuse

of information, the entropy-based information content measure is utilized to determine to decide upon (a) or

(b). The pertinent localization procedure is arrived at by looking at the information contribution provided by

both (a) and (b) and selecting the one that provides

maximum information towards localization. When natural landmarks are used for localization, it

is essential that the extracted natural landmarks from

a scan are reliably matched to those in the map. Whenever a range and bearing laser scan is received, the dominant point landmarks are extracted in the same

fashion as described in Section IV. Locations of all the extracted dominant points above a certain scale level are then compared with the natural landmark map.

Two landmarks that differ only slightly in their posi- tion should be identified as distinct within the Umits

imposed by the sensor noise. Such discriminance is achieved by checking if the computed innovation se- quences pertaining to both the range and bearing of a matched natural landmark fall within the normalized

innovation gate by using the natural landmark obser- vation model given in Equation (2).

If the observations fall within the prescribed limits, then the landmark is accepted as a match. Subsequently, this observation is used to update the vehicle states using the range and bearing innovation se- quences that are obtained as a direct consequence of the matched landmark measurement. The resultant in- formation contribution from a matched natural land- mark, icnt, and that after the ICP-EKF updates for

516
the same scan, icicp-ek/^ are computed by using Equation (1). Based on iCne and icicp-ekf, the procedure

that provides the maximum information is chosen. The

combined algorithm thus bounds the natural degradation of the ICP registering results when there are no

distinguishable landmarks along the longitudinal direc- tion and ensures that the lateral matching (crucial for vehicle guidance) is not deteriorated.

D. Results and Discussion

The results when both natural and artificial land- marks are employed towards locahzation of the LHD

are discussed now. Figure 5(a) and (b) show the esti- mated path and orientation of the LHD by the ICPEKF natural and artificial landmark-augmented algorithm (sohd line). It should be emphasized here that the natural landmarks need to be extrax;ted only once. For locaUzation in a tuimel over several trials, the

natural landmark extraction can be done on an ex- ploratory trial run and such landmarks can then be

utilized. From Figure 5(a), it can be seen that the landmark-augmented ICP-EKF algorithm provides es- timates that are similar to the groimd truth. Note

that natural landmarks have taken the place of artifi- cial landmarks along the straight sections of the tunnel. Unfortunately, in the circular loop section of the tunnel, there were not many persistent extractable natural landmarks and this necessitated the inclusion of artificial landmarks. Nevertheless, the important point

to note here is that the number of required artificial landmarks have been successfully reduced (by a factor of four [1]). In environments where the extraction of

persistent dominant landmarks is possible, the artifi- cial landmarks can be totally eliminated^. Figure 5

(b) shows the orientation of the two trials (solid line) along with those provided by the artificial landmark

algorithm (dotted line). Figure 6 shows the absolute pose errors computed

with the aid of the ground truth and the corresponding 2(7 (95%) confidence bounds. It is evident that the

errors remain white and are well within with the pre- scribed boimds representative of consistent estimates. Absolute error estimates of half a meter were achieved

in the position estimates with the corresponding error

in the orientation estimate being less that 5 degrees.

Figure 7 depicts the validated range and bearing in- novation sequences along with the Icr and 2cr bounds.

The discontinuity in the innovation sequences corre- sponds to periods where there were no updates per- formed as there were no natural landmarks available during such periods. For example in Figure 7, the dis- continuity from 177 - 200 seconds in both the range

^In fact, this claim was substantiated by a third trial run on

a Utility vehicle in an outdoor area populated by people and moving cars in the University of Sydney campus [8].

(a) Estimated path of the LHD

Orientation of the LHD

ICP-EKF+Lmks.

Artif. Lmk,

(b) Estimated orientation of the LHD

Fig. 5. Natural landmark-augmented ICP-EKF estimated path

(a) and orientation (b) of the LHD (solid line) and the artificiaJ landmark-based path (dotted line). In (a), the traversed path runs

right to left. The direction of travel is in the anti-clockwise direction ajound the loop at the left end of the figure. The circles represent the augmented artificial landmark locations ajid the crosses repre- sent the natural landmark locations. The starting location is at (81.1,-30.9).

and bearing innovation sequences corresponds to the loop section of the tunnel where the external aiding is predominantly provided by the artificial landmarks. It can be seen that both the range and bearing innovation sequences also remain white and are well within

the defined bounds.

517
2o bounds tor x. y nnd O'

100 150 POO

100 150 ?on

Fig. 6. Natural landmark-augmented ICI'-ElvP" pose errors and the 2a confidence bounds computed using the covariancc estimate for the error in y and o compared to the actual

error computed with the corresponding artificial landmarkbased estimates.

lo and 2a Bounds for Natural Landmark Rango Innovniloii Sequonco

Fig. 7. Range and bearing innovation sccjucnccs for the natural landmarks matched during the LHD trial. The la and '2a confidence bounds are also shown.

VI. Conclusions

This paper discussed the developmout of a uuifitxl terrain-aided framework for achieving minimal infras- tructure locahzation of high speed vehicles oi)erating

in unstructured and harsh enviroimients.

The first step in the achievement of this goal was tfie development of a map-based ICP-EKF localization al- gorithm utilizing measurements from a scamiing laser rangefinder in combination with dead-reckoning sensors. The next step was the identification of shortcomings of the ICP-EKF algorithm and the development

of an entropy-based landmark augmentation metric: to overcome the deficiencies. Using this metric, evaluation of information content of measurements was possible and thus facilitating tfie acceptance or rejection

of a particular landmark measurement. The metric was shown to be an optimal way of efficiently utiliz- ing measurements by implicitly incorporating the land- marks' utility towards reducing localization error. A

view invariant multiscale natural landmark extraction

algorithm was developed to extract point landmarks

characterized by dominant curvature points from laser scans thus facilitating reliable detection and extraction of persistent natural landmarks. Attenuation of

noise inherently present in laser scans was achieved

l)y convolving the scans with a Gaussian kernel. The

algorithm was also sliown to possesses the attractive property of being invariant to rotation and translation

effects that the laser scans under consideration might

experience due to vehicle travel over harsh terrains. Finally, the paper detailed the integration of the information metric, the CSS and the ICP-EKF algorithms to arrive at a unified localization framework.

The developed localization framework has the ability to use measurements fiom both artificial and natural landmarks as and when they become available and was shown to be sufficiently generic to be used on a variety

of autonomous land vehicles, by its application to a 4WD vehicle and an LHD truck. The results demonstrated the reliability and robustness of the proposed

framework.

References

[1] R. Madhavan, Terrain Aided Localisation of Autonomous

Vehicles in Unstructured Environments, Ph.D. thesis, School of Aeronautical, Mechanical and Mechatronic Engineering, The University of Sydney, Jan. 2001.

[2] R. Madhavan, G. Dissanayake, H. Durrant-Whyte,

J. Roberts, P. Corke. and J. Cunningham, "Issues in Au- tonomous Navigation of Underground Vehicles," Special Edition of the Journal of Mineral Resources Engineering, vol.

8, pp. 313-324, 1999.

[3] Z. Zhang, "Iterative Point Matching for Registration of Free- Form Curves and Surfaces," International Journal of Computer Vision, vol. 13, no. 2, pp. 119-152, 1994.

[4] R. Madhavan, G. Dissanayake, and H. Durrant-Whyte, "Au- tonomous Underground Navigation of an LHD using a Combined ICP-EKF Approach," in Proceedings of the IEEE In- ternational Conference on Robotics and Automation, May

1998, pp. 3701-3708.

[5] R. Madhavan, G. Dissanayake, and H. Durrant-Whyte,

"Map-Building and Map-Based Localization in an Underground-mine by Statistical Pattern Matching,"

in Proceedings of the IEEE International Conference on

Pattern Recognition, Aug. 1998, pp. 1744-1746.

[6] J. Manyika and H. Durrant-Whyte, Data Fusion and Sensor Management: A Decentralized Information- Theoretic Approach, Ellis Horwood Limited, 1994.

[7] A. Witkin, "Scale-space Filtering," in Proceedings of the Eighth International Joint Conference on Artificial Intelli- gence, Aug. 1983, pp. 1019-1022.

[8] R. Madhavan, H. Durrant-Whyte, and G. Dissanayake, "Natural Landmark-based Autonomous Navigation using Curvature Scale Space," in Proceedings of the IEEE In- ternational Conference on Robotics and Automation, May

2002.

518
MONITORING OF THE BORING TRAJECTORY IN UNDERGROUND CHANNEL

Thomas Bock, Alexej Bulgakow*, Dimitry Krapivin, Sergej Aleksyuk, Sergej Pritchin**

* Technical University Munich, a. bulgakow@gmx. de ** South Russia State Technical University, aprim@novoch.ru

Abstract: This paper deals with high precision directional boring of underground conduits,

including programmable curved trajectories for enclosed digging driving communications and

other purposes.

Keywords: underground chaimel, dynamic monitoring, driving communisations.

1. INTRODUCTION: As the working tool for

boring in soft anisotropic soils a cone is modeled, which is imparted a revolving motion

whose angular velocity is copr, its impact

frequency /. The impact makes the revolving cone penetrate into the soil along the screw

trajectory. The cone thus revolves around its symmetry axis OOi with angular velocity cOk

Acted on by various factors the conditions of

oscillating motion of the OOi axis can change

Fig. 1

Fig. 2

in such a way that the apex of the cone is displaced from the axis of the Oz, relative to the tunnel centerline and takes part in

oscillating motion as well, its parameters being

e and Ah to Oz axis (Fig. 2). Here, the cone

slips and performs friction work while its constituent OA is displaced from NM line

during its turn at some angle (p to O2 and O3 at an angular velocity cOg-

(Fig. 1) in such a way that the above axis OOi

itself oscillates eccentrically around Oz at an

angular velocity coo at an angle p.

519
The above parameters of this motion are found following the calculation of the

location of point O2, based on the

principle of the least action. With uniform

distribution of the normal force

longitudinal to the generating line of OA,

the elementary work of the friction force

F on the element d( will be

dA = FVd^

where W = 0)^ S = the linear rate of

di element, and S = the distance of

The slip appearance will make point A shift

from the screw line B'AB". The coordinates of

point A can be derived as

X = (R - e) • cosco^^t ; X = (R-e)sin<yp^/ ; z=n-5,

where n = number of impacts, 6 = penetration

in a direction of operation of impacts; the R-e

value is found from

The total work of the friction forces is

2 " s>\n{/3-a) ^ \

The minimum of the function A will be at —dA L =0 or with ^ = — , where L=OA, i. e. when M 2

the cone constituent slips along the tunnel

boring face relative to point O2 located in the

middle of cone assembly.

where r is the greatest cone diameter.

Thus, dynamic monitoring of the trajectory of a working cone motion is carried out by means of

defining angular velocities cOe, copr and analysis

of the amplitude readings of impacts. These

indications can be used to control the directed

520
cone motion. The shift value, e, at every turn can change with varying cOpr and redistributing

the number of impacts around the face

perimeter.

When boring the tunnel in a uniform medium e

is a constant. In a particular case, if e=0, the

motion parameter relation is observed

h[n] = ^sinA (1)

Where h[n] is the boring length in the preset

direction within n impacts, where h=n5, and P

is the angle of screw line inclination. Figure 3

shows the plane projection of a screw line for a

turn.

The impact of duration T=T and amplitude y

causes line B'AB" to be formed, which consists

of curved portions of separate tunneling for

every impact, thus resulting in screw line

inclination at angle (3.

If the medium is non-uniform^ the parameter

relationship in equation (1) is violated. Thus,

in Figure 3 at the i-th stage the impact

amplitude y, « yn, the impact duration Xi < T,

but Ah, decreases 6, < 6, the angle pi < P

changes and there appears eccentricity Ci. All

the above can result in trajectory deviation due

to variation of dynamic properties of the

tunneling process.

To correct this deviation operatively one must

have a self-adjusting system of automatic

controlling of the direction, which is effective if the anisotropy of the medium acts weakly. The

system shown figure 4 has as a source of data

gauge 1 of the amplitude of impact, gauge 2 of

angular velocity of the turning cone (Ok, gauge 3

of the angle of drive rotation velocity, a discrete

correlator, a controlled filter, and an adaptive

regulator. To find the dynamic properties of the

system consisting of a drive feeding set, and a

penetrating cone with a striker, a pulse

transient function as a sequences of coordinates

is synthesized in a controlled filter as:

Wo = W(0) , Wi = W(r) , W, = W(2 • r) , W„ = W(n • T).

These values enter the RAM on OSi OSnCalibration values O)*o-co*n are recorded on OS 1 to OS n to store the programmable

trajectory into ROM.

On the delay line a periodic signal is put from

the input unit, which is proportional to the

centered correlation input - output function.

Thus, the following expression is obtained on

the adder output:

K:(r) = T^-XW(i-TJ-K;-(r-iTJ.

i=0

The difference is put to the comparator:

By adjusting the coefficients this difference can

be minimized. Extreme regulators are used to make the process of impact function estimate

automatic.

2.0 CONCLUSIONS:

Thus, the procedure of trajectory monitoring

envisages a complete analysis of dynamic

system properties taking into account stochastic

character of effect. This control method uses

intensifying impact effects for probing

anisotropic properties at the face and

controlling the process of direction correction.

521
522
SESSIONS

AUTOMATED INSPECTION AND

MAINTENANCE MANAGEMENT

SYSTEMS

523

A MULTI-SENSORY APPROACH TO

3-D MAPPING OF UNDERGROUND UTILITIES

Leonhard E. Bernold,

Associate Professor

Lashminarayan Venkatesan, GRA

Sushil Suvarna, GRA

Construction Automation Robotics Laboratory (CARL), North Carolina State University.

Abstract: The demand for new buried utilities, such as gas, power and fiber-optic

communication Unes is growing with new construction, re-construction, and the growth

of the communication infrastructure worldwide. Because the machinery for placing the new utiUties underground, such as backhoe excavators, trenchers, augers, drills, and

plows, don't "feel" when they are getting close to already buried object, utilities are

easily damaged. Despite great efforts in locating existing utilities before a contractor is allowed to dig, accidents occur. This paper will present a novel technology for detecting

and locating buried utilities that attaches to the digging equipment and utilizes both EMI

(Electromagnetic Induction) and a GPR (Ground Penetrating Radar). The newest effort involves the development and performance analysis of algorithms to detect and extract the features and characteristics of these utiUties, such as their orientation, diameters etc. One prime focus is to minimize the percentage of false alarms. For that purpose, the two

sensor systems are fused to create a multi-sensory approach to 3-D mapping of all the

UtiUties without a priori knowledge of their location

Keywords: Buried utiUty detection, Electromagnetic Induction, Ground Penetrating

Radar, Sensor fusion.

1. INTRODUCTION

In 1993, the Construction Automation and

Robotics Laboratory (CARL) at North

Carolina State University (NCSU) started an

initiative to address the national problem of

detecting and locating underground buried

utilities. The core idea was to provide the

equipment operator with his own system

integrated with the equipment that alerts him

of the danger rather then to depend on the

color marks made by the locator sent by the

One-Call center. For that purpose, a sensing

platform, operating like a subsurface "Xray" was attached directly to the machinery

hence providing the operator with an

opportunity to "see" and be warned when

the machine tool gets close to an existing

utility. The original system was based on

the Electro Magnetic Induction (EMI)

technology that was integrated with PCbased software to process and analyze the

signal coming from an antenna. Using a

traditional coil, the antenna generates its own magnetic field and senses the existence

of ferrous and non-ferrous material. The

analogue output of the controller is then

digitized and plotted on the computer

screen. By taking advantage of this capability, the technology was used to

retrofit backhoe excavators, trenchers, and

augers. The success of the initially crude

system led to the development of an improved version to be used during the

excavation of unexploded ordinances

(UXOs). In 1997, the Buried Utility

Detection System (BUDS) consortium was

founded that continued the work on three

fronts: a) processing of sensory data, b)

mechanical system, and c) human-machine

interface. A simple user interface was

created by creating a control box for the

operator, consisting of two buttons for

operating the articulated sensory platform

and a red-yellow-green light as feedback.

Details of the system and current

525
developments, experiments and preliminary

results will be discussed later.

Utilities, such as gas lines and optical

communication cables, are mainly nonmetallic making the EMI technology useless

since these utihties are "invisible" to the

metal detector. Other non-metallic objects

underground include sewer lines made of

concrete, clay and plastic. One sensor that has been successfully used even in archeology is the Ground Penetrating Radar

GPR). The GPR transmits RF signals and

detects the signals reflected by changes in the ground. When translated on the surface

it provides a cross-sectional image of the

material below the ground surface. Details

of how this image is decoded, problems

faced and implementation details are discussed later.

2. THE NEED FOR DAMAGE

PREVENTION

The congressional Transportation Equity

Act for the 21'' Century, TEA 21, Title VII,

Subtitle C, SEC. 87301, states that: "...unintentional damage to underground

facilities during excavation is a significant cause of disruptions in telecommunications,

water supply, electric power, and other vital public services, such as hospital and air traffic control operations, and is a leading cause of natural gas and hazardous liquid

pipeline accidents."

Underground Focus Magazine (1999) is a source that publishes an Accident File in every issue. For example it listed that from

December S"' until December 11*^ 1998, seven major accidents occurred. On the 9* a

fiber optic cable was cut by an excavation

contractor that supported the 9 1 1 service for

five counties in Jacksonville, Texas. The

most tragic accident, however, occurred on

Dec. 11 when "a crew using an "anchor

cranker" to install a guy wire anchor for a telecommunications pole augured into a gas

main." four people were killed and fourteen

injured when the gas exploded in St. Cloud,

MN.

There are many different parties, actively

and passively, involved in the excavation

and trenching process. Active participants

include 1) owners of a new facility, 2)

designers, 3) planners, 4) contractors, 5)

utilities, 6) locators, 7) construction workers,

and 8) equipment operators. In most U.S

states, a contractor is required by law to call a "One-Call Center" 48 or more hours

before he digs.

Despite the successful implementation of the

One-Call systems in most of the U.S states, the accidents caused by damaging

underground utilities resulting in wide

variety of impacts reaching from a clogged

residential sewer line to a gas explosion

causing death and destruction. The list of

impacted parties that incur cost comprises

not only the contractor, utility and property

owners, people in the vicinity of the

accidents, but also the customers of a disrupted utility. Some of these groups

include: a) private homes, b) governmental

agencies, c) service companies, d) schools,

e) hospitals, f) industrial firms, g)

transportation systems like airports, taxi services, freight trains and trucking, h)

retailers, and i) the utilities themselves.

Overall, the direct and indirect costs of such

accidents are staggering making the use of more sophisticated prevention approaches

also economically prudent.

3. LOCATING BURIED METALLIC

UTILITIES USING EMI

3.1. CONCEPT AND BACKGROUND

Anything metallic present in the ground can

be induced to create a magnetic field, which

can be detected by an antenna. The magnetic

field is caused by a signal emitted by the

transmitter coil. A receiver coil "listens" to

this reflected signal and gets a measure of

the metal around it. This can be done by

either Continuous wave EMI or Pulse EMI.

EMI sensors have been used since the

1950' s for quality control on manufacturing

526
production lines to safeguard against

contamination. In more recent times, they

have been used as a tool for mining, nondestructive testing, security, archaeology

geology and other related fields. Metal

detectors using electro-magnetic induction,

especially pulse induction are not new in the

field of buried utility detection. With two

antennae, or one moving antenna in many

positions, it is also possible to determine the

depth of the buried pipe. Some researchers

(Das et al., 1990) performed the analysis of

the EMI detector for real-time location of

buried objects. Several response

characteristics of the utility, such as object

depth, orientation, aspect ratio, and material

properties were studied and, due to limitations of direct metal detection, the

need for sophisticated processing was

observed. This technology has also been

used to discover unexploded ordinance

(Lorenc and Bemold, 1997).

3.2. A BURIED UTILITY DETECTION

SYSTEM

Figure 1 presents the basic idea of the equipment-mounted Buried Utility

Detection System (BUDS) developed at NC

State University. It is a prototype aimed at being part of a real-time system, integrating sensor fusion techniques. Presently, efforts are being made to form an extensive

database of utility contours obtained from

BUDS. After forming such a database, the next step is to go in for field-testing of

unknown soils and utilities buried

underneath. With a knowledge base and

classification based learning schemes, we

would be in a position to estimate with a degree of probability, the depth, orientation

and material properties of the object. This

estimation or the data obtained in the cruder

stage of the sensing process would be fed

into the sensor fusion module.

3.3. EXPERIMENTAL TEST BED

The experimental setup developed at CARL,

called BUDS, consists of a moving cart under a stationary antenna. The cart and the

antenna can be positioned at various angles

to represent real-life site configurations. It is completely software controlled and is being

used for collecting sensor contours for various geometric configurations of pipes,

changing the material properties of the pipes

and the antenna characteristics itself.

3.4. INITIAL RESULTS

Initial results (Fig 2) from the experiments

show predictable agreement with previous

work in the field. It has been found that as the antenna scans the utility below and the

computer continuously plots the readings, a peak in the graph shows strong metallic content very near the antenna. By changing

the horizontal angle and vertical tilt we get

slightly different curves and by triangulation

we can estimate depth of the pipe. We also

noticed the change in the curves for deriving

material characteristics, for example,

studying the difference in the contours for a

solid pipe and hollow pipe of the same

dimensions and material.

3.5 APPLICATIONS

Apart from just carrying out experiments for detecting utilities, the CARL team has also

worked on a BUDS application. It consists

of the antenna mounted on a backhoe giving

feedback to the operator about the existence

of buried utilities before excavating (Fig 3).

4. SUBSURFACE UTILITY MAPPING

USING GPR

4.1. WHAT IS A GPR?

The GPR is a remote sensing short-range

system, which measures short pulse

electromagnetic (EM) reflections due to variations of the electrical properties of the

investigated medium. The electromagnetic

wave, which is radiated from a transmitting

antenna, travels through the material at a

velocity that is related to the electrical properties of the material. As the wave

propagates, if it hits an object or a boundary

with different electrical properties, then part

527
of the wave energy is reflected or scattered

back to the source. The wave, that is reflected back, is captured by an antenna and

an image is created that is reflective of the

materials and boundaries present beneath the

surface. The main drawback of a GPR is the

inability to detect the exact material of the

buried object.

4.2. GPR USED IN PIPE AND MINE

DETECTION

New and general methods for landmine

detection using GPR images have been

evaluated. Simple and effective observation

vector representations have been constructed

to model the time varying signatures

produced by the interaction of the GPR and

the landmines. Gader (et al., 2001) used

Hidden Markov Models (HMM) to recognize patterns and to predict the

presence of landmines. Landmines appear in time domain GPR as shapes similar to hyperbolas, although corrupted by noise and

other factors. A signature library was

created using a combination of ground truth and GPR response for that truth-value. HMMs were used to generate probabilities

for the unknown images by comparing them

with the signature library present. The GPR

has also been used for pipe detection. The

same concept of creating signature libraries for different pipes at different depths is used

and searching algorithms are used to predict

the occurrence of pipes from unknown

images. The image consists of distinct patterns, e.g. a hyperbola, which are studied

to obtain a result.

4.3. LABORATORY SETUP

Most GPR image processing algorithms are based on a signature database that maps the

different possible objects with their orientations and the images created by these

objects under different soil depths and

conditions. The optimal algorithm processes

the image of the unknown object and

compares it with those present in the

database and generates an approximate

estimation about the nature of the object. To

study the responses of different pipe

materials and other objects that could be

present underground an experimental

workspace (Fig 4) has been setup.

Most sample tests performed in the detection

of mines or pipes, involved moving the GPR

in one line, either forward or backwards.

However, our setup aims at observing

images in a single plane initially, and

evolving into one that considers the

perpendicular movement of the GPR. This

would result in an overall zigzag movement

that would generate a 3-D GPR image.

4.4 CURRENT WORK / RESULTS

The setup shown in Figure 4 is being used to study patterns generated by pipes of

different materials, kept at various depths

and also patterns generated by objects such

as rocks and wood that might be present.

The responses from various materials have

been collected and the images are being

studied to locate patterns unique to each

object. The next stages include studying

patterns generated by the zigzag motion of

the GPR and creating a 3-D image that could

be easily interpreted. Once the pattern

recognition for pipe like structures has been

studied, the next stage would be mounting

the GPR with the EMI and obtaining a better estimation of the presence or absence of

buried pipes. A sample GPR image of a buried pipe is shown in Figure 5.

5.INCREASING EFFICACY OF BUDS

USING MULTI-SENSOR APPROACH

As mentioned above, the aim is to create a

real-time, accurate, and most importantly

reliable fish-finder type utility detection

system with minimal false positives.

Although the two sensors discussed above

have their advantages, alone neither can give

reliable estimation of the buried utilities. For example, the GPR module is reasonably

accurate on the depth of the object, but is unable to distinguish between a metallic and

a plastic pipe. Similarly, the EMI, by itself is not capable of providing accurate

528
information regarding the position (e.g.

depth) of a metallic object. These

limitations of the individual sensors can be overcome by a fusion of sensor data.

According to Klein (1993), data fusion is a

multilevel, multifaceted process dealing

with the automatic detection, association,

correlation, estimation, and combination of

data and information from multiple sources. The type of fusion architecture used to combine sensor data depends on the

application. There are three broad 'levels' where data fusion can be incorporated: a)

direct fusion of sensor data, b) feature vectors and c) high-level inferences. Since

the multi-sensor data in our case is not commensurate, we can either represent data

obtained from each sensor via feature

vectors, with their subsequent fusion; or perform individual processing of each

sensor's data to achieve independent highlevel inferences or decisions, which are combined to make a collective decision.

The overall process consists of four main

parts: Preprocessing the signal from the sensor, feature/contour extraction,

feature/property selection, and classification. Figure 6 shows the adapted version of a common data fusion model to MS-BUDS

(Multi-Sensory Buried Utility Detection

System). The data from the two sensors are

initially conditioned by independent signal

processing modules which later feed into a

parallel processor running a multisensor

algorithm. The parallel processor uses a

feature recognition and classification

algorithm that operates on sensory data and

'learns' with a knowledge base as it goes

along.

6. SUMMARY

Damage to buried utilities can cost lives and

damage to property and equipment. This

paper presented a novel technology that integrates two common sensory equipment,

the Pulse EMI and GPR, into a multisensory real time underground utility

detection system. The premise of fusing the

two sensory data stream is to maximize

reliability/accuracy while minimizing false

positives. Two experimental facilities have

been built to study the effect of various soil and object conditions on the features of the sensory outputs. In the next phase two

experimental facilities will be combined into one platform, the MS-BUDS.

7. ACKNOWLEDGEMENTS

Funding for the work has been provided by

Public Health Service-National Institutes of

Health under contract IROl 0H04201-01.

8. REFERENCES

Das, Y., McFee, J., Toews J., Stuart G.: "Analysis of an Electromagnetic Induction

Detector for Real-Time Location of Buried

Objects", IEEE Transactions on GeoScience

and Remote Sensing v. 28 No.3, May 1990.

Gader, P., Mystkowski, M., Zhao, Y.: "Landmine detection with GPR using

Hidden Markov Models", IEEE

Transactions on GeoScience and Remote

Sensing v. 39 No. 6, 2001.

Klein, L.: "Sensor and Data Fusion

Concepts and Apphcations", v. TT14, SPIE

Press, 1993.

Lorenc, S.J., Bemold, L.E: "Excavatormounted Ordnance Locating System for

Remote Excavation", 14"" International

Symposium on Automation in Construction,

June 1997.

Underground Focus Magazine, (1999).

Canterbury Communications, Spooner, WI.

URL: http://www.underspace.com/

529
/V Antenna i^s7

Fig. 1. Equipment mounted BUDS

GPR

Image Processor Sandbox

Fig 4. GPR setup for utility detection.

T

Location of the buried rod

Coil Height (inches) x-Position of pipe (inches)

Fig 2. Graphical sensory output of BUDS

Hroui

Fig 3. Buried Utility Detection System

mounted on a backhoe.

Fig 5. Sample GPR image of a buried rod

EMI Antenna GPR Antenna

GPR

Sensor module

GPR interface

\7

Parallel Processing Of Individual Sensor

Data

Data

Fusion

Multi-sensor algorithm

3-D image re-created DATA PROCESSOR

Fig 6. Simplified data fusion model

adapted to MS-BUDS

530
Automated Inspection of Utility Pipes: A Solution Strategy for Data

Management

Tariq Shehab-Eldeen^^* and Osama Moselhi^^^

( 1) Post-Doctoral Fellow, Department of Building, Civil and Environmental

Engineering, Concordia University, Canada.

tshld@cbs-engi.concordia.ca .

(2) Professor and Chair, Department of Building, Civil and Environmental

Engineering, Concordia University, Canada.

moselhi @cbs-engr.concordia.ca

ABSTRACT; Rehabilitation of urban infrastructures has received considerable attention in North America, creating a need for automation. Automating the rehabilitation process of

various infrastructure facihties is driven by the need for cost reduction, higher quality and

improved safety. This paper describes an automated system, AUTO-DETECT, recently

developed, for rehabihtation of sewer pipes. AUTO-DETECT automatically analyzes the CCTV videotapes that depict the conditions of the surveyed pipes and consequently detects and classifies defects. It introduces five sets of specialized neural networks, each is dedicated for one type of defect. The paper also presents the integration aspects of these

five sets of neural networks to formulate a solution strategy that is utiUzed to improve the performance of the developed diagnostic system.

KEYWORDS: Automation; Sewer pipes; Inspection; Data management.

1. INTRODUCTION

Rehabilitation of urban infrastructures has

received considerable attention in North

America, creating a need for automation.

Automating the rehabilitation process of

various infrastructure facilities is driven by the

need for cost reduction, higher quality and

improved safety. A typical maintenance or

rehabilitation process of underground sewer

pipes usually starts by surveying these pipes

and collecting relevant data about their condition. This data usually highlights many

aspects and provides useful information such

as the presence, type, number and location of

defects. CCTV (closed circuit television) cameras are commonly used to capture these

data. CCTV cameras produce a videotape that has to be visually inspected by a human expert

in order to identify and locate defects, if they

exist. The process is usually time consuming,

tedious and expensive. Interviews conducted

with several municipal engineers and

consultants in Quebec and Ontario, Canada

revealed that the cost of sewer inspection is about CDN $1.5 per linear meter, 30 % of this

cost (i.e. $0.42) is spent on inspection of

videotapes (Shehab-Eldeen 2001).

This paper describes an automated system,

AUTO-DETECT, recently developed, for

rehabilitation of sewer pipes (Shehab-Eldeen

2001). AUTO-DETECT automatically

analyzes the CCTV videotapes that depict the

conditions of the surveyed pipes and

consequently detects and classifies defects. It utilizes image analysis techniques and artificial intelligence (AI) to perform its task through

five sets of specialized neural networks, each

set consists of three networks. Unlike the work

developed earlier by the authors (Moselhi and

Shehab-Eldeen 2000) where one classifier was

developed to detect different types of defects,

this paper introduces five sets of specialized

neural networks, each is dedicated for one type

of defect. This paper also presents the

integration aspects of these five sets to formulate a solution strategy that employs a

multiple classifier technology, designed to improve the performance of the developed

system. An example application is presented to demonstrate the use and capabilities of the

developed system.

531
2. DEVELOPED SYSTEM

The developed system makes use of and builds on current practice. The process used in current practice for detecting defects has been

described elsewhere (Moselhi and ShehabEldeen 1999 (a) and (b)). Figure 1 depicts the

overall configuration of AUTO-DETECT. As

shown in this figure, a closed circuit television

(CCTV), or a zooming, camera first scans the

inner surface of a pipe and produces a videotape which is then played back using a VCR. The VCR then feeds the information

captured on the tape to a computer equipped

with a frame grabber and multiple classifier

modules. The frame grabber captures and

digitizes the frames of the acquired images.

The multiple classifier module utilizes an image analysis software package to analyze

those digitized frames and processes them in a manner so as to prepare a suitable input (i.e. feature vectors) to each classifier. A solution

strategy is designed to integrate these

classifiers (See Figure 2). The feature vectors

are then fed into the developed system and are accordingly classified into five categories of

defects. These categories are deposits, joint

displacements, cross-sectional reductions,

infiltration and cracks. This paper focuses

primarily on the solution strategy module,

other modules have been presented elsewhere

(Moselhi and Shehab-Eldeen 2000 and 2001).

3. SOLUTION STRATEGY

Neural networks work in an analogous way to human experts. The more focused, i.e. domain

specific, they are, the higher their problem

solving capabilities. In order to express and

demonstrate the importance of specialty in

classification tasks, several classifiers (i.e. neural networks) were developed; each is considered suitable for a certain category of

defects. This was considered advantageous, as opposed to one network that classifies more

than one type of defect. Although diversity of

networks is advantageous, it may lead to a problem in guiding the detected patterns to the

proper channel so as to ensure that each

category of defect is received by the most

suitable specialized classifier. To overcome

this problem a solution strategy is presented to organize data traffic so as to guide the patterns

in an efficient manner and accordingly

improve the performance of the system.

Figure 2 depicts the proposed solution strategy.

As shown in this figure, all images are processed three times. In the first pass (i.e. inverted images), all images are inverted,

dilated, background subtracted, thresholded,

segmented and finally analyzed. In the second

pass (i.e. non-edge detection), images are subjected to the same image processing

techniques except for inversion. In the third

pass (i.e. edge detection), all images are subjected to a number of operations such as background subtraction, edge detection,

dilation, thresholding and analysis. The reason behind subjecting the same videotape to a number of passes is to benefit from all image

processing techniques that are necessary to detect all categories of defects recognizable by

the system.

As can be seen in Figure 2, patterns depicted on images subjected to the first pass (i.e. inverted images) will first be processed by set of networks number 1, specialized in

classifying deposits. These networks will

classify the input data (i.e. patterns) into two

categories: "Deposits" and "Else" (i.e. nondeposits). All patterns classified as "Else" will

be screened based on their X and Y coordinate

and will be further processed by another two

sets of networks (i.e. sets no.2 and 3), each is specialized to deal with a specific set of

defects. Patterns with X and Y coordinates

located only at the center of an image will be

fed into the networks specialized in classifying

cross-sectional reductions and misalignments

(i.e. set no. 2 and 3, respectively). Patterns

classified as "Else" by set # 2 and 3 will be

ignored being either non defects or defects that are not recognizable by the system. It should

be noted that the system recognizes more than

90% of defects that commonly exist in sewer

pipes (Moselhi and Shehab-Eldeen 1999(b)).

Patterns depicted on images subjected to the

second pass (i.e. non-edge detection) will be

fed into the networks specialized in classifying

infiltration (i.e. set no 4). These networks are capable of classifying patterns into two

categories: "Infiltration" and "Else" (i.e. noninfiltration). It should be noted that all patterns

classified as "Else" are considered as either

532
non defects or defects that are not recognizable

by the system.

Patterns depicted on images subjected to the

third pass (i.e. edge detection) will be fed into

the networks specialized in classifying cracks

(i.e. set no 5). These networks are capable of

classifying patterns into two categories:

"Crack" and "Else" (i.e. non-crack). It should

be noted that all patterns classified as "Else"

are considered either non defects or defects

that are not recognizable by the system. It should be noted that each of the five sets consists of three neural networks (Moselhi and

Shehab-Eldeen 2001 and Shehab-Eldeen

2001).

4. EXAMPLE APPLICATION

To demonstrate the use of the developed

system and the capabilities of its solution

strategy module, the image shown in Figure 3 was considered. It should be noted that due to space limitations, the case example will focus

primarily on the third pass (i.e. detection and

classification of deposits using edge detection).

As can be seen, the image depicts a number of

objects. These objects are cracks and a number

of non-defects. To detect and classify these

objects, the image was processed in the same

manner as explained earlier. The image was

segmented as shown in Figures 4. As can be

noticed 15 objects were detected. The feature vectors describing these objects were then fed

into two classifiers. The first is specialized in cracks, while the second was trained to classify

four types of defects: (1) cracks; (2) multiple

cracks; (3) cross-sectional reductions and (4)

misalignments. The results obtained from the

specialized and non-specialized classifiers are shown in Figure 5 and 6, respectively. As can be noticed that the specialized classifier reduced the false alarm for presence of cracks

by 50%. Clearly this finding, while indicative

of benefits of multiple specialized classifiers, can not be generalized.

5. CONCLUSION

An automated system for detection and

classification of defects in sewer pipes has

been presented. The system utilizes image

analysis, solution strategy and multiple

classifier modules to performing its task. To

demonstrate the importance of specialty in classification tasks, several classifiers (i.e. neural networks) v/ere used; each is considered

suitable for a certain category of defects. These

classifiers are specialized in deposits, crosssectional reductions, misalignments,

infiltration and cracks. The paper focused

primarily on presenting a solution strategy that was developed to organize data traffic so as to guide the extracted feature vectors (i.e. signatures) of various defects to a set of

specialized neural networks in an efficient manner. This was carried out in order to improve the overall performance of the

developed system. This was considered

advantageous, as opposed to one network that

classifies more than one type of defect. A case example was also presented.

6. REFERENCES

Moselhi, O. and Shehab-Eldeen, T. (1999)

(a) ,"Automated Detection of Defects in Underground Sewer and Water Pipes." Journal

of Automation in Construction, Elsevier

Science, 8,581-588.

Moselhi, O. and Shehab-Eldeen, T. (1999)

(b) ." An Al-Based System for Detection and

Classification of Defects in Sewers."

Proceedings of INFRA 99 International

Conference, Center for Expertise and Research on Infrastructures in Urban Areas (CERIU),

Montreal, Canada, 3B: 42-54.

Moselhi, O. and Shehab-Eldeen, T. (2000).

"

Classification of Defects in Sewer Pipes Using

Neural Networks." Journal of Infrastructure

Systems, ASCE, 6 (3), 97-105.

Moselhi, O. and Shehab-Eldeen, T. (2001)."

Multiple Classifiers for Automated Detection

of Defects in Sewer Pipes"." Proceeding of

2001 International Conference on

Rehabilitation of Infrastructures, Waterloo,

Canada, 273-278.

Shehab-Eldeen, T. (2001)." An Automated

System for Detection, Classification and

Rehabilitation of Defects in Sewer Pipes." PhD

thesis, Concordia university, Canada.

533
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534
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535
INPUT VIDEOTAPE

Inverted Images

Pass # 1

Non-Inverted Images

Pass #2

Deposits

1 SET#1

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Pass # 3

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(Ignore)

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(Ignore)

Figure 2: Solution Strategy

536
A Concept of the Robotoid Manager with AR

Thomas Bock, Shigeki Ashida

The Chair for Realization and Informatics of Construction

The Faculty of Architecture, Technical University of Munich

Arcisstr. 21 80333 Munich, Germany, Tel. +49-89-289-22100, Fax. +49-89-289-22102

Email: Thomas.bock@bri.ar.tum.de : ashida@bri.ar.tum.de

ABSTRACT: For efficiency, construction managers take care of several job sites simultaneously. In order to be omnipresent, we propose a notification of ubiquitous construction management.

Here we try to adopt the system, so named the Robotoid Manager, with; • AR system with mobile computers

• Message board information system

• Multi schedule optimizing

• Progress monitoring and schedule modification

In addition, we have taken an embedded system into account for a fast and easy recognition of real

situation. Total efficiency of management of several sites is improved.

KEYWORDS: Ubiquitous management, AR (Augmented reality). Message board. Schedule

optimizing. Schedule modification. Embedded system, RFID (Radio Frequency Identification)

1. INTRODUCTION

For efficiency, construction managers recently take

care of several sites simultaneously in many cases.

In order to be omnipresent, we propose a

notification of ubiquitous construction management

by adopting of augmented reality system with

mobile computers.

It is able for a robotoid manager to reduce a time of

transfer to each job-site, and to have coinmunication

better with more people who are not on the site and

even not concerned directly with the construction.

Just-in-time decision and fast information

transmitting will be possible, because of accessing

updated and large volume of data from various

aspects, whenever and wherever he/she is.

There are also a lot of chances to do another task at a different situation while managing. It reduces a

total required time of work.

2. Difficulties

2.1. Differences of situation

Under a ubiquitous management, the situation of

managing may often be quite different from the site. There are also many other disturbances. For

example, there are many people, e.g. in an office,

who are not concerned on the site.

And processes on the site are not recognized

directly. If the manager is always at the site, he/she can supervise all activities. Sometimes it is said that these human senses are most important to make a

best decision. A robotoid manager must recover this lack of recognition as well by using additional

communication devices.

2.2. Confusion of several sites

Different situations of each site may be sometimes

not allocated to the proper site, especially caused by

unexpected apprehension or unclear information.

The manager must always take it into account,

which information belongs to which site. Misunderstandings may sometimes result in a

serious loss of efficiency.

537
3. A concept of the Robotoid Manager

3.1. Possibilities of AR system

Here we can adopt an augmented reality system

(shortly AR) with mobile computers for a robotoid

manager. Many of these systems have been already

introduced in the market; sometimes as wearable

style that means it is easy to carry and use. It provides anywhere a similar vision as that on the

site, and also free from a disturbance in different

surrounding conditions. A robotoid manager can always wear all related data and communication tool

with visual help of AR. AR can also increase

efficiency of communication without oral method.

With an AR system, in addition we can take

following possibilities. • Visual comparison between a plan and a

real progression.

• High visibility

Without a dead angle / Through

obstacles / Inner-structure / Underground / Clear through dense

dusts, darkness, mud, water etc. • Visual help for a consideration

Situation of temperature, Humidity,

; air flow, direction and level of

lighting, smell, sound and others

• Indication for a pointing of position and

time

• Management of construction materials and

parts

• Pre-check of a process and effect simulation

• Communication crossover situations

• For training

In case information should be shared by other

people, it can either be projected on screen or on

each person goggles. For better visibility, a larger screen is necessary, which is harder or more

troublesome to carry. Then a useful indication

device, for example a mobile or wearable beamer,

should be the best combination.

3.2. Message board information system

A manager must always be aware of a present

situation, which changes time to time, in order to make a just-in-time decision. Therefore it is better to use real time data and their recent previous related

actions, instead of using too much stored data. Too

much data require many capacity of computer

server, and they are sometimes never used anymore.

And also it requires for a manager complicate

searching, comparing and selecting the proper data.

To get real new data while classifying, message

board information system (Fig.l) is a practical

method. This method means to gather opinions of

all workers at each site at the real time. Due to the use of this system, we can spare sub managers on

various site. An Internet message board system with

a mobile communication device has been already

used. So almost all worker on site can use this system easily without any complicate installation or any expensive devices.

Sites

site A Topics \

site B schedule

site C material

| site D operation

site E ^ \working time

site F

^ \

taking a rest others

Move to top of the list

Opinions / operation / site A

- 1 think it is better to ... newest

- 1 don't think so ... 23:00 13,05

- It is going very well because ... 22:53 13,05

- What can we do under such a ... 21:34 13,05

- Hey! Where are you, Mr. Manager?! 17:03 13,05

- We have a problem with ... 08:55 12,05

Fig.l. Message board information system

538
same time

optimized

Sequence A

Optimized

schedule

T, MI) •

Sequence B

Critical sequence

o time

Flexible sequence o Decision required node

Fig.2. A concept of multi schedule optimizing

Each information is already classified by its site and

topic (interest). Always newest information is listed up at the top. Opinions of both "goes good" and

"problem, decision required" can be collected at the

real time. Special topics, in which the workers on

site are actually interested, occur naturally in the

message board by themselves. The more they are

interested in a topic, the more arguments about the

topic are listed. This is an indication of the necessity

for a manager to take action or to be alert.

This system is effective not only collecting

opinions, but also informing a decision of the

manager.

Tf=(t,-te)-T, (1)

Here, Tf : a flexible time, ti : the latest time to be

allowed, tg : the earliest time to be able to start, : a preset required time

When Tf=0, then the sequence is critical and the

decision for the next sequence must be prepared

before the time of

ti in order not to make delay of total construction

period. A concept image of multi schedule

optimizing is shown as a part of arrow diagram in Fig. 2.

3.3. Optimizing the combination of each other site

While sequences on several sites are progressing in

parallel, and when some of them are a decision

required at one time, the rest of them must be wait

for a decision. So it is the best that there comes

always one decision required sequence after another. A combination between automated

sequences and decision required sequences should

be optimized automatically with a multi schedule

optimizing method.

All sequences are related each other owing to its order and required time. It is indicated as an arrow

diagram. A progress is monitored and its criticality

of time is considered. A flexibility of the sequence

is evaluated as follows;

And the optimized schedules are always possible to be indicated on this managing system.

3.4. Modification of a preset schedule

In case of an unpredicted disturbance or change of

the condition, the manager must realize its pre- signal and make a better decision as soon as possible.

For a changed situation, the schedule of each site must always be modified with an analysis of the

trend. We can take te into account at this modification as follows;

te(n) = te(n-l) + Tp(+Tu) (2)

539
Here, te(n) : tg of the sequence "n", te(n-l) : tg of the

previous sequence of "n", Tp : a required time which

is predicted from a real progress of the sequence, Tu

: a required time of the unscheduled sequence (if

necessary)

The index tg is always rewrote owing to a monitoring of the progress. Rewriting concept is shown in Fig. 3. Tp is predicted by comparing a progress with a preset required time. There may be

also a case that an unscheduled sequence becomes

necessary.

And the optimizing of a combination, which is described before, is repeated over and over

automatically for all these modification to make the

total efficiency higher. This system indicates all better possibilities up to this optimizing whenever a decision is required for a ubiquitous manager.

Fig. 3. Rewriting concept on the modiflcation

4. Situation recognizing with embedded system

4.1. Installation of RFID

All decisions should be always made regarding a

present requirement. Making a decision effectively

we analyse the present situation and refer the

consolidated findings in the future.

3D scanning with AR is one of the best methods to grasp the real situation. AR itself with wearable

computers has also already been popular. But in the use of AR for 3D scanning, there are still some

technical and practical difficulties to realize. It is sometimes expensive, inexact and time for

scanning is required. Also it is still hard to carry or wear the equipment easily, for example still many

devices are required as that for recognizing self position. Therefore an accepted technique method

only with visual 3D scanning for every concerned

site is not practice to use, at the moment.

On the other hand, RFID (Radio Frequency

Identification) is one of the popular identification

methods. The chip is embedded in all objects at each site containing its specific data. The scanner

for this system is in most of the cases easy to carry or wear.

4.2. Concept of recognizing

We are here trying to adopt an embedded system

with RFID and AR system with mobile computers

for recognizing of sites to a robotoid manager.

Specific data of all objects at the site are preliminary registered and embedded with RFID

chip. In case, more detail data must be stored, the

identification is related to data bank automatically

(Fig. 4).

540
Objects

- worker Data

- structure j automatically - function

- material R related - date of installation -tool F N

- to whom belongs

- atmosphere 1 - data of appearance

- machine D - position

- papers

Fig. 4. Embedded data

With RFID all objects on the site in the radio

effective distance are identified at the same time

and grasped its specifications fast and easily. The

visual situation, which means position, wearing,

movement and others, is shown virtually with AR,

like as Fig. 5. The manager can take also an

invisible object into account. The ability of RFID

for rewriting is important as well. On the view of

AR, a robotoid manager compares the real present

situation with the virtual view, which made from

pre registered RFID data (Fig. 5). Then the

difference is rewritten on RFID system.

5. Future work

This trial is still just a concept. There has been no

real adoption yet. We must think furthermore about

the realization. The concrete systems should be

created and combined at its best. And of course its efficiency must be confirmed with some case study

or practical adoption.

Furthermore this method will be used in many other

kind of management, for example buildings,

facilities, infrastructures and others. Therefore this method should be not only used to analyse the

construction site, but also included into total system

of management to be used effectively. We will try to implement such a robotoid management system with

AR.

a) real situation b) scheduled situation

Fig.5. Comparison on the view of AR

541

Representation and Integration of As-Built Information to IFC Based Product and

Process Models for Automated Assessment of As-Built Conditions

Burcu Akinci\ Frank Boukamp^

ABSTRACT: Frequent assessment of as-built conditions is necessary for active project control

during construction. Assessment of as-built conditions involves collecting accurate as-built

information and comparing the as-built information collected with given design and schedule

information. Currently, different technologies exist for collecting accurate and comprehensive

as-built information. The as-built information generated through these technologies is then

manually evaluated by comparing it to the design information. This process is time-consuming

and error prone. Therefore, there is a need for an automated assessment of as-built conditions.

This paper discusses the applicability of the Industry Foundation Classes (IFC) in their current version 2x to support the assessment of as-built conditions of construction projects. The goal is to create a project model that represents and integrates as-built and design information. In this paper, we state different types of information that need to be represented in this integrated

model, describe common ways of representing this information in IFC Rel.2x, and highlight the

limitations of current IFC Rel.2x specifications in representing an integrated design and as-built

model. The paper concludes with a proposal for extending the IFC specifications to enable the

automated assessment of as-built conditions.

KEYWORDS: Industry Foundation Classes, integrated design and as-built models, construction

1. Introduction

Frequent and comprehensive assessment of

as-built conditions is necessary for project

control and to minimize delays caused by

late detection of defects at construction sites. A comprehensive assessment of as-built

conditions involves frequent, complete and

accurate collection and storing of data on asbuilt conditions, and a formalized approach

for comparing the as-built conditions with

the as-designed requirements.

Different technologies can now enable the

frequent, complete and accurate collection

of as-built conditions. For example, laser- scanning technologies are gaining

acceptance in the A/E/C (Architecture/

Engineering/Construction) industry because

of their ability to create complete and

accurate 3D as-built environment models

based on spatial information [1]. However,

' Assist. Prof., Dept. of Civil and Environ. Eng.,

Carnegie Mellon University, Pittsburgh, PA

15213. bakinci@cmu.edu

' Research Assist., Dept. of Civil and Environ.

Eng., Carnegie Mellon University, Pittsburgh,

PA 15213, boukamp@cmu.edu

currently, even if a laser scanner is used at a

construction site, the comparison of as-built

models with existing design information is

still being performed manually by visually

inspecting both design and as-built

information according to a construction

schedule and design specifications [2]. This

process is time-consuming and error prone.

Therefore, there is a need for an automated

assessment of as-built conditions.

To automate the assessment of as-built

conditions, the as-built information,

consisting of as-built product model and

schedule, needs to be integrated with the as- designed product and process information.

Both as-built and as-designed models need

to be represented in a semantically rich way

and the necessary relationships between

these two models need to be created and

maintained throughout construction.

This paper discusses possible ways to integrate as-built information within IFC

(Industry Foundation Classes) based product

and process models, and evaluates the IFC

Rel.2x specifications in terms of its ability to represent integrated design and as-built

information. The discussions in this paper

543
are based on the implementation of a small

portion of a warehouse construction case.

2. Background

Currently different industry efforts exist for

modeling and merging design, construction

and FM (facility management) information.

For example, the Steel Construction Institute

is developing CIMsteel Integration

Standards (CIS), a framework for modeling

construction projects that are mainly based on steel structures. The goal of this effort is to "allow software vendors to make their

engineering applications mutually

compatible" [3]. As another example, the

International Alliance for Interoperability

(lAI) is developing the Industry Foundation

Classes (IFC), a similar framework that shall allow making A/E/C and FM related

information exchangeable between different

software programs by standardizing the

representation of A/E/C and FM related

information within project model

descriptions. In our research, we decided to use the IFC representation since it does not focus on only one specific industry and

hence it is more generally applicable.

Currently IFC models are either used to store design or as-built information. Often an IFC-based design model is created and

later on updated with as-built information,

overwriting the designed information. To

allow the storage of different versions of a

project, like 'Schematic Design", 'Detailed

Design', 'As-Built', etc. these models are usually stored into different files, which then

are associated with the description of the

version. For example Metracker, a performance metric tracking tool, uses this approach [4].

To be able to automate the assessment of asbuilt conditions efficiently, we need to represent detailed design information and

as-built information in one IFC model. An

integrated representation of design and asbuilt models allows to identify and reason about the relationships between design

model and as-built model efficiently, and

hence minimizes the computational efforts

associated with checking one model with the

other to assess as-built conditions.

Section 4 of this paper describes how we

build on and extend the current IFC Rel.2x

specifications to develop an integrated

design and as-built model for the case that we implemented.

3. Case Study Description

In November 2001, we performed a case study at a warehouse construction project in Pittsburgh, PA, where we collected design

and schedule information through

conventional methods and as-built

information through laser scanners. The

main structure of the warehouse consists of

steel frames. We modeled the design and asbuilt information of one of the steel frames

using IFC Rel.2x to automate the assessment

of as-built conditions for that frame.

Assessment of as-built conditions in the

frame example involves comparing the as- designed and the as-built geometric, material

and schedule information. Figure 1 shows

the design and as-built information of the

frame that we modeled. In this case, the contractor used the right material and built it in the right location. However, the as-built

schedule deviated from the as-designed.

Hence, an automated assessment system

should be able to compare the different

types of information represented in as- design and as-built model and identify the

schedule deviation in this case.

4. Integrating Design and as-built

Information Using IFC

Since the assessment of as-built conditions

requires reasoning about material

information, building element type

information, geometric information,

scheduling information and relationships

between building elements, we need to explicitly represent this information. In IFC

Rel.2x it is usually represented as follows:

Material information is usually

assigned to the respective IfcObject-ohject,

544
through a relationship called

IfcRelAssociatesMaterial (Figure 2).

Building element type information is usually modeled through properties or type

libraries defined by relationships of type

IfcRelDefinesByProperties (Figure 3) or IfcRelDefinesByType (Figure 4)

respectively.

Geometric information is modeled by

grouping IfcRepresentation-ohjects in an

IfcProductRepresentation-ohject that is then

assigned to a building object (Figure 5) or through properties providing geometric

information being assigned to an IfcObjectobject by an IfcRelDefinesByProperties

relationship (Figure 6).

Scheduling information is represented

in IFC by assigning an IfcTask-ob]tci,

representing a task in a schedule, to an

IfcObject-oh]&c\., via a relationship of type

IfcRelAssignsToProcess (Figure 7).

Connections between building

ELEMENTS are modeled by using

IfcRelConnectsElements relationships.

As stated before, IFCs were developed to allow the representation of either design or

as-built information in an interoperable

product model. When trying to incorporate

both into one model, three scenarios might

be observed [5]:

1. The current IFC model representations

should be used if possible.

2. The current IFC model representations can be extended if necessary.

3. New concepts are developed only if a

sufficient representation cannot be

created using scenarios 1 and 2.

Since minimal changes to the IFC model are

desirable, first we tried to use existing

representations to integrate the as-built information into the IFC-based model and

then suggested extension to the current representations before we develop any new

representation schema.

4. 1 Utilization of current IFC Rel.2x

Representations

Three approaches seemed promising in representing iniegrated as-designed and asbuilt information using the current IFC

Rel.2x specifications:

(1) Utilization of representation context concept defined through

IfcRepresentation Context. IfcRepresentationContext objects, to which

product representations can be assigned,

allow products to have different

representations, e.g. one that represents a sketch of the product and one that represents

the detailed design of the product. To do

this, the ContextType attribute of this object

is being proposed to be used to store different context information such as 'Sketch' and 'Design' to distinguish

between the different contexts. By using

'Design' and 'AsBuilt' as values for. this attribute we would be able to create two

different representation contexts for a building element to which we can assign

design and as-built information respectively.

This would allow having the design and asbuilt information incorporated into one IFCbased product model. Currently, only

IfcRepresentation objects can be assigned to an IfcRepresentationContext. As a result,

only geometric or topologic information can

be assigned to these different contexts. However, as we discussed in the case study,

other information, such as scheduling

information, will also have to be kept in distinguishable design and as-built contexts. The usage of different

IfcRepresentationContexts thus becomes

insufficient for our purposes.

(2) Utilization of logical grouping concept

to group as-designed and as-built information. lAI provides the possibility to group

information by using IfcGroup-ohjects.

Based on this, we can group design

information and as-built information in a design-group or an as-built-group through

the assignment of the information to the

respective IfcGroup-ohject (Figure 8). The

545
design and as-built information can be

assigned to the respective groups by using

IfcRelAssignsToGroup relationships. The

IfcRelAssignsToGroup-ve\dX\ox\s\\\T() is a subtype of //c^eM55/^n5-relationships,

which can only link subtypes of IfcObject

among each other. This creates a problem

for representing designed and as-built

material information using

IfcMaterialProperties-ohiects which are not derived from IfcObject. Since it is important

to represent and reason about the material

information in design and as-built models,

the IfcGroup-hased approach becomes

inadequate for our purposes.

(3) Creation of new properties of entities using IfcProperty object.

This would involve the creation of

IfcProperty-objects having a specific value

in its A^am^-attribute which tells whether it describes design or as-built information.

These IfcProperty-ohjects then will be

assigned to the related entities through an

IfcRelDefinesByProperties-relationship . The

usage of properties for extending IFC

concepts is the most common technique

used. Currently properties can only be

assigned to objects derived from the class IfcObject. This again creates a limitation of

the usability of this concept for our

purposes, since in IFC for example material

information or relationships in general are not derived from IfcObject.

4.2. Extended Concepts

Since the current IFC Rel.2x specifications

do not allow us to model the as-built

conditions completely we investigated other

ways to incorporate design and as-built

information into one project model with

minimal extension of existing IFC concepts.

Extending the concept of reified

relationships looked most promising for our

purposes. Most of the information that we

need to model to support automated

assessment of as-built conditions is assigned

through relationships to the objects (Figures

2-4, 6, 7). All of these relationships are represented as instances of classes that are

derived from the superclass IfcRelationship.

Thus, if we add a new attribute called

Context to the IfcRelationship-cldLSS, then we

can use that attribute to determine whether

the information is related to the design or the

as-built context. This Context-aitrihute

should be of type IfcLabel and have a

descriptive name, e.g. 'Design' or 'AsBuilt',

assigned as value.

To enable the interoperability of the model,

it is necessary to standardize these values

that will be assigned to the contextdistinguishing attributes. Otherwise,

software developers using IFCs will have to agree on how to describe the different contexts to be able to interpret the models

that are interchanged using their software.

Enabling the class IfcRelationship to describe the context it is assigned to through

the new Context-QWx'ibnit allows us to keep

nearly all the information that we need for

automated defect detection in separate

contexts, i.e. a design and an as-built context. This is because all the information

is assigned through subtypes of

IfcRelationship to the entities in the IFC

model (Figures 2-4, 6, 7). With this extension we can provide a 'Design'

relationship to the design information of an

element and an 'AsBuilt' -relationship to the

respective as-built information of an

element.

However, this extension of the IFC concept

of objectified relationships is not entirely

sufficient, since the geometric information is the only information that may not be

assigned to an object through a relationship

but may also be described through

IfcRepresentation-oh]QCts that are directly

assigned to the element not using

IfcRelationship-ohjects.

4.3. Proposed Concept

In the previous two sections, we described

four different approaches to incorporate

design and as-built information into one

integrated model:

- using IfcRepresentationContext-objects

546
- using //cGroMp-objects

- using new IfcProperty-obiects

- using an extended version of

IfcRelationship

All of these approaches, when used alone,

are insufficient for the purpose of automated

as-built assessment. Instead of creating a completely new concept for the integration

of design and as-built information into one

IFC-based project model, we propose

combining two of the approaches described

above as the proposed way of modeling as- designed and as-built information in an

integrated way.

Our proposed approach combines utilization of different IfcRepresentationContextobjects and extending the class IfcRelationship as explained before (see

Figure 9).

The weakness of the concept of extending

the class IfcRelationship was that the part of

the geometric information that is described

through IfcRepresentation-oh]tcis, cannot be

distinguished by using 'Design'- and

'AsBuilt' -relationships. This weakness can be overcome by the usage of different

IfcRepresentationContext-ohjects. The

IfcRepresentation-ohjects, representing the

geometric information of the entities in the

IFC model, are assigned to a 'Designed*- or

'AsBuilt' -representation context. All the other information will be assigned to the

entities through objectified relationships that are defined through our extended version of

the IfcRelationship-dsLSS, which makes the

information distinguishable.

5. Conclusions

The current release 2x of the EFC

specifications have limitations in modeling

as-designed and as-built information into one project model to support the automation

of as-built conditions. It is necessary to extend the current IPC representation

without increasing the complexity

unnecessarily from both an

understandability and a processability point

of view.

For the purpose of allowing IFCs to represent both design and as-built

information in one project model

simultaneously, v/e propose a solution that allows for fast processing of the IFC model

without increasing the complexity of the

IFCs. This was accomplished through the

utilization of the IfcRepresentationContext

concept in IFCs and adding a new attribute to the IfcRelationship class. We have tested this approach in automating

the as-built assessment of the construction of

a steel frame that we observed on a recent

project. We will further test the scalability

of this concept by adding different types of

design, schedule and as-built information

that we are going to collect in an upcoming

construction project.

6. Acknowledgements

The project is funded by a grant from the

National Science Foundation, CMS

#0121549. NSFs support is gratefully

acknowledged. Any opinions, findings,

conclusions or recommendations presented

in this paper are those of authors and do not

necessarily reflect the views of the National

Science Foundation.

7. References

[1] Cyra Technologies, Inc. Case Studies;

http://www.cyra.com/case_studies/case_stud

ies.html (accessed: 06/2002)

[2] Cyra Technologies, Inc. Cyra Case

Studies: Condition Assessment of Old

Suspension Pipeline Bridge; 1999;

http://www.cyra.com/PDFs/PipelineBridge.

pdf (downloaded: 06/2002)

[3] The Steel Construction Inst. CIMsteel

Integration Standards, Rel. 2, Vol. I, Ov^rv/ew;http://www.cis2.org/documents/

Voll/SCI-P265on.pdf (06/2002)

[4] R. J. Hitchcock, M. A. Piette, S. E. Selkowitz: Documenting Performance

Metrics in a Building Life-cycle Information

System; Building Technologies Depart.,

Lawrence Berkeley National Lab., Univ. of

California, Berkeley, CA, August

547
1998;http://eande.lbl.gov/BTP/

papers/4 1942.pdf (downloaded: 06/2002)

[5] lAI: IFC 2x Extension Modeling Guide;

http://cig.bre.co.uk/iai_uk/documentation/

Ifc2x_EMG/EMG-Base.htm (06/2002)

[6] T. Froese, M. Fischer, F. Goebler, J. Ritzenthaler, K. Yu, S. Sutherland, S. Staub, B. Akinci, R. Akbas, B. Koo, A. Barron, J. Kunz: Industry Foundation Classes for

Project Management - A Trial

Implementation; FTcon Vol. 4 (1999);

http://www.itcon.Org/1999/2/paper.pdf

(downloaded: 06/2002)

Figures:

Materials; Column 1: Steel ASTM A3E Column 2: Steel ASTM A3e Beam 1 : Steel ASTM A36 Beam 2: Steel ASTM A36

m task

t ©reel column 1 J erecl column 2 Z. place beams

design information of a steel frame u

Comparison

Materials; Column 1; Steel ASTM A3« Column 2; Steel ASTM A36 Beam 1; Steel ASTM A36 Beam 2: Steel ASTM A3S

to

1 ered column 1 2 erect column 2

place beams

as-built information of a steel frame

Figure 1: The design and as-built information of a steel frame.

ColumnJ : IfcColumn

Column_1_Geonietry

IfcProductRepresentation

Column_1_GeometryRep

KcRepresentation

Figure 5: Representation of geometric

information as a group of

representation items.

Column_1

llcColuinn

RelGeoCI : IfcRelDefinesByPropertiesCIGeometricProperty

HcPropeitySet

Figure 6: Representation of geometric

information through property sets.

Column_1 : tfcColumn RelTaskCI : IfcRelAssignsToProcess

Erect_C1 : IfcTask

Figure 7: Representation of scheduling

information to a column.

DeslgnGroup : AssignToDesign : IfcGroup IfcRel/teslgnsToGroup

Column_1 : IfcColumn

RelTaskCI designed : IfcRelAssignsToProcess Erect_C1 .designed : tfcTask

RelTaskClasBuilt

IfcRelAssignsToProcess

Erect_C1_asbullt

;

HcTask

AsBulltGroup : AssignToAsBullt

IfcGroup KcRelAssignsToGroup

Figure 8: Representation of design and as- built information through groups.

Column_1 : RelMatCI : MaterialCI : IfcColumn IfcRelAssociatesMaterial IfcMaterial

Figure 2: Representation of material

information of a column.

Column_1 : RelTypeCI : TypePropertyCI : IfcColumn o—

o

IfcRelDefinesByProperties IfcPropertySet

Figure 3: Representation of element type

information through property sets.

Column_1 : IfcColumn RelTypeCI : IfcRelDefinesByType

TypeCI : IfcTypeObject

Figure 4: Representation of element type

through predefined types.

548
RelMatCI

:

—Cj HcRelAssociatesMaterial

Context = "AsBuilt"

MaterialCI

:

tfcMaterial

RelMatCI : tfcRelAssociatesMaterial

Contert = "Design"

MaterialCI

:

tfcMaterial

DesignContext

:

HcRepresentationContext

ContextType = "AsBuilt"

LA

Column_1.Geometry Rep

IfcRepresentation

CdumnJ : HcCotumnColumn^1_Geometiy

:

HcProductRepresentation

Column i GeometryRcp

:

HcRepresentation

ReTTaskCI

:

IfcRelAssignsToProcess

Conleil = "AsBuilt"

Ere<:t_C1

:

IfcTask

RefTaskCI

:

-Cj HcRelAssignsToProeess

ContexT "Design"

Erect_C1 : IfcTask

AsBuiltComexl

:

tfcRepresentationContext

ConteirtTvpe - "DesiqiT

Figure 9: The proposed concept.

549

A Case Study: Using The Wearable Computer In The Construction Industry

by

Scott Fuller, Zhihui Ding, and Anoop Sattineni

ABSTRACT: This paper aims to explore the prospective applications of cuttingedge technology like wearable computers in construction industry. The history, current research, application areas and future trends of wearable computing are

investigated. The first-hand experience of the authors through a well-designed

field experiment is introduced in detail to show how the technologies actually

work. The field experiment is performed using three different methods, including

by hand, by Palm PC and by wearable computer. The pros and cons for each are analyzed and compared to reveal why wearable computer is a better tool to help

construction professionals to perform their daily duties like "punch-list". The

results in summary showed that in immediate future, wearable computer is a better solution for construction than Palm PCs. But the advocates of the wearable

computer should always bear in mind that the technologies are always developing.

Palm PCs are still expanding their functionality while maintaining the mobility. It

is not impossible that tomorrow they could have the same storage and processing

capacities as wearable computers today. So Palm PCs are going to be strong

competitors of wearable computer.

KEYWORDS: Construction, Palm PC, Punch List, Wearable Computers

1. INTRODUCTION:

The construction industry is on the edge of

something that could drastically improve the

entire construction process. Recently, a new

kind of computer has caught the public

attention, a 'wearable computer': a computer

that can be worn on a human body. Its mobility

and functionality has made it useful in many

places where a regular computer could not be

carried. This "...has the ability to bridge

time/distance constraints imposed by working

at remote construction projects... the

opportunity for real-time decision making in construction is improved." '

2. LITERATURE REVIEW

Through the extensive research, the authors

found the term "wearable computer" has been

defined in several ways. For example,

according to MIT wearable computing lab,

wearable computer is a computer that should

be worn much as "eyeglasses or clothing", and

interact with the user based on the context of

' Mills and Beliveau, 1998

the situation. With features like heads-up

displays, unobtrusive input devices, and

personal wireless local area networks, the

wearable computer can act as an intelligent

assistant. NASA (National Aeronautics and

Space Administration) used the term Body

Wearable Computer (BWC), which is a battery-powered computer system worn on the

user's body. And the unit is designed for

mobile and predominantly hands-free

operations, often incorporating head-mounted

displays and speech input.'

Today, there are a lot of commercial wearable

computing systems available in the market.

Some prototypes require special glasses, while

others rely on sensors similar to medical

electrodes on various body parts to feed data to the computer. The differences depend on the

purpose of each system. Among all systems,

Xybemaut Corporation is one of the largest

sellers, partly because it has locked up a big

Auburn University, Department of Building

Science, 1 19 Dudley Hall, Auburn, Alabama

36849, 334-844-5431, fulleds@aubum.edu

- Mizrachi, 2000

551
chunk of the patents.'' Figure 1 shows Mobile

Assistant V, one member of Xybemaut

wearable computer family.

In summary, wearable computers are more

powerful, durable than laptop/palm computers,

but more convenient to use than desktop PCs."* As Ed Newman, chairman and CEO of

Xybernaut, said, "We're not talking about a Windows CE device; we're not talking about a PDA, we're talking about a product that

literally will run anything your laptop or desktop will run with almost no change."

Wearable computers are able to run "all the

programs on a PC", including word

processing, spreadsheets, and databases, but in a more efficient way.^

Today, wearable computers are not stagnating

at the laboratory and exotic-toy stage.

Instead, they are finding wide use in the real world. For Xybemaut alone, its current customers include many companies that have

large field forces, such as FedEx Corp., Bell

Canada, and the U.S. Army and Navy, to name

a few.^

FIATECH, a research and development firm,

has a two-year goal to introduce wearable

computers to the construction industry.

FIATECH will record the activities of people

in the field to understand how their work is done and how it can best be improved through

the use of a wearable computer.^

One of the major issues with the construction

industry is that the production activity is dispersed and the site locations frequently

change. This is a disadvantage for the

construction industry that most other industries

do not have. This makes IT support and

integration for the construction industry more

difficult.^ This in turn makes it a great

candidate for the wearable computer or mobile

computing. In addition, effective

communications is the most important

component for successful projects.

Communication between the participants on a

^ Maney, 2001

Merritt, 2001

^ Mizrachi, 2000

^ Mizrachi, 2000

^ Neel. 2000

* Newland and Owings, 2001

^ Rebolj, Magdic, and Cus-Babic, 2000

job site is difficult, due to the large number of

participants, their remote locations, the visual nature of many issues/solutions, the number of

problems that arise at the site and the need for

them to be solved on-site. However, it is also

exactly these kinds of issues that might make

the wearable computer a very effective,

efficient, useful and beneficial tool for

construction.'"

Certainly for the construction industry the

wearable computers and all attached devices

must be accessible, lightweight, and easy to use. They must be able to withstand all types

of weather and environmental conditions. For

example, the screen should be readable in all types of lighting, the computer should be

impact resistant, have rechargeable batteries

and a host of other functions and ergonomic

features. "

'^Mills and Beliveau proposed the idea of

"Virtual Site Visit" using wearable computers.

A "Virtual Visit" is a visit to a construction site to observe, evaluate, clarify and correct actions

and activities, but it occurs without the

individual's actual physical presence. This is of

great benefit when it is impossible to visit the

site and will diminish project delays. The

reduction in travel time and increased project

knowledge translates into immediate cost savings to the contractor, owner and designer.

Just as Jim Porter, with Dupont says, "In today's competitive environment, we need to be able to access data, drawings, and other

information on demand remotely at the

construction site. Wearable computers will allow us to do this."

'"^

Essential to using advanced computing

technology for field decision making is an

understanding of the jobsite informational

needs. Research on using wireless

communications for construction information

needs has been undertaken and reported by the

Construction Industry Institute.

'"^

Two of the authors conducted a preliminary

survey with some construction firms. The

'°Miah, et al, 1998

" Newland and Owings, 2001

Mills and Beliveau, 1998

Newland and Owings, 2001

De la Garza, et al, 1997

552
purpose of the survey was to investigate the

potential uses for the wearable computer

technology and the interest in the industry.

The survey indicated that the construction

industry is already using information

technology to improve performance on

projects. It also showed that an enormous amount of data is recorded on the job site by

construction personnel. All respondents

indicated that they would be willing to experiment with wearable computer

technology, thus indicating that there is a tremendous potential for the success of

wearable computer technology.

3. METHODOLOGY

The objective of this research project is to test the wearable computer in a real-life situation in construction to see how technology could help

construction professionals. For example,

compare the different time periods required to perform the same amount of work, under

different methods including by hand, by Palm

PC or by wearable computer.

In order to do so, first the author should have a wearable computer system configured and use

it extensively to get to know it well. Secondly,

the author should identify a testing area where

experiments with such appropriate scale could

be performed to "mock" the real-life situation. Lastly, putting the two aspects together, the

author should design a testing scheme and

further configure the wearable computer

system for the testing purpose.

The wearable computer used in research will come from Department of Building Science,

Auburn University. This Xynemaut computer,

the Mobile Assistant V (MA V), will contain a 500-MHz Intel Celeron processor, 128-MB of

RAM, and a 2-GB hard drive that can be worn

in a vest or on a belt. It will be able to run all major PC operating systems, including

Windows 2000/NT and Linux. The MA V will also incorporate a daylight-viewable, headmounted display or a wrist-mounted SVGA

flat panel touch-screen viewable in all light levels. Interaction with the computer will be

made via a wrist-worn keyboard, touch-screen,

or voice recognition software.

The following lists three ways that we

proposed to test the wearable computer for construction applications: 1. Traditional

Manual Method, 2. Palm-size PC, 3. Wearable

computer.

In our testing, the actual situation might vary

from the above. However, at least, the following conditions must be met, before

performing research related to punch list: a

building should be identified and available for research purpose; drawings (traditional

blueprints or electronic format), specifications

(or scope statement ) should be made

available; the author should develop sample

checklist and punch list for field use; technical

tools, such as Palm-Size PC, wearable

computers, should be well-configured before

hand; and bring some accessories, like stop

watch to record time, pens and paper.

4. RESULTS

4. 1 Field Testing

The author selected Intramural Fieldhouse at Auburn University as the target building for

carrying out the "Punch-list" experiment.

Based on the information from drawings and

specifications, a sample checklist and punchlist were first developed in MS Excel

spreadsheet and Word document format,

respectively. Then three trips were made

separately to perform the building inspection,

by hand, by Palm PC and by wearable

computer. Plumbing and electrical systems were the primary emphases, but interior finishes and furniture were also included. The

process is defined as from the time when the

author entered the building to the time when

the checklist and punch list were completed.

From the experience in performing the "punchlist", the author summarized the pros and cons

for each method, as in Table 1

Firstly, the advantage for using mobile

computing device over manual method is quite

apparent. Whether using Palm PC or wearable

computer, when the punch list is done, it will be sent through e-mail instantly. But with the

manual method, the superintendent will have

to come back, find a desktop PC, and manually

put all information into a computerized system

553
(or scan in the paper form) to be sent via e- mail to subcontractors at the same day.

If we assume the distance between the jobsite

and home office is two miles, the additional

travel time and data input time, in our case,

will be approximately 20 minutes. In real life, the travel time will be even significantly

longer. So if assuming the added time for

communicating the punch list to subcontractors

is one hour under the manual method, the

above timetable should be adjusted as Table 2

indicates. Now one could see clearly that using

computerized methods, the problem of "double

data entry" and delivery time could be

eliminated, thus significantly improving the

efficiency.

In our experiment, the electronic drawings are around 20 MB in total. This was not a big issue

for our wearable computer, which has two hard

drives (2 GB in total storage capacity). But it was a huge burden for our Palm PC, which

only has 8 MB storage. So our experiment

reveals that wearable computer did outperform

Palm PCs in storage capacity, with or without

external devices.

4.2 Data Access

With wearable computer, the electronic

drawings were loaded as well as electronic

version of checklist and punch-list, all that the

author needed to do is to carry the wearable

computer around. It should be noted that in our

experiment, the idea of electronic drawings

didn't apply to the manual method or Palm PC

at all. That is because Palm PCs do not have

the power to manipulate electronic drawings.

Even within the near future, this situation is not very likely to change, considering the fact that the drawing viewing tool itself alone will

take more than 4 MB and doesn't work with

Palm PC at all.

4.3 Data Processing

Wearable computers don't require special

applications loaded in order to process data. But Palm PCs will require special software to perform the same tasks., like Pocket Microsoft

Office (Pocket Word, Pocket Excel, Pocket

Access etc). This software costs the same

price, if not more, as the standard software

does. In addition, some features in regular

applications will be unavailable in the software

designed for Palm PCs. In this experiment, the

authors was able to add a password-protected

digital signature to the punch list when using

wearable computer. But using Palm PC, the

document was converted to Word Pad text file, and all macros were lost. In addition, the

software installation process is also more

complicated for Palm

4.4 Data Synchronization

An important issue for mobile computing

devices is how the data on them could be

communicated back and forth into the current corporate network, which is almost exclusively

based on a group of desktop workstations.

Although our experiment finished when punch

lists were complete, in real life, all data on

wearable computer or Palm PC must be finally

backed up and updated. E-mail is fine for

exchanging small files like the punch list as a Microsoft Word document in our experiment.

But for larger files, other solutions must be

sought.

For Palm PC, as described earlier, this relies on the communication between Palm PC and a desktop PC. First prepare desktop PC for

synchronization purpose by installing special

utility software like Microsoft ActiveSync on

it. Then connect Palm PC with desktop PC by

using a cable. Activate Microsoft ActiveSync

or other similar program, and the data between

the two will be exchanged or updated. Except

for the first time, which requires software

installation, all one has to do is connect the

cable and click the button.

In our experiment, the solution for wearable

computer was "Sneak Net", i.e. transporting

data via 3-1/2" floppy-disks with the help of

related USB devices. But even by that,

wearable computers still outperform Palms in

this aspect, because the USB devices are basically mechanical operated (Plug-PlayUnplug) and easy to bring with wearable

computers.

From the discussion above, it seems that within the near future, wearable computer is a

better solution for construction than Palm PCs.

But the advocates of wearable computer

should always bear in mind that the

technologies are always developing. Palm PCs

554
are still expanding their functionality while

maintaining the mobility. It is not impossible

that tomorrow they could have the same

storage and processing capacities as wearable

computers today. So Palm PCs are going to be

strong competitors of wearable computer.

5. CONCLUSIONS:

For wearable computers, a lot of things could

be done. Especially, one should look at the

strengths of Palm PCs to improve the

performance. For example, wearable

computers could be made smaller in size,

easier to carry, having lighter CPU or even

integrating CPU with monitor into one unit etc.

In our experiment, the punch list and checklist

files were first edited in a desktop computer,

and then saved to a floppy disk to be later transferred to wearable computer. This is the

"Sneak Net" process we talked about earlier. But in construction, the needs for data updates

between office and field could be very frequent

and heavy. Thus the data synchronization

process described above could be so labor

intensive and time consuming for anyone.

Ideally, the wearable computer will be a workstation ("Client") in the corporate client- server networking environment. Just like a normal desktop PC, a wearable computer could

download file from, and also upload files to, the company server. It will have Internet access via the corporate server. Considering

the diverse nature of the construction industry,

the wearable computers could be configured

into wireless communication mode. The

limitations for current wireless technology

could be overcome by setting up a small-scale

LAN in each jobsite, where the local server in the trailer could directly meet the needs of

mobile devices by communicating the

company server. However, the costs for

establishing such networks and maintaining

them could be so prohibitively expensive for any contractor. Some recent innovations in IT

industry like ASP (Application Service

Provider) might provide better solutions to such problem.

In addition to the issues discussed above, some

technologies that are supposed to work with

wearable computers, like speech recognition

and head-mount display, are far from mature to

be applied in construction industry in a

significant scale.

In summary, the application of wearable

computers in construction industry could offer improved efficiency. But the future researchers

and developers should improve the

performance and practicability of the

technology before it is widely accepted by

construction industry professionals.

6. REFERENCES:

De la Garza, Jesus M., Howitt, Ivan. Wireless

Communication and Computing at the

Construction Jobsite. Construction Industry

Institute Research Summary 136-1, 1997.

Maney, K. (2001, April 18). Wearable PCs:

A different kind of fashion statement [WWW

document]. URL

http://www.usatodav.com/life/cyber/tech/revie

w/200 1 -04- 1 8-wearable.htm

Merritt, R. (2001). Switching fabric. Electronic Engineering Times, 1191, 1-3

Miah, T., Carter, C, Thorpe, A., Baldwing, A.,

and Ashby, S. (1998). Wearable computers

an application of BT's mobile video system for

the construction industry. BT Technol Journal,

Vol. 16, No. l,pp 191-199.

Mills, T., and Beliveau, Y. (1998). Virtual

Site Visit Using Wearable Computers. The

1998 International Conference on Wearable

Computing, Fairfax, VA, 1998.

Mizrachi, D (2000) Info-Fashions for the New

Millennium, Online, 24(1), 82-85

Neel, D (2000) Wearable PC goes to work,

InfoWorld, 22(47), 10

Newland, B., and Owings, C. (2001, Jan. 9). In the field, wearable computers will change

how work is done. [WWW document]. URL

http://wwM'. die, com/news/co/11 127075. html

Rebolj, B., Magdic, A., and Cus-Babic, N.

(2000, Jan 9). "Mobile Computing in Construction". [WWW document]. URL

http://kamen. unimb.si/cgi/Mobile %20computins%20in %20con

struction.htm

555
CPU W/Battery

Monitor

Figure 1 : MA V Wearable Computer by

Xybemaut Corporation.

Table 1. Comparison of Three Different Methods

Method Advantages Disadvantages Human Factor

Manual Quick and easy to input data Hard to manipulate blueprints and

writing pad simultaneously

Fatigue in wrist and arms and sweating body

Palm PC No need for paper forms,

Palms easy to carry, light

weight

Wearable No need for blueprints or Computer paper forms, instant access

to everything from

anywhere

Still require blueprints, screen hard

to read where not much lights,

slower input

Require time to put up parts on

body, and wait for the system to boot up; Require operations to drawings like zooming in and out, moving up and down

Eye fatigue

Finger fatigue after continuous data input using arm-worn keyboard

Table 2. Adjusted Results due to communication time.

Method Original Adjusted

Time Time

Manual

Palm PC

Wearable

76 Minutes 1 36 Minutes

95 Minutes 95 Minutes

66 Minutes 66 Minutes

556
The Value of Handheld Computers in Construction

by

Kamel S. Saidi', Carl T. Haas', Nicole A. Balli'

Abstract: Construction is an information intensive industry in which the accuracy and timeliness of information is paramount. Construction projects can experience extensive delays or rework due to information that is unavailable,

inaccurate or simply outdated. Handheld computers (HHC) have the potential to solve some of these problems by

providing field workers with accurate, reliable and timely information at the location where it is needed. Thus,

HHC's can increase the amount of direct work on a project indirecdy by directly decreasing the time spent on

support work (such as accessing drawings and sending RFI's) and by reducing idle time. Applying a HHC evaluation

method to 6 hypothetical construction field activities (punchlisting, materials tracking, MSDS access, drawing

access, RFI's, and quantity surveying) showed that HHC's could potentially save time and improve accuracy at the task and activity levels of a construction project. However, barriers related to the HHC's technological Umitations

and to the nature of the construction industry must be overcome in order to reap the full benefits of HHC's.

Keywords: field data, handheld computers, material tracking, punchlisting, quantity tracking

1. INTRODUCTION

1.1 Problem Statement

The successful and timely completion of a

construction project depends on the accuracy and

timeliness of a vast amount of information [1,2].

Craft foremen spend more than 50% of their time

in the field where data is difficult to access

outside of the site office. Projects often

experience extensive delays or rework due to information that is unavailable, inaccurate or

outdated. These delays decrease the overall

productivity of the project and increase indirect costs due to schedule delays or direct costs due to rework. The construction industry is in need of

tools that can provide accurate, reliable, and

timely project information to the field and gather

and transmit up-to-date project information from

the field. Handheld computers (HHC) can

potentially fulfill these needs.

1.2 Research Objective

The objective of this research was to investigate the potential of HHC's to add value to a construction project through impacts on time

and money" and to evaluate this potential.

' Department of Civil Engineering, University of Texas at Austin, ECJ 5.200, Austin, TX 78712, (512) 471-4645,

kamel@mail.utexas.edu, haas@mail.utexas.edu,

nballi@mail.utexas.edu

^ Other measures such as safety, rework, and productivity

are also widely used, however, these are intrinsically related

to the above three metrics. Although quality is as important

as the other two metrics, apart from measuring factors such

1.3 Hypothesis

HHC's can indirectly increase direct work by

directly decreasing the amount of support work

and idle time within an activity (see Figure 1).

1.4 Methodology

The following methods contributed to this research: 1) an extensive literature review was

performed; 2) informal interviews with

construction contractors and IT companies were

administered; 3) a simple, systematic HHC

evaluation method was developed; 4) HHC

hardware, software and other peripherals with

specifications suitable and beneficial to the

construction industry were classified; 5) six construction activities in which HHC's were

thought to have the greatest potential benefit were

identified; and 6) an evaluation method was

applied to the above activities as case studies. Details of the above methods and their results are presented in [3, 4].

2. BACKGROUND

A HHC is a self-contained electronic device

that fits in the palm of a user's hand and

possesses, at a minimum, enough computer

processing power to surpass the functions of an

electronic personal organizer and to run software

applications that can extend its built-in functionality.

as rework and owner satisfaction in an effort to quantify it, quality remains an illusive metric.

557
The use of HHCs on the construction jobsite was investigated as early as 1992 for field data

acquisition [5]. The implementations of HHCs in

construction discussed in the literature have

focused primarily on project management,

schedule management, facility inspection, and

field reporting applications [4]. Various

construction firms have started using handheld

computers on the jobsite for gathering schedule,

quality, layout, inspection, and other types of

information [6, 7, 8, 9]. However, due to the

relative immaturity of HHC use in construction,

there have been very few applications in construction that may be considered an accepted

way of doing business.

A study of the software applications

available on the handheld computer market

conducted in 2001 showed that there were

approximately 40 titles geared specifically

toward the construction industry whereas over 300 titles were commercially available for the

health industry alone [4]. This seems to indicate a

lack of interest in HHCs on the construction

industry's part [10] and a lack of interest in

developing applications for the construction

industry on the part of the HHC hardware and

software manufacturers. Of the top 8 HHC

manufacturers contacted by the authors, none

indicated that they had identified the construction

industry as a differentiated customer for their

product development and marketing [4]. In

contrast, the manufacturing, white goods, process

plants, transportation, heaUhcare, and other

industries have been marked as targets by most

of the same manufacturers.

In a survey of 179 construction foremen,

Alemany [11] showed that foremen who used

computers at work saved time on paperwork and

spent more time on supervision. Most of the

surveyed foremen expressed a desire to automate

time reporting, visualizing and interpreting

drawings, job progress recording, and tools and

materials management functions [11]. In another survey conducted internally by a

large construction company the authors found

that supervisors spent between 36 to 50% of their

time on paperwork related to employee time

keeping and material management functions [5]. The above 2 surveys suggest that using HHCs

effectively in the field for employee time keeping

and materials management alone could enable

foremen to spend more of their time supervising.

Consequently, this could have positive impacts

on productivity and quality. Similarly, providing

construction workers with HHCs that can help

them locate tools, equipment, and materials, send

requests for information (RFI's), and access

relevant schedule information (among other

important functions) could potentially allow them

to spend more time on direct work and less idle time waiting for answers or needed tools and

materials. Other benefits of HHC in construction

have also been identified in the literature [6, 12,

13, 14].

3. THE EVALUATION METHOD

Several researchers have proposed formal

techniques for evaluating IT in construction [15,

16, 17, 18]; however, none of these techniques

deal with HHCs. The justification for using HHCs

in the construction industry (and other industries)

must account for impacts on the organization's IT

infrastructure, the construction processes, and so on [14, 19].

3.1 Basis of the Method

Since most technologies are applied at the

task level within a project [20], and their impacts

propagate up toward the project level, the

evaluation of the suitability of using HHCs on a

project must begin at the task level. The HHC

evaluation method presented herein breaks down a

construction activity hierarchically into a detailed

set of final elementary tasks [21], and defines time

and cost values for each elementary task [22]. As

a means of representing the decomposed task

hierarchies, information flow charts (also known

as decision-action diagrams, logic diagrams,

process flow charts, etc.) are also used [21, 22].

Finally, the evaluation method incorporates a simple accounting process whereby elementary

task times and costs are accumulated in order to calculate totals [9].

3.2 The Evaluation Process

The evaluation method first requires that the

construction process as it currently exists (i.e., the

traditional process) be systematically documented.

While the traditional process for the same activity

may differ from company to company, the change

that would occur in the process when HHCs are introduced is the evaluation method's primary

concern.

558
Once the elementary tasks of the construction

activity in question are defined, the next step

involves assigning responsibilities for each task. From the list of elementary tasks, a flow chart is created in order to capture the sequence of

activities and any feedback loops that may exist. Next, minimum and maximum completion times

are assigned to each elementary task to capture

the variation that may occur. Although, the times

assigned may not be entirely accurate, or may

differ between companies and/or projects, as already stated, the differences in task times

between the traditional process and the HHC

process are the focus. Finally, the possible errors and corresponding delay times for each

elementary task are documented.

After describing the traditional activity, the same method is applied to the activity as it would

exist with the introduction of HHCs. Depending

on the activity, certain tasks are changed,

combined, or altogether eliminated. Times are reassigned to each elementary task in the HHC

process and the potential errors and associated

delays are also adjusted.

The final step in the evaluation process is to estimate the total activity time both with and

without the use of a HHC. The time difference

between the traditional and HHC processes is estimated to determine whether the use of the

HHC might be beneficial to that particular

activity. Table 1 shows a blank sample form that

is used to record task information for each

activity.

4. CASE STUDIES

The HHC evaluation method outlined above was applied to 6 construction field activities: 1) punchlisting, 2) materials tracking, 3) MSDS

access, 4) drawing access, 5) RFT's, and 6)

quantity tracking. Except for the quantity

tracking activity's evaluation (which was based on field observations and interviews) the method was applied to theoretical models of the

construction activities involved rather than to actual activities on a construction project. The

reader is referred to [3, 4] for detailed results and

descriptions of these evaluations. A primary

assumption made in the case studies below is that the introduction of HHCs in each activity is coupled with an implementation of the Center for Construction Industry Studies' (CCIS) Tier II

strategy [22]. One of the central premises of the

Tier II strategy is that field personnel have greater access to information and certain decision-making

powers without management's approval.

4.1 Punchlisting

The punchlisting activity lends itself well to HHC implementation because it is a field-based

activity whose information is typically collected

into a form. In addition, the punchlisting process

is cyclical, since it may occur repeatedly

throughout the project and some items may be relisted on the punchlist if not satisfactorily

completed [23].

Applying the HHC evaluation method to the

punchlisting activity showed that the use of HHCs

can theoretically eliminate 14 elementary tasks,

which could reduce each punchlisting cycle's time

by an estimated 40%. The addition of HHCs to the

punchlisting process can also contribute to a 39 to 46% reduction in delay time. Overall, HHCs can

potentially reduce delay time by approximately 50

to 70%.

4.2 Materials Tracking

Received materials are often improperly

recorded, relocated or not recorded at all. Materials that are lost, misplaced or improperly

stored can cause major delays and disruptions on a

project and drastically affect project cost and

schedule [24]. Handheld computers could help

resolve some of these problems by eliminating

handwritten notes and the reliance on human

memory, and by offering foremen access to up-todate material information. The materials tracking

activity was selected because it is field-based and was identified by foremen as a priority for automation in Alemany's [11] research.

Applying the HHC evaluation method to the

materials tracking activity showed that the use of

HHCs can potentially eliminate 9 elementary

tasks. Approximately 26 to 51% of the overall

activity time can also be saved by implementing

HHCs and the Tier II strategy in concert. Overall, the potential delay time saved was

estimated to be 88 to 95%, with a majority

stemming from the addition of a HHC to the

process.

4.3 MSDS Access

The MSDS (Materials Safety Data Sheets) access activity was selected because it requires

559
onsite access to large amounts of textual information, and thus lends itself well to HHC

implementation. For this evaluation it was

assumed that an online MSDS database could be

accessed wirelessly (many are currently publicly

available) or stored on the HHC itself. Applying the HHC evaluation method to this activity showed that 5 elementary tasks can be

theoretically eliminated. Implementation of the

Tier 11 strategy eliminated those tasks that required information transfer between different

hierarchical levels of the organization; while the

addition of HHCs to the process eliminated travel and distribution tasks. A 59 to 71% reduction in overall activity time was estimated. The total reduction in the activity delay time was

approximately 65 to 75%.

4.4 Requests for Information (RFI)

The RFI activity was selected for

investigation because a large number of inquiries

arise at the work face and a means of

documenting them and receiving answers quickly can eliminate delays. In addition, the process

does not involve much data entry and can take

advantage of on-site wireless communications to send and receive information. The new HHC

process assumes that the Tier 11 strategy would

allow the foreman to communicate directly with

the A/E via e-mail, and that the work in question

could be viewed in a digital photograph (sent via

e-mail wirelessly from the HHC) by the A/E

rather than in person.

Applying the HHC evaluation method to the

RFI activity showed that the use of HHCs can

theoretically eliminate only one elementary task. However, the new process reduces the activity

time by an estimated 16 to 23%. While all of that time is saved due to the use of a HHC, the time

saved due to implementation of the Tier II strategy is captured in the delays. The reduction

in delay time is key in this activity and is due in large part to the elimination of the hierarchical

structure that a traditional RFI follows. In

addition, the delay between the time that an RFI

is generated and answered is greatly reduced

because the architect does not have to travel to the site. The new process can potentially reduce

delay time by 83 to 91%.

4.5 Drawing Access

The drawing access activity was chosen

because it is a field-based activity that requires

only access to information, and therefore does not

require any data entry. It is assumed that foremen

will have access to a central database to which

drawings are regularly uploaded. In addition, the

assumption is made that in the new process the

Tier II strategy will allow the foreman access to the drawing database directly rather than having to go through a superior.

Applying the HHC evaluation method to the

drawing access activity showed that the use of

HHCs could potentially eliminate 3 elementary

tasks. Using the HHC and the Tier II strategy in

this process reduces the activity time by an

estimated 70%, primarily due to reductions in travel time and time taken to obtain the

information through hierarchical channels. Delays

associated with the eliminated tasks are also

reduced by an estimated 64 to 72% in this activity.

While the overall result shows a reduction in delay time, the issue of the HHCs small screen could prove to have adverse effects on the

activity's productivity.

4.6 Quantity Tracking

The purpose of tracking (or surveying)

quantities on a construction project is to measure

progress in order to control cost and schedule. The

quantity surveyor (or tracker) tracks the quantities

of materials that have been installed or that are in various stages of installation. These quantities are

essential for controlling a project's cost, schedule,

and quality. Therefore, the accuracy of the

quantity survey data is critical [4]. Applying the HHC evaluation method to the

quantity tracking activity showed that the use of

HHCs eliminated 6 elementary tasks and saved

approximately 60% of the overall activity's time;

in addition to improving the accuracy of the data,

providing an auditing tool to check takeoff

quantities in the field, and reducing the chance of

quantity over-reporting.

5. CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions

The use of HHCs in six construction activities was evaluated above. The evaluations showed that time savings at the task and activity levels do not

560
translate directly into project-level time savings

and that benefits are more likely to be achieved if HHCs are implemented in multiple activities and

projects.

Based on the preliminary experiments with a HHC purchased as part of this research (see [4]), HHCs are currently bound by several key

technologies that limit their functionality under

certain conditions. These limitations involve

HHC features such as screen size, screen

visibility, processing capability, and input

method. Table 2 presents a list of construction

tasks that are suited for HHCs, followed by tasks

that are not suited (these tasks do not take into

account HHCs extended range of functions

when combined with other peripherals).

This research also found that the barriers to HHC implementation in construction are a result of two factors: 1) the HHC technology's

limitations and 2) the construction industry's

characteristics. The HHC technology's

limitations where discussed. The construction

industry barriers consist of the physical jobsite

conditions (such as temperature, humidity, dust,

etc.) as well as organizational issues such as the

industry's fragmentation and low risk tolerance,

among others [4]. Handheld computers have many benefits that can improve construction processes. The most

significant benefit is perhaps the HHCs ability to provide workers with real-time access to relevant

information at the jobsite, and to send real-time

information back from the jobsite to the

appropriate decision makers. In addition, an HHCs ability to improve the accuracy of the

information being exchanged is one of its primary added values in construction. The type

of information and the transmission method are some of the issues that must be assessed during

the design of an HHC evaluation and

implementation strategy.

5.2 Recommendations

The lack of empirical data on HHC

peiformance in construction could be improved

through well-documented pilot projects at construction companies and through controlled

experimentation with HHCs under simulated

environments. In addition, future research should

also address HHC hardware issues that constitute

barriers to their implementation on construction

projects.

6. REFERENCES

1. Rezgui, Y., Cooper, G., and Brandon, P. (1998), "Information Management in a Collaborative Multifactor Environment: The COMMIT Approach," Journal of Computing in Civil Engineering, 12 (3), 136-144

2. Shahid, S. and Froese T. (1998), "Project Management

Information Control Systems," Canadian Journal of Civil Engineering, v 25, n 4, 1998, pp 735-754

3. Balli, N.A. (2002), "Handheld Computer Applications for

the Tier-II Worker," Masters Thesis, The University of Texas at Austin, Austin, Texas

4. Saidi, K. (2002), Possible Applications of Handheld

Computers to Quantity Surveying, PhD Dissertation, The

University of Texas at Austin, Austin, TX

5. McCuIlouch, E.G. and Gunn, P. (1993), "Construction

Field Data Acquisition with Pen-Based Computers,"

Journal of Construction Engineering and Management,

vll9, n2,pp374-384

6. Inglesby, T. (2000) "Handheld Computing: In the Field, Handhelds Can Make a Difference," ConstrucTECH,

3(4), http://www.constructech.com/, accessed 7/31/2000

7. CII (2000) "Mobile Inspection Assistance," CII's Emerging Construction Technologies website,

http://www.new-technologies.org/, accessed 8/1/2000

8. CII (2000) "Palm Estimating," CIFs Emerging

Construction Technologies website, http://www.newtechnologies.org/, accessed 8/1/2000

9. CII (2000) "Updater: Mobile Schedule Tracking

Software," CII's Emerging Construction Technologies

website, http://www.new-technologies.org/, accessed 8/1/2000

10. Coble, R.J. (1995), "Expanding Pen Computing

Capabilities to Include More Effective Field Application," Computing in Civil Engineering:

proceedings of the Second Congress held in conjunction with A/E/C Systems '95 / ASCE, Atlanta, GA, ppl340

11. Alemany, C.H. (1999), "Construction foremen computer

use and impacts," Masters Thesis, The University of Texas at Austin, Austin, Texas

12. WiUiams, T.P. (1994), "Applying Portable Computing

and Hypermedia to Construction," Journal of Management in Engineering: May-June 1994, vlO, n3, pp41

13. Newell, D.M. (1994), "Pen Computers in Civil Engineering," Computing in Civil Engineering:

proceedings of the First Congress held in conjunction with A/E/C Systems '94 / ASCE, Washington, D.C., June

20-22, pp 1631

14. de la Garza. J.M. and Howitt, I. (1998), "Wireless Communication and Computing at the Construction

Jobsite," Automation in Construction. v7, pp 327-347

15. Lindorfs, C, Chang, P., and Stone, W. (1999), "Survey of Construction Metrology Options for AEC Industry," Journal ofAerospace Engineering, vI2, n2, pp 58-64

16. Chun. D.A., Seo, J., and Haas, C.T. (1997), "Leveling

Technologies for Building Construction," Proceedings of

the ASCE Construction Congress V, ppl030-1037,

Minneapolis, MN., October 5-7, 1997

17. Jung, Y. (1997), Information Systems Planning

Methodology for the Construction Industry, Dissertation, The University of Texas at Austin, Austin, TX

561
18. Jung, Y. and Gibson, G.E. (1999), "Planning for Computer Integrated Construction," Journal of Computing in Civil Engineering, ASCE, vl3, n4, pp217-

225

19. Aberdeen Group, Inc. (2000), "The Benefits of Mobilizing Enterprise Applications with Handheld

Devices," Aberdeen Group, Inc., Boston, MA, August

2000

20. Back, W.E., Moreau, K.A., and Toon, J. (1998), "Determining the Impact of Information Management on

Project Schedule and Cost," CU Research Report 125-

11, Construction Industry Institute, The University of Texas at Austin, Austin, Texas

21. Kirwan. B. and Ainsworth, L.K. (1992), A Guide to Task

Analysis, Taylor & Francis Ltd., Washington, DC

22. Borcherding, J.D., Glover, R.W., Haas, C.T., and

Tucker, R.L. (2001), "Metric-Based Implementation of

Tier II Work Force Strategy," Center for Construction

Industry Studies, Report No. 20, The University of Texas at Austin, Austin, Texas, August 2001

23. Oberlender, G.D. (2000), Project Management for Engineering and Construction, The McGraw-Hill

Companies, Inc., Boston, MA

24. Stukhart, G. (1995), Construction Materials Management, Marcel Dekker, Inc., New York, NY

Decrease in Support Work and

Idle Time

Currert Pnxess V*hH-C

Figure 1. HHC's decrease support work and idle time.

Table 1. An activity task information form

Task IDTask

Description

Task

Time

(minutes)

min max

Possible Delay

(minutes) nun max

Source

of Delay

20

30

Table 2. Tasks for which HHC's are and are not suited.

# Tasks that are Suited Example

1 Tasks that require access to large amounts of text information Reading MSDS sheets, building codes, knowledge base, etc.

2 Tasks that require viewing a small detail of a document Viewing a close-up of a steel beam connection diagram

3 Tasks that require the entry of binary data Answering yes/no questions, checking-off items on punch lists 4 Tasks that require the entry of data into a form Filling-in a safety or equipment usage report, recording

material receiving information, etc. 5 Tasks that require instant transfer of small amounts of information to and from a network

Sending and receiving e-mails, looking up the latest material procurement information # Tasks that are not Suited Example

1 Tasks that require computer processing power

comparable to that found in desktop computers

Editing a 3-D construction drawings

2 Tasks that require a "big-picture" view of a document Viewing a drawing or a network schedule

3 Tasks that require a constant (i.e., always on) connection to a computer network Working with data stored on a mainframe

4 Tasks that require a considerable amount of manual

data entry (or writing)

Writing a progress report

5 Tasks that are likely to be performed mostly in direct day light, or under very bright artificial lightingWorking with no roof overhead during the day

6 Tasks that actually put work in place Naihng, cutting, digging, and etc.

562
Situation-aware Interface Design: An Interaction Constraints Model for

Finding tlie Right Interaction for Mobile and Wearable Computer Systems

Christian Biirgy*; James H. Garrett, Jr.*

ABSTRACT

The design of mobile and wearable computing

devices involves decisions about how the user

interacts with the hardware and software

composing the device. Since applications of, and

usage environments for, mobile and wearable

computers has varied greatly, it has been difficuh

to build on previously collected design knowledge.

The Interaction Constraints Model described in

this paper offers an application-neutral and

domain-independent approach for comparing

different applications and usage scenarios. The

Interaction Constraints Model provides a means to map information about user interface

implementations to specific work situations. In

this way, a system designer can use a set of

generic interaction constraints to identify and

retrieve information about user interface

components from previous projects. In a proof-ofconcept implementation of the Interaction

Constraints Model, we were able to validate the

approach of the model and we demonstrate the

usefulness for the design of wearable computer

user interactions.

KEYWORDS

Design Constraints; Human-Computer Interaction;

Industrial Applications; Mobile Computers;

Wearable Computing

1. INTRODUCTION

On construction sites, we see ever changing

'work situations' that differ in their 'work locations'

and 'work activities'. Mobile and wearable

computer systems can support workers in these

work situations. But to be useful tools, these

systems need to offer specific user interfaces that are appropriate for the work location and the work

activity at hand. The 'Interaction Constraints

Model' aids system designers in choosing the right

interaction means for specific tasks with respect to the environment in which the task is performed

and the kind of mobile or wearable computing

system that supports this task.

In this paper, we describe the underlying

concept of the Interaction Constraints Model and

the benefits of using it for interaction design and

conclude with showing the result of our proof-ofconcept implementation.

2. BACKGROUND

For computer-aided engineering applications,

mobile IT support helps to improve construction

processes [1] and enables mobile workers to perform their tasks better, faster, and with higher

quality, i.e., with higher data consistency (less

manual data entry and reentry), shorter data access times (connection to the company's intranet and to online manuals), and better communication means

(Internet telephony, short messages, expert

forums). However, mobile workers usually

perform several different tasks in ever changing

environments. This generates different

'constraints' on the system design of the mobile IT

support with respect to: the kind of the task to be

performed; the application, for which the task is performed; the influences caused by the

environment; the device chosen as the supporting

hardware platform; and the abilities and work

patterns of the user.

* Department of Civil and Environmental Engineering, Camegie

Mellon University; Porter Hall 1 19, 5000 Forbes Ave., Pittsburgh, PA, 15213, USA, Tel.; ++1 (412) 268-5674; e-mail; buergv@cmu.edu; e-mail; garrett@cmu.edu.

563
Each situation demands that the user and the

mobile or wearable computer device adapt their

interaction with respect to the task, the

application, and the environment. Many mobile

input devices have been developed for use "on the

move", such as mobile, body-worn pointing

devices and keyboards, scanners, or data gloves.

However, these interactions still involve using at least one hand. Some tasks, however, have to be

performed using both hands. Thus, it would be

helpful to get support in making the decision about

which user interface to use for which situation.

3. INTERACTION CONSTRAINTS MODEL

The concept of the Interaction Constraints

Model is a generic description of different work

situations based on the constraints that impact

interaction with mobile and wearable computers in industrial applications. The idea is to compare

different work situations between different

applications of the same or different domains.

Thus, we can compare the system design of a mobile IT device and re-use the design decisions.

This concept helps to identify similar situations

and evaluate how well a specific means of

interaction performed in previous applications.

The Interaction Constraints Model builds on two definitions: the constraints themselves

(section 3.1) and the work situation that is described by a specific set of constraints (section

3.2). A description of the implementation of the

model (section 3.3) and a usage example (section

3.4) demonstrate the concept of describing a work

situation with a set of constraints. Section 4

illustrates the contributions and results of the

Interaction Constraints Model.

3.1 Constraints

Leffmgwell and Widrig define constraints as "a restriction on the degree of freedom we have in providing a solution" [2]. Constraints in the

Interaction Constraints Model restrict the use of a

specific interaction modality for a system design

for a specific usage situation. Before the

introduction of mobile computing, the constraints

that implied the design of IT systems could be

associated with three constraint categories:

namely "user," "device," and "application." Now

there are five categories, since mobile and

wearable computers imply changing "tasks" in changing "environments." These constraint

categories contain constraints that influence

constraints of their own category as well as constraints of other categories during operation.

For example, a device constraint, such as the

absence of a display, influences other device

constraints, such as the need to provide alternative

output means; it also influences the application

constraints, such as no GUI interface being

possible. Sections 3.1.1-3.1.5 describe these five

constraints categories [3].

3.1.1. Task

Tasks are considered to be "states in the

working process" as a part of the workflow. Task

constraints are all those constraints that restrict the interaction between the user and the device,

such as a task that requires both hands of the user.

3.1.2. Environment

Environment constraints are defined as constraints of the working / usage environment of

the device, composed of such influences as ambient noise level, lighting, potential hazards

(need for gloves, masks, etc.). However, properties

of the IT infrastructure are covered by the device

description.

The considered environments are mainly

those in which multiple (non-traditional) input

modalities are applicable and special demands on

the user are present (i.e. office environments are covered by existing HCI research and thus not the

main target of this research).

3.1.3. Application

Constraints of the application influence the user interaction by demanding different navigation

564
/ operation tasks of the software, e.g., a CAD

application deals with 2D or even 3D drawing

navigation, whereas an inspection application

deals more with check lists. There are domainspecific applications, such as construction or manufacturing applications and general

applications that for example support the "back

office" processes. Furthermore, different

application structures or software architectures cause different behaviors of the software. Finally,

the application constraint category holds the

actual interface / interaction layer, i.e. the interface

to the user of the device.

3. 1.4. User

User constraints result from different

cognitive, logical, and physical abilities of users, as well as different expertise and experience.

Users and their capabilities are also constrained by

the working environment, such as situations that demand special attention or occupy the user in some way.

Working habits of users should not primarily

go into the constraints design, since these habits

might change completely with the use of the

mobile IT support. However, these habits have to be investigated thoroughly to fully understand the

tasks that have to be supported by the IT device.

3.1.5. Device

The device constraints result from the device

itself, as well as from other IT components

connected to the device. These constraints are for example the presence of different input / output

modalities that are more or less appropriate for a given task.

3.2 Work Situations

Work situations are uniquely defined by a combination of a work location, the place where

the user of the mobile or wearable device performs

a job, and the work activity, the actual task of the

user. The following are descriptions of the

components that enable the comparison of

different work situations and thus the re-use of

design knowledge.

3.2. 1 . Work Location

Work locations identify the location, and thus

the conditions, in which a work activity is performed. The reason to have locations as an

identifying factor in the model is the fact that interaction with a device is constrained differently

at different locations of one project and at locations of other projects.

Example: "Inspecting a bridge structure" and

"assembling tubular steel scaffolding, " have many

conditions in common; e.g., the sunlight, the

height of the workplace, safety concerns, etc. Working on a "tunnel construction project" and in a "pit of an automotive workshop, " also have

similarities: the artificial light (if any) and the

dust / oil of the machines or vehicles.

3.2.2. Work Activity

Work activities represent primary tasks of the

user. Primary tasks are the tasks that the

envisioned mobile or wearable device will finally

support. As mentioned above, work locations and

work activities define unique work situations. And

the motivation for including the work activity as an identifier is similar to that for the work

location. Here, too, the goal is to find patterns of

similar constraints that result from different

activities and to re-use these patterns for design

decisions for new work situations.

It may seem hard to compare activities from

different domains and to find similar patterns

amongst them. But the work activities themselves

will not be compared, but rather the constraints

and the constraints' influences on the user

interaction, which originate in these work

activities, are compared. Thus, we create constraints that are not domain-specific and

enable a domain-independent model.

565
Example: It is obvious that some activities, such as

"inspecting bridges" and "inspecting vehicles"

have similarities, but even the two activities,

"determine the inventory of construction

material" and "perform quality assurance at a manufacturing facility, " can be mapped to a common constraint pattern.

3.2.3. Work Situation

Work locations and work activities define

unique work situations. The link between the

location and the activity is the user who literarily

brings the work activity to the work location. This

is a new aspect that is caused by having mobile

and wearable computers, which enable IT support

away from the desktop or kiosk-like terminals.

Thus, we have to identify varying sets of

conditions or requirements to which the design has

to be adapted, and to which future adaptive

devices will adapt automatically.

Each work situation is unique in a sense that exactly one work activity is performed at one work

location. However, the conditions at different

work locations and the demands of different work

activities can have common patterns, and can thus

lead to similar constraints on the user interaction

with a mobile or wearable device.

Example: We can use the two examples above to show the concept of a work situation: "bridge

inspections" and "vehicle inspection" differ in their location; so do "assembling steel scaffolding " and "quality assurance " with respect

to the activity. However, "inspecting a bridge's

interior structure" and "assuring the product

quality in a poorly lit manufacturing plant" have

similarities in both respects.

3.2.4 User Interface

Finally, the Interaction Constraints Model

provides information about user interfaces that were implemented and evaluated in previously

conducted projects. The system designer can

retrieve this information, which is mapped to

specific work situations, and use it for designing

the user interaction for mobile IT devices for a

similar work situation.

3.3 Implementation

In order to conduct a proof-of-concept of the

Interaction Constraints Model, we implemented

the model as a database that stores all the

necessary information about the constraints of

work situations and the user interfaces that were

used in about 15 different previous designs of

mobile and wearable computer systems. The

implementation allows the user to enter the

constraints of a new work situation and to query

the case-base. Figure 1 shows the attributes of the

different constraint categories that describe each

work situation.

Each of the attributes of the constraints can

take several values, e.g. "low," "normal" or "high"

ambient lighting. We needed such a simple

classification, since the documentation of the

investigated projects did not provide more detailed

data. However, this classification was sufficient

for this proof-of-concept.

As a case-base, we collected project

information on 15 system designs of our own

research group, from other researchers at Carnegie

Mellon University, and from the literature [4]. This case-base was diverse enough to illustrate the

usefulness of the application and the domain

independence of the model, and showed that we

can use constraints to retrieve similar situations of

previous projects.

3.4 Usage Example

To demonstrate the concept behind the

Interaction Constraints Model, we want to present a brief example on how the interaction design of a new wearable computer system can be supported

by using the model: first, the system designer

performs a task analysis and identifies the work

locations and the work activities that occur for the

envisioned application. For each relevant

566
combination of work location and work activity

the designer defines a work situation and enters estimated or measured constraints for each work

situation in an implementation of the Interaction

Constraints Model. Depending on the am.ount of

cases entered in the case-base and the query

capabihties of the implementation of the model,

the designer gets a set of similar work situations

that occurred in previous projects. Now the

designer can retrieve information about the user

interfaces used in these work situations and

evaluate the performance of these user interfaces. Based on that information, the designer can decide

which user interface to include in the new system

design and which interfaces would not perform

well. After collecting user feedback on the design,

the designer enters information about the new

design and thus adds information to the case-base.

4. RESULTS

Using the proof-of-concept implementation,

we performed several different types of tests. First,

we took situations that an experienced designer

could map without any help to prove that the

system is valid; then we used the system to query

the database for work situations that could not

easily be imagined, but served as good design

examples.

One example was to compare a progress- monitoring task on a construction site (Progress

Monitor by Reinhardt, et al. [5]) with a vehicle

inspection performed in the field (VuMan

Amphibious Vehicle Inspection System by

Smailagic, et al. [6]). The similarity of the

constraint patterns for the two work situations

results from the fact that both locations are outside

in sunlight, with noisy machinery close by, low

cleanliness due to the construction site or vehicle

oil, respectively, and rough conditions under

which the devices are used for the inspection.

The second example in which the system

returned corresponding design examples from a

different domain were the transmission of patient

data of EMS personnel at a highway accident at

night and an inventory maintenance task in a tunnel construction site. The matches derived from

the system show that in the different work

situations of the two applications, the same set of

constraints restricts the user interaction and thus can be designed in a similar way.

Finally, the system mapped a tourist guide

application helping a tourist in a restaurant to find

the next attraction in an online multimedia guide

and a worker querying a mobile spare part

database in a manufacturing application. In this example, the match of the environment constraints

and the transfer from one domain to the other

domain made it unlikely to imagine the match

without the help of the Interaction Constraints

Model implementation. The conditions in an

industrial supply room are surely not the same as

in a bar or restaurant, but they impact the design of

mobile IT system with the same set of constraints.

Another finding about the tourist guide project is that using the system in a museum restricts the

"Linguistic Ability" of the user and the "Audio

Input" of the device. Thus, it matches in these

categories to many other industrial applications.

However, these restrictions do not result from the

high ambient noise, which does not occur at a museum, but in the required silence expected from

museum visitors, which does not allow for using

speech input by the user.

These results showed us that we indeed could

compare work situations based on the constraints

that impact the user interaction. However, we have

to extend the case-base of mobile and wearable

computer design projects to sufficiently support a broader variety of work situations.

5. CONCLUSIONS

With the Interaction Constraints Model, our approach to determining the best interfaces for a given situation is to map the possible constraints

for different work situations to a set of potential user interfaces. Thus, we map the possible

interfaces and their applicability to the constraints,

independent from the application or domain in

567
which the constraints occur. This approach allows a more systematic means by which to search for

and apply previous experience gained in mobile

computing projects.

6. REFERENCES

[1] Trupp, Torsten. 2001. Mobile Computing in Construction Management. Thesis, Department of

Civil Engineering, University of Applied Sciences

Giessen-Friedberg, Germany, p. 7

[2] Leffmgwell, Dean and Don Widrig. 2000.

Managing Software Requirements - A Unified

Approach. Addison-Wesley, p.44

[3] Biirgy, Christian and James H. Garrett, Jr. 2002. Wearable Computers: An Interface between

Humans and Smart Infrastructure Systems. Bauen

mit Computem 2002, Bonn, Germany. VDI

Verlag GmbH, Duesseldorf, Germany.

[4] Biirgy, Christian. 2002. An Interaction

Constraints Model for Mobile and Wearable

Computer-Aided Engineering Systems in Industrial Applications. Thesis, Dept. of Civil and

Environmental Engineering, Carnegie Mellon

University, Pittsburgh, PA, USA. p. 82

[5] Reinhardt, Jan, James H. Garrett Jr., Raimar J. Scherer. 2000. The preliminary design of a

wearable computer for supporting Construction

Progress Monitoring. International Conference on

the Application of Computer Science and

Mathematics in Architecture and Civil

Engineering (IKM 2000). Weimar, Germany.

[6] Smailagic, Asim. 1998. An Evaluation of

Audio-Centric CMU Wearable Computers. ACM

Journal on Special Topics in Mobile Networking

and Applications, Vol. 6, No. 4, 1998, pp. 65-76.

-| Constraint Pattern - Example [

pnvironment

Task

Task Type

Tools Needed — Full Attention Needed — Interaction with People — Data Access Needed

Lighting

Noise

Cleanliness Roughness

tSevfce

lipplication

User

T~ Tactile Cognition — Visual Cognition — Aural Cognition — Tangibility — Visual Ability — Linguistic Ability — Mobility of User

Text-based Data

Table-based Data

Drawings Required

Sketches Required

Photos Required

Video Required

Audio Required

Tangible Output blocked

Visual Output blocked

Audio Output blocked

Tactile Input blocked

Visual Input blocked

Audio Input blocked

Dimensions

Figure 1 : Each work situation can be described with a specific set of constraints (or constraint pattern).

568


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