bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fundamentals of Workpiece Localization: Theory and Algorithms
Authors: Li Z. X. , Kang B. , Gou J. B. , Chu Y. X. , Yeung M. 
Published: July 2023

Abstract
In this paper, we present an algebraic algorithm for workpiece localization. First, we formulate the problem as a least-square problem in the configuration space Q = SE(3) × ℝ3n, where SE(3) is the Euclidean group, and n is the number of measurement points to be matched by corresponding home surface points of the workpiece. Then, we use the geometric properties of the Euclidean group to compute for the critical points of the objective function. Doing so we derive an algebraic formula for the optimal Euclidean transformation in terms of the measurement points and the corresponding home surface points. We also give for each measurement point a system of two nonlinear equations from which the corresponding home surface point nearest to the measurement point can be solved. Finally, based on these analytic results we present an iterative algorithm for obtaining the complete solution of the least-square problem.
Optimization and Interpolation Issues in Evaluating Actual Geometric Deviations From CMM Data
Authors: Nassef Ashraf O. , ElMaraghy Hoda A. 
Published: July 2023

Abstract
Coordinate measuring machine data are used to determine whether ornot parts conform to the specified tolerances. Much of the analysis involve optimization to evaluate the values of actual geometric deviations detected by CMM inspection. If the optimization method does not arrive at the global minimum value of a deviation and settles for a higher value instead, a part could be unnecessarily rejected during inspection. This paper proposes the use of genetic algorithms as global optimizers to evaluate geometric deviations and shows their advantage over the currently used methods through examples. Since the definition of some deviations in the new GD&T standards, such as the local size, do not lend themselves easily to optimization algorithms using the CMM data directly, the presented work proposes the approximation of the manufactured surfaces using NURBS for facilitating the evaluation of such deviations. Finally, the paper recommends the use of some genetic parameters to decrease the computational intensity associated with using the genetic algorithms.
Dimensional Measurement Data Analysis: Part II — Minimum Zone Evaluation
Authors: Choi Woncheol , Kurfess Thomas R. 
Published: July 2023

Abstract
Modern inspection systems such as coordinate measurement machines generate discrete three dimensional coordinates representing points from the surface of a manufactured part. These coordinates must be compared to a target or nominal geometry to determine if the part conforms to specification. Quite often a least squares fit or a min-max fit are employed to determine the geometry of the part. However, as described in Part I of this paper, acceptable deviations are often specified as tolerance zones about the nominal geometry. Part I of this paper presents a zone fitting algorithm having an objective of placing the sampled data points within a specified tolerance zone. If all of the points fit within the zone, the part is passed. This pass/fail result does not provide information as to the quality of the part. The question that is not answered is “Did the points just fit into the tolerance zone, or did the points fit with ample space remaining?” This question is important as it informs production personnel whether their processes are operating well within specifications or just barely within specifications.
In this part of the paper, the zone fitting method developed in Part I of this paper is extended to a minimum zone evaluation. This can be formulated as a one dimensional search for the critical value of the zone fitting objective function, which is to place all sampled points within the zone via geometric rigid body transformations (e.g., rotations and translations). The minimum zone evaluation algorithm developed in this paper can be applied to an arbitrary geometry profile evaluation, and a number of examples are presented to demonstrate its capabilities.
On the Manufactured Part Model Approach to Characterize Shape
Authors: Fussell Paul S. , Novic Bradley 
Published: July 2023

Abstract
The methodology of the manufactured part model, MPM, a means to reduce measurement data to meaningful shape information, is elucidated. The MPM permits one to fit a parameterized model of the nominal geometry to the set of surface location data resulting from measuring a part. This note describes recent successes using the MPM method, particularly in discovering the true deformed shape: this insight has led directly to improved schemes for process operation which reduce part variation, as well as quantifying process capability. We further discuss suitable applications of the methodology, areas of immediate and longer term research, and applications to more complex assemblies.
Fault Diagnosability Enhancement Through Sensor Optimization in Multi-Fixture Assembly Systems
Authors: Khan Ashraf , Ceglarek Dariusz , Ni Jun 
Published: July 2023

Abstract
The effectiveness of fault diagnosis in assembly is contingent on the effectiveness of the sensor measurement of assembled parts. Using a diagnosability enhancement methodology for a single fixture, a means to achieve an optimal sensor configuration for a multi-fixture assembly of sheet metal parts is proposed. A Hierarchical Group description of the assembly is used to build a State-Transition representation which, with fixture CAD information, is used in multi-level hierarchical optimization to arrive at the optima. A defined Coverage Effectiveness Index quantifies fault isolation performance. The index also serves to evaluate the performance effectiveness of the measurement station location and change in the sensor number. The approach has significant utility in automotive body assembly where system complexity makes the choice of sensor location vital to fault isolation performance. Examples using multi-fixture simulated automotive body assembly sequences are provided to illustrate the methodology.
Uncertainty Management for CMM Probe Sampling of Complex Surfaces
Authors: Edgeworth Robert , Wilhelm Robert G. 
Published: July 2023

Abstract
A method is presented to reduce the measurement uncertainty for surface point inspection when using a Coordinate Measuring Machine (CMM) equipped with a mechanical touch trigger probe and rotary probe head. The largest contributor to measurement uncertainty in this situation is the variation in probe deflection before a trigger signal is sent to the CMM. This variation is dependent on the angle between the major axis of the touch trigger probe and the surface normal of the point being probed. When the major axis of the probe body is nearly collinear with the surface normal at the sampled point, the probe deflection variation decreases significantly. Experimental results show that the uncertainty due to repositioning the probe head to achieve this near collinear orientation is considerably less than the uncertainty associated with probe approaches where there is a large angle between the major axis of the probe and the surface normal of the point being probed. This result is particularly applicable to the measurement of complex surfaces.
A Framework on Automated Root Cause Identification Methodology Using Fuzzy Neural Network Reasoning
Authors: Tadayon Farhad , Lee Jay 
Published: July 2023

Abstract
Early recognition of assembly interface problems can save noticeable time and money by eliminating the red tape and procedural activities among different and often redundant organizations. Automated Root Cause Identification System (ARCIS) is a quality control expert assist database system which can suggest and identify the root cause of an assembly variation problem based on the history of the previous occurrences and in conjunction with the on-line multivariant statistical information obtained from the principal clusters of variations. A fuzzy Cerebellar Model Arithmetic Computer (CMAC) neural network system serves as a “watch-dog” to perform feature extraction of the output from the ARCIS and compare its pattern with previous patterns. As a result, the trends of performance degradation can be measured through this integrated methodology.
Dependency Relations in Product Families
Authors: Shek Stanley C. , Chan Stephen C. , Lee John W. 
Published: July 2023

Abstract
A product is usually composed of other products with a number of different variants. The user may select among a number of options for certain features of the product. The option selected for a feature may, in turn, determine the available options for other features or the available variants of certain components to be used in composing the product. This paper proposes to extend the ODMG data model to support the concept of a product family and some common dependency relations among its features and components. It classifies these dependency relations based on the features and components involved and their respective values and cardinality. A graphical notation is also included.
Integration of Activities to Step Product Data Models Using Object Oriented Methodology
Authors: Ghodous Parisa , Vandorpe Denis 
Published: July 2023

Abstract
A modern engineering environment needs to solve the problem of integration between different applications. Recent works on product data integration have led to STEP (international Standard for Exchange of Product data models). Unfortunately STEP doesn’t emphasize on the reprsesentation of activities. In this paper, firstly we describe a methodology for classification of activities and then using the object-oriented approche, we define a model which integrates the STEP product data models with activity data models. Some examples in the domain of kinematics analysis and geometric modeling are included.
Manufacturing Information Systems Integration: A Proposal Using SIP
Authors: Jardim-Gonçales Ricardo , Barata Manuel M. , Sousa Pedro C. , Steiger-Garçao Adolfo , Pamiés-Teixeira Jorge 
Published: July 2023

Abstract
Usually, the available software packages qualified to run within the manufacturing world were developed without a global view of the manufacturing system. When a factory wants to move towards Computer Integrated Manufacturing (CIM) the integration of these commercial tools should be considered.
Therefore, a possible approach to enhance production can be to consider the integration of already existent system’s tools using a standard data exchange format. UNINOVA - Institute for the Development of New Technologies, in the scope of a European project, has been developing a STEP (ISO10303) based toolkit (SIP) to aid the integration of these applications and the management of the achieved integrated system.
Up to the moment some managerial and engineering software applications have been integrated using SIP inside industrial companies. The software packages used, the steps followed to integrate them, and the results obtained using SIP in these manufacturing environments will be described and commented within the paper. Also, the internal architecture of SIP and the global information system architecture based on standard models are presented, highlighting the implementation aspects occurred during the developments for the industry.
Modeling Product Structures and Engineering Changes Using Express Representation Scheme
Authors: Peng Ting-Kuo , Trappey Amy J. C. 
Published: July 2023

Abstract
In recent years, information has become an important resource for managing the life-cycle activities of product development. Due to the heterogeneous and distributed nature of product R&D, related product data in electronic forms are often poorly managed even within the product design phase alone. As the result, an international standard for product data exchanges, STEP, is emerged and developed cooperatively by many organizations. This paper describes two main data models using STEP-EXPRESS representation scheme. One model is defined to represent the assembly structure of a product, the other is to describe the process of engineering changes in the design/redesign stage. These two models are essential in conveying the most updated product information for the concurrent engineering practice, particularly for complex product designs. Using the STEP-compatible data modeling technique, the product data integration between product structures and detailed CAD data is achieved without further efforts. Data involved in all product life-cycle activities are captured under the same format without any information loss. Furthermore, the integrated architecture for a heterogeneous design environment is also described that aims to achieve the information communication and sharing among various design systems.
Automatic Feature Recognition Using a Neural Network Technique
Authors: Chan Chu-Chai (Henry) , Fischer Gary W. 
Published: July 2023

Abstract
For a concurrent engineering environment, two critical steps are needed. The first step is to share information between design engineers and manufacturing engineers. The second step is to understand the meaning of the information being shared. This paper focuses on an automatic feature recognition method for interpreting part feature information created by a design engineer. Automatic feature recognition can help understand the meaning of features and provides the basis to link CAD to CAM.
A big problem for automatic feature recognition is that the increasing number of recognized features causes the process of recognition to become very complicated. The conventional feature recognition methods, such as graph-based and rule-based recognition, construct graphs or need experts to define an extensive set of sophisticated rules and use exhaustive searches to identify features. An artificial neural network methodology is proposed to avoid these problems. Neural networks can recognize features very quickly and the trained features can be interpreted directly from the geometric information instead of relying on expert-defined rules.
A common difficulty encountered when using neural networks is that the training process can take a long time or in some cases even be impossible. In order to increase the learning rate, this paper presents a neural network algorithm called CMAC (Cerebellar Model Arithmetic Computer). The paper also demonstrates other advantages of using neural networks, such as the recognition of partial features and compound features.
A Framework for Logistics System Metrics
Authors: Byers Jill E. , Landers Thomas L. , Anderson Steve 
Published: July 2023

Abstract
With global competition intensifying and companies battling to keep market share, it is imperative that they carefully manage costs while maintaining service levels. Many companies are considering outsourcing transportation and distribution functions as a way to reduce costs. Before costs can be reduced in a particular division, these costs must be defined and a method found for their calculation. In addition, companies need ways to measure service. Well-defined metrics can help a company measure costs and service and analyze tradeoffs between the two.
Metrics are quantitative measurements that track certain processes within a business (refer to Figure 1). These processes might seem simple (e.g. shipping a load of computer chips). However, even simple processes can become complicated when the underlying costs such as carrying, holding, material handling, and transportation costs, eta are considered. Since many processes have multiple sub-levels, it can be very difficult to identify which metrics to use.
This paper develops a list of potential metrics for distribution and transportation operations, and constructs a conceptual framework.
Communications Technology Requirements for Virtual Warehousing
Authors: Walker Bryan H. , Landers Thomas L. , Stuart Don , Kasilingam Raja , Rupert Clyde 
Published: July 2023

Abstract
Global logistics is the new frontier for information technology. World trade is expected to increase four-fold to over US$16 trillion by the year 2010. Logistics represents over US$600 thousand million in the United States of America (USA), which is roughly equivalent to the cost of health care in that country. Additionally, logistics is the second largest employer of new college graduates in the USA. Because of the importance of logistics, the National Science Foundation in the USA sponsors The Logistics Institute (TLI), and its predecessor the Material Handling Research Center (MHRC) to conduct basic and applied research, continuing education, and technology transfer in logistics. TLI is an Industry / University Cooperative Research Center operated jointly by the Georgia Institute of Technology and the University of Arkansas. It is sponsored by seventeen member companies in addition to the National Science Foundation. TLI has close relations with the Fraunhofer Institute at the University of Dortmund in Germany and is establishing cooperation with Gintic Institute of Manufacturing Technology at Nanyang Technological University in Singapore.
Non-Linear Finite Element Analysis of the Contact, Strain and Stress States of a Bolt-Nut-Washer-Compressed Sheet Joint System
Authors: Váradi Károly , Joanovics László 
Published: July 2023

Abstract
A non-linear finite element model with contact elements was developed to evaluate the contact state of a bolt-nut-washer-compressed sheet joint system.
Applying the proper material law the non-linear behaviour of the members of the joint was studied in terms of the clamping force. Based on the FE results the load distribution among the threads in contact and the real preload diagram of the system were evaluated.
To produce the required clamping force at medium strength bolts it is advisable to use heat-treated washers instead of lower strength ones.
Thermoelastoplastic Stresses in a Rotating Disk of Temperature Dependent Properties With Temperature Gradient
Authors: Jahanian Shahriar 
Published: July 2023

Abstract
There are numerous situations in industry where rotating disks are subjected to cyclic thermal loading. If the operating thermal loading remain in the shakedown region, no plastic deformation occur and the system works safely. However, depending on the speed of cooling and other operating situations, inelastic deformation and incremental growth of the structure in question may occur. This may lead to the incremental deformation, and eventually incremental collapse of the mechanical components. Accordingly. it is essential to develop a numerical method to predict the ine|astic response of mechanical components to the thermal or thermo-mechanical loading. Analysing the aformentioned problems is quit complex, accordingly in this reaserch effort we begin with a simple case.
In this paper a numerical method is presented for estimating the thermoelatoplastic stresses developed in a rotating disk, subjected to temperature gradient. The disk’s temperature in the radial direction varies from 100 °F temperature to 1500 °F. The steady state temperature distribution is evaluated using the familiar Carslaw and Jeagar equations. For inelastic behavior of the disk a combined analytical and numerical method is presented. The properties of the material are assumed to be temperature dependent. The material is also assumed to be characterized by nonlinear strain hardening. For this analysis a quasi static uncoupled thermoelastoplastic solution is presented. The problem is also solved for a case when the properties of material are not function of temperature. The effect of temperature dependency of the material on the results is investigated.
Experience With the Application of Risk Concepts in Developing Equipment Prioritization Systems
Authors: Tallin Andrew G. , Conley Michael 
Published: July 2023

Abstract
As consultants to refining and petrochemical companies, Det Norske Veritas (DNV) has been involved in developing risk based prioritization and management systems for a number of years. This paper follows DNV’s experience as it developed these methods, beginning with the initial concepts through the completion of several projects. The paper discusses some of the efforts that have been made to standardize the application of risk based prioritization.
In applying risk based inspection, the likelihood and consequence of each individual item is considered and the result is a ranking system that identifies and ranks failures on a uniform scale. In virtually every study DNV has performed, the “Pareto Principle” has been confirmed: at least 80% of a plant’s total risk exposure is due to at most 20% of the equipment. In many plants, the 90% of the risk is due to only 10% of the equipment. The principle is demonstrated here by presenting the overall distributions of risk that have resulted from prioritization studies that DNV has done.
The highest expected return is produced by prioritizing maintenance and inspection efforts to concentrates on this subset of items.
Systems Engineering of Complex Commercial Systems
Authors: Hale Pat 
Published: July 2023

Abstract
The formal Systems Engineering process was developed by the Department of Defense and its contractors in the late 1950s, during the development of the first ballistic missile systems, and was first documented as a standard process in 1969 in MIL-STD 499, Engineering Management. The process is intended to provide an overall framework for managing the development and acquisition of complex defense systems, describing an orderly sequence and supporting documentation to be implemented by both the government customers and development contractors. During the definition of systems engineering, defense and aerospace systems clearly represented the most complex products undertaken by the U.S. scientific, engineering, and industrial communities. As commercial products, particularly those spanning many technical disciplines, began to exhibit the same degree of complexity, the companies responsible for these commercial products have started adapting the DoD systems engineering process and practices for use in commercial product development projects.
Balancing Management and Technical Considerations for Environmentally Responsible Engineering
Authors: Kistler Ernest L. 
Published: July 2023

Abstract
This paper is about ways of visualizing and achieving harmonious balance between technical and managerial considerations with regard to environmental aspects of the design of complex systems. Environmental considerations strongly involve GeoSpatial Technology (GST) in the overall Life Cycle Analysis (LCA) of a total Product Realization Process (PRP). Hence, GST is a critical Emerging Technology essential for competitiveness and sustainable development in a global economy. Human dimensions of sustainable development are discussed as part of Total Productivity Management (TPM), and it is shown that certain aspects of the so-called “reengineering revolution” are not robust in the sense of Taguchi (and therefore are not sustainable). The concept of profit is discussed, and management considerations for maximizing corporate profit are examined through use of Kistler’s Productivity Gain Function (PGF) or Generalized Productivity Gain Function (GPGF) to account for numerous complex issues.