ICT for Supply Chains and Product Lifecycle 

Management: A Research Agenda for 

French-US Collaboration 

Abdelaziz Bouras 

Sudarsan Rachuri 

Eswaran Subrahmanian 

Jean-Philippe Lagrange 

(Editors)

NISTIR 7464

 
NISTIR 7464

ICT for Supply Chains and Product Lifecycle 

Management: A Research Agenda for 

French-US Collaboration 

(Editors)

Abdelaziz Bouras 

LIESP, Université de Lyon (ULL) 

160 boulevard de l'Université, 69676 BRON Cedex 11, France 

Sudarsan Rachuri 

MSID/MEL 

Eswaran Subrahmanian 

MSID/MEL 

Jean-Philippe Lagrange 

Scientific Attaché 

Embassy of France 

4101 Reservoir Road NW - Washington DC 20007 

October 2007

Carlos M. Gutierrez, Secretary 

National Institute of Standards and Technology 

James M. Turner, Acting Director 

 U.S. Department of Commerce

2
 

 

 

 

ICT for Supply Chains and Product 

Lifecycle Management 

A Research Agenda for French-US 

Collaboration 

Sponsored by: 

www.nist.gov 

With the partnership of: 

www.ambafrance-us.org/ 

http://www.cluster-gospi.fr/

 

 

 

 
 

 

 

 

 

 

Steering Committee 

Aziz Bouras Université de Lyon – France 

Eswaran Subrahmanian Carnegie Mellon University & NIST – USA 

Sebti Foufou Université de Dijon - France 

Albert Jones National Institute of Standards and 

Technology – USA 

Jean-Philippe Lagrange Embassy of France - France and USA 

Sudarsan Rachuri George Washington University & NIST – 

USA 

Ram Sriram National Institute of Standards and 

Technology - USA 

 

 

 

 

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 ICT for SCM & PLM: A Research Agenda for French-US collaboration 

 

 

 

 

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Preface

Innovation is becoming more and more dependent on global networks of 

resources and skills. Research plays a critical role in the innovation 

process, providing a base for scientific and technological knowledge to 

help develop new products, processes, and services. This relationship 

between research and innovation can be ensured by collaboration 

between distributed teams and organizations across the globe. Knowledge 

stemming from this collaboration supports the generation of ideas, 

facilitates the processes for product design, development, and 

manufacturing, and improves existing products. 

There are a lot of IT research efforts being carried out both in the US and 

the EU related to issues such as product lifecycle management and supply 

chains. In order to foster collaboration and leverage the research 

outcomes from these and other research programs, the French-US 

researchers held a workshop at the National Institute of Standards and 

Technology (NIST, Gaithersburg, Maryland, 6-7 November 2006). This 

French-US workshop aimed at fostering research cooperation between 

French and US researchers and research students in the use of 

Information and Communication Technologies (ICT), computer science 

research for Supply Chain Management (SCM) and Product Lifecycle 

Management (PLM). These domains are of growing importance, as 

witnessed by: 

- National Science Foundation (NSF) programs such as the 

Manufacturing Enterprise Systems (MES) program 

(http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=13342&org

=ENG&more=Y). 

- The European Framework Program for Research and 

Development (FP7) funding for IT and their applications such as 

the FP7 NMP-2007-3.1-1 call (Nanosciences, Nanotechnologies, 

Materials and new Production Technologies, Beyond lean 

manufacturing – new industrial models for product and process 

life cycle). 

- The funding of new centers by NSF and NIST (such as CELDi 

(http://fp.okstate.edu/celdi) and the forthcoming NIST ICT and 

Supply Chain Center (http://www.mel.nist.gov/msid/). 
 

 

 

 

 

 

- The ANR (French National Agency for Research) programs such 

as the Techlog call (Software for modeling and design of complex 

systems). 

This workshop addressed fundamental and practical issues in 

interoperability pertaining to the modeling of complex objects and 

systems, such as the simulation of supply chain processes, the design of 

web-based engineering collaboration support systems, and defining 

semantic and ontology-based models for PLM/Supply chain integration. 

The workshop explored common areas of interest, and sources of 

support for co-operative research among French (EU) and US 

research teams. Several junior researchers and research students 

from France and the US, working in the area of ICT and standards 

were also invited to take part in this workshop, aiming at building 

long lasting research relationships. 

Further, the work done on identifying common research interests, 

whose results are documented in this report, should provide a good 

basis and a good reference to foster research collaboration between 

students and researchers on both sides of the Atlantic, and for funding 

agencies to know of potential synergies. 

This report is available online at: 

http://iutcerral.univ-lyon2.fr/fr_us_workshop_06/

---- The Workshop Steering Committee 

Disclaimer: No approval or endorsement of any commercial product by 

NIST is intended or implied. Certain commercial software systems are 

identified in this paper to facilitate understanding. Such identification does 

not imply that these systems are necessarily the best available for the 

purpose. 

Acknowledgement: We would like to thank NIST researchers, especially, 

Dr. Steve Ray, Dr. Ram D. Sriram, Dr. Hratch Semerjian, and Dr. Simon 

Szykman, for their support and participation. We also thank all the 

participants for their contribution, especially for the inputs to Section 1. 

 

 

 

 

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Table of Contents

1 Executive Summary _______________________________________ 9

Setting the Socio Technical Context of the Problem ____________________ 9

Current Support for International Collaborative Programs________________ 9

Perspectives of the participants____________________________________ 10

Synthesis of Ideas for a collaborative research Program ________________ 10

Collaboration - The way forward __________________________________ 11

2 ICT for PLM and Supply Chains: Research Trends _____________ 12

ICT for interoperability: A science-based approach ____________________ 12

ICT for Networked Organizations: Supply Chain and PLM integration ____ 12

3 French-US Collaboration: A Research Agenda________________ 13

1. Multi-Agent Planning and Scheduling for Dynamic Optimization of 

Supply Networks_______________________________________________ 15

2. Fulfilling Innovation: Robust Product Lifecycle Management ______ 16

3. Decision-Making Models for Supply Chains: A multi-agent system 

approach _____________________________________________________ 18

4. Performance validation of distributed Supply Chain control systems, 

Creation-Verification-Validation through simulation tools, development of 

metrics and benchmarks _________________________________________ 19

5. Vulnerability and Dynamics Analysis of Distributed Supply Chain 

Systems under Disturbances ______________________________________ 20

6. A methodology for prediction and mitigation of undesirable supply 

chain behavior_________________________________________________ 21

7. Eco Design of Industrial Products (EcoDIP) ____________________ 23

8. Using Multi-Agents Modeling to understand Supply Chain Networks 24

9. A framework to analyze collaboration performance ______________ 25

10. Digital Preservation: Data and Knowledge Archiving and Retrieval 

(DKAR)______________________________________________________ 26

11. Early integration of Supply Chain Management in PLM___________ 27

12. Harmonizing Meta-data and Ontologies _______________________ 28

13. Adoption of Model Driven Approaches to Product Lifecycle 

Management __________________________________________________ 29
 

 

 

 

 

 

14. Autonomic Product Lifecycle Management System ______________ 30

4 -APPENDICES _________________________________________ 33

A. Meeting Participants__________________________________________ 33

B. Meeting Agenda _____________________________________________ 40

C. Break-out Sessions Research Key-Points__________________________ 43

D. References to the research _____________________________________ 44

 

 

 

 

8 
 

 

 

 

1 Executive Summary

A US-France workshop on the topic of Information and Communication 

Technologies (ICT) for Supply Chains and Product Lifecycle Management 

(PLM) was held on November 6-7, 2006 at the National Institute of 

Standards and Technology (NIST) in Maryland. There were about forty 

participants from the US and France; representing universities, 

laboratories, and funding agencies from both countries, the European 

Commission and NIST. NIST and the Embassy of France provided 

support for this workshop. 

Setting the Socio Technical Context of the Problem 

The workshop was inaugurated by Dr. Hratch Semerjian, Chief Scientist 

of NIST, emphasizing the importance of global trade, information 

technology and international co-operation. His talk was followed by a talk 

by Dr. Simon Szykman, currently the CIO at NIST, then Director of the 

National Coordination Office for Networking and IT R&D (NITRD), the 

office that co-ordinates IT research across all US federal Agencies. 

Identifying the government as one of the largest procurers of services and 

products, he emphasized that the use of IT is very important to improve 

the effectiveness of government operations. On the second day, Maj. Gen. 

John Phillips (Retd.), a former Deputy Assistant Secretary of Department 

of Defense (Logistics) gave a talk from the perspective of the military 

services. He pointed out that the cost of supply chain and logistics for the 

Department of Defense is $170B/yr. He stressed that the use of ICT is 

critical to achieve cost-effectiveness of defense systems. From a business 

enterprise perspective, Prof. Prabir Bagchi, Senior Associate Dean of the 

School of Business and Professor of Operations and Supply Chain 

Management at George Washington University Business School gave a 

talk on the importance of supply chain management, reverse logistics and 

product design for global competitiveness. 

Current Support for International Collaborative Programs 

Information about the current programs from the EU, US and French 

national agencies was presented to the participants with the intent to 

familiarize them with the existing cooperative research funding 

possibilities and mechanisms. Dr. Miriam Heller, Program Director of the 

Office of Cyber Infrastructure at National Science Foundation (NSF) 

(presenting on behalf of the NSF Office for International Science and 

Engineering), Dr. Bertrand Braunschweig, Program Director for ICT at 

 

 

 

 
 

 

 

 

 

 

ANR (French National Agency for Research), Dr. Laurent Bochereau, 

Counselor for Science and Technology at the EC Delegation to the US, 

Dr. Jean-Philippe Lagrange, Attaché for Science and Technology at the 

French Embassy in the US and Dr. Sue Zeisler from the Office of 

International Affairs at NIST, provided details on different programs, 

processes and mechanisms in their respective agencies. Dr. Abhijit 

Deshmukh, Program Director at NSF (Civil Mechanical Manufacturing 

Innovation Directorate) with Dr. Bertrand Braunschweig and Dr. Lagrange 

participated in a panel discussion that reiterated the possible collaboration 

mechanisms and the future possibilities for encouraging collaborations. 

Perspectives of the participants 

The participants were from different backgrounds and perspectives with a 

common interest in PLM and supply chains. Research topics of the 

participants were related to organizational management, processes and 

products management, green engineering, and mostly technology and 

information systems development. The presentation of the projects by the 

participants covered specific themes including but not limited to: support 

of collaborative work in engineering and supply chains, distributed 

decision making, distibuted and collaborative models for manufacturing 

and supply chains, semantic integration and ontologies. 

Synthesis of Ideas for a collaborative research Program 

The breakout sessions identified areas of exploration that are unique and 

common to the PLM and supply chain community. These areas included: 

- Supporting planning and scheduling. 

- Developing modeling and simulation tools. 

- Facilitating interoperability. 

The creation of models and simulation for forecasting, operations and 

planning for multi-level, distributed product design and supply chain 

organizations were identified as significant components of the 

collaborative research program. To achieve this goal there was an 

agreement that different technologies and formalisms such as multi-agent 

systems, optimization, discrete event simulation and their composition will 

have to be explored. In the area of interoperability across functional and 

organizational boundaries, the importance of formalisms such as 

ontologies, their alignment and standards for information exchange were 

also discussed. Several cross-cutting themes such as human-computer 

interaction, decision-support systems, ICT implementation and socioeconomic impacts, ICT standards, green engineering, long-term 

management of information throughout the life cycle were also discussed 

as areas for exploration. 

 

 

 

 

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There was a general consensus that the research program as envisioned 

would require a collaborative approach that leverages the socio-cultural 

practices, experiences and competences of Europe and US in creating 

valid and useful methods and support systems. 

The workshop’s participants worked on this common research agenda in 

the months following the workshop, through email exchanges, and by 

using the common Web site which had been set up by the University of 

Lyon. 

Collaboration - The way forward 

The representatives from the EU, ANR, NSF and NIST urged the 

participants to use existing collaborative mechanisms supported by their 

agencies as per current programs and also agreed that there was a 

necessity to co-ordinate the research programs to achieve the best 

outcomes (e.g., by means of coordinated call for proposals). To the extent 

possible, the program managers agreed to look into possibilities of coordination of research areas for support. Beyond the funding, there was 

general agreement that the participants themselves would use this 

workshop as an event that laid the foundations for fruitful collaborations 

in defining and influencing the areas of research important for PLM and 

Supply Chain Management (SCM). 

In the following sections we summarize the research trends, as identified 

by the workshop’s participants, and most importantly describe the 

common research agenda which has been produced during and after this 

workshop.
 

 

 

 

2 ICT for PLM and Supply Chains: 

Research Trends 

The workshop sessions addressed both fundamental and applied sides of 

the research and could be summarized as follows: 

ICT for interoperability: A science-based approach 

ICT plays an important role in exchanging data among diverse functional 

groups involved in a supply chain or product lifecycle processes. 

However, specific research is still needed to solve semantic and 

architectural issues. Some presentations focused on the interoperability 

concepts and also barriers due to diversity of used technologies. They also 

reviewed technologies to capture common meaning of data exchanged 

among interoperable information systems (through development of 

ontologies) and to provide comprehensive interoperability frameworks. 

Keywords: semantics, languages, standards, ontologies, simulation 

models.

 

ICT for Networked Organizations: Supply Chain and PLM 

integration 

Supply Chains and PLM are emerging as major concerns for most 

organizations (be it discrete parts manufacturers or process industries such 

as pharmaceuticals and healthcare) and major opportunities for those 

involved in integrating diverse ICT tools and standards. The 

interoperability needs for SC and PLM were discussed and some 

interesting developments and challenges were highlighted. 

Keywords: Integration approaches, multiple-views modeling, knowledge 

management, decision making, collaboration. 

In the following section a brief explanation of the discussions during the 

break-out sessions and possible research collaboration projects are 

outlined. 

 

 

 

 
 

 

 

 

 

 

 

 

3 French-US Collaboration: 

A Research Agenda 

As mentioned earlier, the workshop’s participants have been working, 

both during workshop sessions, and after the workshop, on developing a 

common research agenda. The post-workshop efforts focused on 

strengthening the research Key-Points (Annex C) proposed during the 

workshop sessions and a template has been proposed for the writing of the 

proposals. As a result the Key-Points from the workshop (see Figure 1) 

were collected into an agenda of 14 proposals. 

These proposals are grouped into three topics. The first topic, 

“Supporting Planning and Scheduling,” includes the proposals with the 

aim of: 

Developing Models 

Supporting and Simulation Tools Planning and 

Scheduling

Facilitating Interoperability

Figure 1: Workshop Key-Points of Discussion 
 

 

 

 

 

 

- Investigating effectiveness of various optimization and problemsolving models in distributed SCM settings. 

- Integrating techniques of problem detection, diagnosis and 

optimization to support real time predictive analysis. 

- Developing techniques that enable real-time management of 

exceptions. 

The second topic, “Developing Models and Simulation Tools” consists of 

proposals that attempt to: 

- Develop metrics and benchmarks for design and evaluation of 

PLM/SCM systems. 

- Generalize models for PLM/SCM performance validation. 

- Create, verify and validate models through simulation tools. 

The last topic “Facilitating Interoperability” included proposals that have 

the aim of: 

- Creating guidelines for selection/creation of standards 

- Analyzing methods for sharing knowledge and SC dynamic concepts 

- Investigating current state of standards regarding ontologies and 

writing recommendations for their harmonization. 

The proposal identified in the workshop will be described in this chapter. 

They do not aim at encompassing every research activity of interest in this 

field, but research directions and subjects shared by the participants. 

More detailed key points discussed during breakout sessions are presented 

in Figure 2. 

 

 

 

 

14 
 

 

 

 

1. Multi-Agent Planning and Scheduling for Dynamic 

Optimization of Supply Networks 

Supply network management has transformed more and more into a 

distributed optimization problem in recent years, as firms have specialized 

around core competencies to remain competitive in the global marketplace 

and rely increasingly on partnering relationships for non-core capabilities. 

Globalization has also significantly shortened product time-to-market 

cycles and lead times, placing a greater premium on the ability to quickly 

recognize and respond to potential problems and new opportunities. 

We propose a collaborative research program into the development of 

distributed, execution-driven methods for planning and scheduling, to 

support synergistic operations among supply network partners, dynamic 

real-time response to exceptional production events, and optimized overall 

network performance. Whereas classical approaches to optimization of 

supply network performance have assumed a centralized, static problem 

structure, recent progress in the multi-agent systems, incremental search 

technologies, and execution-sensitive planning and scheduling provide a 

basis for alternative supply network coordination and optimization 

frameworks. 

The proposed project would seek to investigate the efficacy of multi-agent 

planning and scheduling techniques for dynamic, distributed supply 

network optimization. The project would involve 3 main elements: 

1. Development of distributed, execution-sensitive planning and 

scheduling framework – of central interest here is the development of a 

framework based on a coupling of incremental search techniques with 

multi-agent coordination strategies and protocols. One basic design 

question will seek to investigate the value of maintaining prescriptive 

schedules at supply chain nodes that are consistent with the current 

production state (and continuously updated as new real-time information 

is received from suppliers and customers). 

2. Specification of representative dynamic supply network problem 

environment - Ideally in collaboration with an industrial partner, we 

propose to define supply network simulation environment to support 

testing and analysis of the distributed planning and scheduling framework 

to be developed in (1) above. This environment would provide 

mechanisms for executing planned/scheduled activities jointly across the 

network and for introducing relevant dynamic events into the system (e.g., 

unexpected supplier loss of capacity, new, high priority orders, etc.). It 

would also provide a means of controlling the rate of flow of information 

from node to node, allowing the modeling of a range of assumptions about 

“real time” information flow. 

3. Comparative performance analysis of developed techniques – A third 

element would concern an empirical evaluation of the developed approach 

 

 

 

 
 

 

 

 

 

 

to multi-agent supply network optimization, using the simulator developed 

in (2). To provide a basis for comparison, we propose to define an 

appropriate set of baseline strategies, reflective of current supply network 

practice. 

Relevant methods and tools: 

Multi-agent systems; incremental search and optimization technologies; 

discrete event simulation 

Projected Outcome: 

Produce new techniques for optimization of supply network performance 

that make more realistic assumptions about both the distributed nature of 

the problem and the need to synchronize supply chain operations with the 

actual current production state. Overall, we expect this research to yield 

techniques that will lead to measurable gains in supply networks 

performance over current practice 

Impacted Areas: 

- Supporting Planning and Scheduling 

- Developing Models through empirical studies 

- Developing metrics for SCs 

- Designing and Implementing SCs 

- Optimizing distributed product development 

- Integrating decision support systems 

Partnership: 

- Carnegie Melon University 

- George Washington University 

- ENIT - Ecole Nationale d’Ingénieurs of Tarbes 

- University of Lyon 

2. Fulfilling Innovation: Robust Product Lifecycle Management 

Shorter product lifecycles, global competition, globally outsourced supply 

chains and increased regulation make it imperative for companies to focus 

on the effective management of the lifecycle of a product to achieve 

profitability. To get the most out of their innovations, companies need to 

solve a variety of complex challenges: 

- Use whole life performance metrics that provide visibility to 

financial implications of operational decisions. 

- Improved decision-making in the face of higher risks and 

uncertainties associated with demand and supply. 

- Closed-loop process integration between product development and 

supply chain operational activities through the whole life of the 

product. 

The main activities proposed are: 

1. Development of whole life performance metrics. 

 

 

 

 

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2. Research of representation models to link operational decisions to 

financial metrics. 

3. Development of standard case study library and evaluation 

workbench to enable comparison of representations and decisionmaking methods. 

4. Risk and uncertainty modeling and analysis in whole life product 

management. 

5. Representation and decision-support models for analysis of 

environmental/regulatory impact of product development and 

supply chain decisions. 

Relevant methods and tools: 

Ontologies are of interest for (1), (2) and (5). Multi-agent systems are of 

particular interest for (2) and (3). Development of robust optimization 

techniques is of interest for (4). 

Projected Outcome: 

The proposal addresses some key challenges facing US and European 

companies today. Case studies and workbench will provide a foundation 

for researchers to evaluate their models and methods on a common 

framework to enable effective comparison. Performance metrics and the 

financial implication of operational decisions are critical issues for 

companies and will enable them to realize continuous financial control 

leading to improved margins and Return On Assets (ROA). Addressing 

environmental/regulatory issues are becoming major concerns for 

companies and need to be addressed immediately and pose major cost 

elements. Finally, managing risk and uncertainty, while a reality, is poorly 

addressed by most companies. Establishing effective, practical methods 

will provide leading-edge companies tools that give them a competitive 

advantage. 

Impacted Areas: 

- Supporting Planning and Scheduling 

- Developing Models through empirical studies 

- Facilitating Interoperability 

- Developing metrics for SCs 

- Enabling Green Engineering 

Partnership: 

- ValueCHAiNGE 

- National Institute of standards and Technology 

- University of Michigan 

- Ecole Nationale d’Ingénieurs of Tarbes 
 

 

 

 

 

 

- University of Nancy 

- Troyes University of Technology 

3. Decision-Making Models for Supply Chains: A multi-agent 

system approach 

Supply chain management encompasses various processes including 

various conventional logistics activities, and various other processes. 

These processes are supported – to a certain limit – by coordination and 

integration mechanisms, which are long-term strategies that give 

competitive advantage through overall supply chain efficiency. Effective 

SCM and PLM require coordination among the various channel members 

including retailers, manufacturers, and intermediaries. Decisions are 

usually based on department’s own constraints and are optimized locally 

within the departments, but do not assure a global optimum for the 

enterprise. Of course, decision support tools exist for local decision 

making (i.e., planning and scheduling systems, replenishment systems, 

optimization systems, etc.), however an integration of these tools would 

not really solve the problem without a unified approach for modeling and 

analysis of supply chains, which explicitly captures the interactions among 

enterprises and within the departments. 

One of the main benefits of using agent technology for SCM is the use of 

intelligent agents that have the capacity of reasoning, collaborating, 

negotiating and, sharing information. The Multi-Agent Systems (MAS) 

modeling presents an efficient approach for modeling and analysis of 

supply chains. However, the limitation of existing agent systems is that it 

is difficult to make agent-based supply chains, adapt to new products or 

new trading partners because agent systems usually use a fixed set of 

transaction sequences. 

So, the purpose of our actual research in MAS for supply chain 

management is to propose flexible agents systems, which are adaptable to 

the dynamic changes in supply chains, and are capable to learn and change 

their objectives and goals dynamically within their context and 

environment. 

In this context, our main interest in the use of MAS concerns the following 

domains of research: 

- A first issue for agent-based SCM is concerned with coordination and 

collaboration. We will try to develop a collaborative distributed 

information system using communication systems, negotiation 

mechanisms... 

- A second issue we will tackle is agent-based simulation of SC, so as to 

show how agent-based supply chains can gain visibility and efficiency 

through simulation under various strategies. 

Relevant methods and tools: 

 

 

 

 

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Multi-agent architectures; Discrete-event simulations; Supply chain 

decision making. 

Projected Outcome: 

A review of MAS for SC decision making; A methodology for SC 

modeling using MAS; An open architecture for SC-MAS implementation; 

An industrial case study 

Impacted Areas: 

- Developing Models through empirical studies 

- Applicability of alternative methods for simulation of design 

operation and management 

- Integrating decision support systems 

Partnership: 

- University of Lyon 

- University of Central Florida 

- National Institute of standards and Technology 

- Carnegie Mellon University 

4. Performance validation of distributed Supply Chain control 

systems, Creation-Verification-Validation through simulation 

tools, development of metrics and benchmarks 

Simulation is a powerful tool to analyze manufacturing systems for 

purposes of design and on-going operations. Recently, there is increased 

interest in companies to employ simulation modeling and analysis towards 

distributed process control. To support this interest there is a need to create 

an underlying modeling discipline, or structured approach to modeling 

factory operations. The focus of our studies will be on simulation of 

industrial systems with distributed control. We propose to design a 

structured approach to build the simulation models enabling to evaluate 

new holonic Supply Chain Control through metrics and benchmarks.

This approach, coming from six sigma philosophy (DFSS), led us to 

construct emulation models for physical systems associated with control 

systems built on a Multi-Agents platform or on a simulation system. 

Generic special templates will be created to enable the evaluator to obtain 

in a very short time the particular/specific emulation models. 

Relevant methods and tools: 

Discrete event simulation tools, Multi-agents systems 

Projected Outcome: 

Demonstrator to evaluate decision-making process in a Holonic 

Manufacturing System (HMS) context. 
 

 

 

 

 

 

Impacted Areas: 

- Supporting Planning and Scheduling 

- Developing Models through empirical studies 

- Developing metrics for SCs 

Partners: 

- University of Nancy 

- George Washington University 

- Carnegie Melon University 

- National Institute of Standards and Technology 

- University of Central Florida 

5. Vulnerability and Dynamics Analysis of Distributed Supply 

Chain Systems under Disturbances 

Today, under the pressure to be lean, distributed supply chain systems lack 

sufficient buffers to respond to various disturbances (unplanned demand 

distortions, unintended variability, etc). These insufficient buffers play a 

significant role in making the distributed supply chain systems 

increasingly vulnerable to disturbances and can lead to undesirable results 

(excess inventories, deterioration in product quality, increased raw 

material and shipping cost, longer lead times, strained or severed suppliercustomer relationships, and lost business). Higher order interactions and 

dynamics among numerous tiers make the supply chain systems 

vulnerable to such disturbances as well. Often, firm’s efforts to manage 

supply chain systems under these disturbances have led to frustration and 

helplessness because managers have to struggle with the dynamic and 

complex nature of SC, and the inevitable lack of prediction and control. 

Therefore, creating a science for vulnerability analysis and study of the 

dynamics of the distributed supply chain systems under vulnerability 

exploitation scenarios is highly required to provide the basis for robust and 

resilient design of the systems and realistic predictions on their behavior. 

The primary objective of this proposal is the development of sciencebased frameworks for measuring vulnerability of the supply chain systems 

to disturbances and analyzing temporal dynamics of impacts exercised by 

the disturbances. Specifically, a concept of influence matrix to model 

higher order interactions among resources under disturbances, will be 

developed. Then, this influence model will be used for examining the 

situation at hand, caused by disturbances through stability analysis. Using 

these models analytical frameworks will be developed that would measure 

supply chain vulnerability to (i) disruptions using probability distributions 

of situation development when the system is perturbed from the steadystate; and (ii) deviations using probability distributions for state transitions 

based on Markov-chain in inventory control. Importantly, temporal 

dynamics of impact propagation during the course of disturbances will be 

 

 

 

 

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21 

thoroughly modeled and analyzed for different mitigation policies. Finally, 

justification and validation of the notions will be conducted by developing 

a simulation module for dynamic analysis of the distributed supply chain 

systems under disturbance. 

Relevant methods and tools: 

Non-linear differential equations; Entropy theory; Discrete Simulation 

Projected Outcome: 

The proposed work would show considerable promise for the vulnerability 

and the relationship between vulnerabilities and system dynamics, and 

design and simulation of the distributed supply chain systems under 

disturbances. The novel concepts being proposed and the approaches taken 

are expected to make significant inroads into and advance the state-of-theart in design and control of the distributed supply chain systems under 

disturbances. 

Impacted Areas: 

- Developing Models through empirical studies 

- Developing metrics for SCs 

- Designing and Implementating SCs 

Partnership: 

- University of Miami 

- University of Central Florida 

- University of Nancy 

- Ecole Nationale d’Ingénieurs of Tarbes 

6. A methodology for prediction and mitigation of undesirable 

supply chain behavior 

The overall objective of the proposed research is to contribute to the 

advancement of prediction and mitigation of undesirable supply chain 

behavior within short− and long−term horizons by promoting a better 

understanding of the structure that determines the behavior modes through 

the integration of tools such as system dynamics, discrete-event 

simulation, neural networks, model-predictive control, and optimization 

techniques. It is imperative for manufacturing industries to equip 

themselves with tools to detect changes in the supply chain behavior due 

to external and/or internal factors and be prepared to counteract any 

undesirable consequences. The interaction of different supply chain 

components, characterized by the continual co-evolution of system 

components with respect to each other and the environment, create a 

highly non-linear dynamic system. While considerable research has been 

done to understand the dynamic and nonlinear nature of the supply chain 
 

 

 

 

 

 

behavior, there are currently few, if any efforts focused on encapsulating 

the knowledge captured by simulation models into intelligent agents and 

mitigate adverse consequences via robust optimization based on modelpredictive control. This is likely due to the effort required to automate and 

integrate these tools and the lack of clarity on how to conduct and interpret 

this type of analysis. 

This proposal is based on the concept that a supply chain is a complex 

dynamic system consisting of a hierarchical nesting of both continuous 

and discrete dynamics. The discrete dynamics can model the process flows 

while continuous dynamics would represent the cause and effect 

relationships consisting of actions and their direct and indirect 

consequences. However, given the fact that actions may propagate effects 

over time in complicated ways, we will develop a methodology which will 

be able to work with combined continuous-discrete or hybrid models. 

Based on the above premise, we focus on appropriate use and extension of 

system modeling and control theories. This would be done through 

investigation of neural network architectures for behavior pattern 

recognition, model-predictive control using hybrid models, optimization 

techniques, and the design of an integrated methodology. The experiments 

would involve the collaborative work of universities supported by global 

manufacturing enterprises. 

Relevant methods and tools: 

Predictive models, Neural Networks, Software agents 

Projected Outcome: 

- Design of neural network architectures for available models 

representing multiple views of a global and distributed supply chain 

along with a validation test of the integrated methodology to be 

performed within a different global supply chain. 

- Enhance the infrastructure for research between the actual group, by 

facilitating a network of information concerning hybrid modeling 

and supply chain management, while fostering partnerships between 

units actively involved in the supply chain control research and 

technology development. 

Results of this research would have important and immediate application 

to a wide variety of commercial industries, including manufacturing, 

electronic, and aerospace. 

Impacted Areas:

- Developing metrics for SCs 

- Designing and Implementing SCs 

Partnership: 

- University of Central Florida 

 

 

 

 

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- University of Miami 

- University of Nancy 

7. Eco Design of Industrial Products (EcoDIP) 

The recent major concern on sustainable development creates a growing 

interest on product recyclability. More and more strict norms and 

regulations will be prescribed to companies in order to increase the level 

of recyclability of their products. It is now clear that selling products 

which are compliant with such norms will become more and more a 

competitive advantage for companies.

Usually described in natural language, the concerned norms can be 

difficult to interpret for the product designer. Hence there is an increasing 

need for tools to verify the compliance of a product for given norms and 

standards. Towards that purpose, a first step is to define an extended 

product model to include data for checking the recyclability of a product, 

for the creation of ad-hoc tools for an on-line verification of compliance 

of the product under design with norms and standards. 

The objectives of the project are: 

- To analyze the already available standards and regulations for 

Green Engineering. 

- To identify the product data that needs to be captured for 

verification of these norms and standards. 

- To define an extended product model adding these data to those 

already defined during product design. 

- To specify the requirements regarding a decision support system for 

Green Design allowing an on-line verification of the compliance of 

a product with a given norm or standard. 

- To develop a prototype of the system. 

Relevant methods and tools: 

Ontologies; decision support systems; knowledge engineering

Projected Outcome: 

Makes cheaper and quicker the verification of the compliance of a product 

with recyclability norms and standards 

Impacted Areas: 

Enabling Green Engineering 

Partnership: 

- Ecole Nationale d’Ingénieurs of Tarbes 

- University of Michigan 

- Grenoble University 

- Troyes University of Technology 
 

 

 

 

 

 

8. Using Multi-Agents Modeling to understand Supply Chain 

Networks 

Supply Chain Networks (SCN) are complex dynamic networks that are 

produced by the multiple interactions being held between the components 

of the supply chain, while being used as a support for these interactions. 

A Supply Chain Network is distributed, dynamic, and provides a structure 

to handle information and/or material flows between its components. The 

SCN performance is thus dependent on the network configuration and the 

material/information flow organization. 

Multi-agents modeling of such a network, will offer the possibility to 

represent different levels of the global system: at the micro level, the 

system’s components represented by agents (with a local perception/action 

loop) capture the fine grain features of the global system. These 

components interact with each other, through different protocols 

(cooperation, negotiation, coordination, etc) in order to produce global 

properties/behaviors that could be observed at the macro level of the whole 

system. 

In such a configuration, the coupling between the micro level of the system 

and its macro level is achieved through the global system’s dynamic that 

need to be captured and organized. This intermediate level (meso level) is 

the level where the system has to develop its cognition (intelligence) 

capacity. 

We believe that modeling SCN through these 3 levels: micro level 

(component), micro level (system), meso level (interaction and information 

exchange) will help to better understand the SCN as a complex system and 

help to improve its performance. 

The MAS paradigm offers naturally the ability to represent in the same 

framework these different levels, and to associate to each level a specific 

modeling tool to represent specific aspects of the system, providing by this 

way, an intelligent hybrid approach to model a Supply Chain Network. 

Our proposal is thus to provide a multi-agents framework, allowing the 

representation of the SCN at the three levels (micro, meso, macro) 

described above and endow these frameworks with specific multi-agents 

mechanisms that facilitate the integration of different specific models, and 

make the system to use its network structure as a support for its cognition 

(intelligence) emergence. 

Relevant methods and tools: 

Multi-agent systems; discrete simulation; optimization methods; ontologies 

Projected Outcome: 

Better understanding/modeling of supply chain networks (SCN) as a 

complex system 

Better (qualitative and quantitative) performance of SCN 

Impacted Areas: 

 

 

 

 

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- Supporting Planning and Scheduling 

- Facilitating Interoperability 

- Designing and Implementing SCs 

- Optimizing distributed product development 

- Integrating decision support systems 

Partnership: 

- University of Lyon 

- National Institute of standards and Technology 

- University of Maryland Baltimore 

- Carnegie Mellon University 

- University of Central Florida 

9. A framework to analyze collaboration performance 

When competitiveness, responsiveness and customer satisfaction are 

keywords of a successful management in a business area, companies cannot 

work in an autonomous way anymore. They have to get closer to their 

supply chain partners and to optimize their relations, to interface and to 

integrate their information systems and decision-making in order to 

synchronize product flows and activities. 

In this context, we propose a general framework that characterizes the 

performance of the collaboration in supply chains. This framework is based 

on two models: a collaboration characterization model (CC model) and a 

collaboration-oriented performance model (CoP model). Both are based on 

main supply chain business processes. 

CC model: The framework characterizing collaboration in supply chains 

focuses on information exchanged between partners as well as on the 

exploitation of this sharing. Thus, this first model is based on many facets 

such as the characterization of the perimeter of the exchanges along the 

supply chain, the use of this collaboration, its intensity and its regularity. 

CoP model: Collaborative actions across the organization and throughout 

the supply chain can significantly enhance individual and global 

performance. Various indicators, which illustrate the impact of potential 

collaborative practice benefits, allow the measure of the performance. 

These performance indicators can be classified in order to propose a 

structured set of indicators. In the CoP model, we keep a well-known 

classification adopted by many models: reactivity–reliability–flexibility–

quality and cost assessment. The set of performance indicators associated to 

the CC model has to reflect this performance classification. 

A collaboration profile and a perceived collaboration-oriented performance 

profile result from these two models. The application of this general 
 

 

 

 

 

 

framework on an industrial case study allowed its validation. Furthermore, 

it allowed the estimation of the coherence and the efficiency of 

collaborative actions practiced by the company. 

Relevant methods and tools: 

Business process approaches, qualitative and analysis approaches. 

Projected Outcome: 

Bringing together companies, through frameworks and tools allowing them 

to qualify and to estimate the performance of their supply chain. Focusing 

on the different ways to collaborate with partners, without forgetting related 

stakes and risks. Instantiation and validation on various industrial case 

studies will be undertaken. 

Impacted Areas: 

- Developing Models through empirical studies 

- Developing metrics for SCs 

Partnership: 

- University of Lyon 

- University of Maryland Baltimore 

- George Washington University 

10.Digital Preservation: Data and Knowledge Archiving and 

Retrieval (DKAR) 

A tremendous growth in computational power, and in networking 

bandwidth and connectivity, has resulted in an explosion in the number of 

organizations making digital information available. Transactions among 

all types of organizations are being conducted using digital forms that are 

taking the place of more traditional media such as paper. However, while 

we are still able to read our written heritage from several thousand years 

ago, the digital information created merely a decade ago is in serious 

danger of being lost. With product lifecycles often far longer (i.e., aircraft 

fifty years) than the expected lifetime of a manufacturing software 

application used to interpret the data (approximately three years), or of the 

technologies used to store and retrieve the data (approximately ten years), 

searching for archived information is routinely problematic. 

The constant input of effort, time, and money to handle rapid 

technological and organizational advance is considered the main 

stumbling block for preserving digital information beyond a couple of 

years. 

Because digital preservation affects such a diverse community, it is useful 

to distill the issue down to an elemental set of concepts, relationships and 

processes common to a wide cross-section of digital preservation 

 

 

 

 

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activities. These reference points serve as the common ground from which 

joint discussion and mutually beneficial collaboration can proceed. 

A reference model is expected, by establishing minimum requirements for 

an archive along with a set of archival concepts. Such models will provide 

a common framework from which to view archival challenges, particularly 

as they relate to digital information. It should also provide a basis for more 

standardization and, therefore, a larger market that ICT providers can 

support in meeting archival requirements. The archived information must 

be useable by consumers who are separated in time, distance and 

background from the producers. 

Relevant methods and tools: 

 Specification standards; knowledge engineering; semantic web 

Projected Outcome: 

- Provide a framework for the understanding and increased awareness 

of archival concepts needed for Long Term digital information 

preservation and access, including terminology and concepts for 

describing and comparing architectures and operations of existing 

and future archives. 

- Provide the concepts needed by PLM and SC partner companies to 

be effective participants in the preservation process. 

- Provide a foundation that may be expanded by other efforts to cover 

long-term preservation of information that is NOT in digital form 

(e.g., physical media and physical samples). 

Impacted Areas: 

Developing methods and technologies for long term retention 

Partnership: 

- National Institute of standards and Technology 

- University of Lyon 

- University of Dijon 

- Troyes University of Technology 

11.Early integration of Supply Chain Management in PLM 

Currently, there is no integration of SCM throughout the entire product 

development life cycle. The product is designed by a group without any 

supply chain design recommendation or feedback on how the supply chain 

would manufacture the part. By designing and producing parts to perform 

according to customer specifications or requirements without the 

involvement of the supply chain could lead to products which were based 

on lack of knowledge about manufacturing process. This forces the design 
 

 

 

 

 

 

group to reconsider how the part is designed due to component 

manufacturing capability, costs, and timing. Any single part that needs to 

be redesigned due to these issues can affect how all the other parts in the 

product interact with that part and each other, possibly resulting in their 

redesign as well. 

To overcome this problem a product would need to go through a redesign 

process based on the supply chain management feedback on the 

component(s). Effectively the whole product development process has to be 

reinitiated, costing valuable time, money, and effort that has an impact on 

the business case and timing for the product. 

The aim is to create a standardized design process that allows organizations 

to be profitable by integrating the supply chain early in the product 

development cycle. This should lead to manufacturable and cost effective 

designs. 

There is a need to create a business model that includes SCM as part of the 

Product development cycle. For example, from the time that a request for 

quotation from a potential customer to the submission of the quotes, the 

design team has to work with core supply groups in the development cycle 

to provide the knowledge of the manufacturing capabilities. Such an 

interaction early in the design process could lead to the emergence of right 

designs that are manufacturable without problems. 

Relevant methods and tools: 

Optimization methods 

Projected Outcome: 

Integration of SCM concepts in the first phases of PLM 

Impacted Areas: 

- Optimizing distributed product development 

- Integrating decision support systems 

Partners: 

- Delphi, Technical Center Rochester 

- Carnegie Melon University 

- Ecole Cenrale of Nantes 

- University of Reims 

- University of Lyon 

12.Harmonizing Meta-data and Ontologies 

Too many ontologies are being created which focus on PLM. These are 

being created at different levels across different domains. Even within the 

same domain, some ontologies take a top-down approach to definitions, 

while others take a bottom-up approach. There is a need to work through all 

 

 

 

 

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these approaches and define a streamlined approach with inter-ontology 

bindings and, probably, a unification of the more formal AI and the more 

practical engineering approach. The projected outcome is a formal 

representation of what information in PLM should encompass. 

Relevant methods and tools: 

Muli-agent systems; ontologies; ontology-mappings 

Projected Outcome: 

A demonstrator (testbed) useful to evaluate a decision-making process in a 

HMS context 

Impacted Areas:

- Developing Models through empirical studies 

- Facilitating Interoperability 

- Integrating decision support systems 

- Harmonizing Meta-data/ontologies 

Partnership: 

- University of Michigan 

- National Institute of Standards and Technology 

- University of Buffalo 

- Purdue University 

- University of Reims 

- University of Dijon 

13.Adoption of Model Driven Approaches to Product Lifecycle 

Management 

Computer science as a field is still focusing on technologies to improve 

design, production and maintenance of computer programs. The most 

recent approaches under the name of Model Driven approaches do focus on 

meta-modeling. These approaches are dedicated to provide frameworks 

managing various meta-models (related with ontologies) and, to create 

interoperability between corresponding models. While Model-Driven 

approaches have shown to be useful, there are no developments in this area 

relevant to applications dedicated to PLM. This is partly due to the fact that 

most experts who develop PLM-dedicated applications are not often 

computer scientists, and conversely computer scientists are not PLM 

experts. A second factor is related to the complexity of the information 

used along the PLM phases. No single ontology can address all the PLM 

concepts. Many meta-models (Core Product Model, Standard for the 

Exchange of Product model data, Product Process Organization model, 

Function Behavior State model, etc.) have been developed but none of them 

by themselves are sufficient for PLM management. It should be possible to 

take advantage of existing Model Driven Approaches to try to connect 
 

 

 

 

 

 

various ontologies together and to provide a kind of framework for 

adaptation to PLM needs. As an initial thrust, the work should address: 

- Common points between various meta-models. 

- State of the art of model-driven approaches. 

- Definition of scenarios where interoperability between the current 

models should be solved by model-driven approaches. 

- Key points for a framework managing interoperability with a 

model-driven approach. 

- Measures of the correspondent complexity: many things seem 

logical but are very hard to solve when real complex problems are 

under focus. 

Relevant methods and tools: 

Ontologies (standards and others); meta-meta modeling; ruled-base 

programming 

Projected Outcome: 

Building a framework that links various heterogeneous applications. 

Achieve a better management of interoperability. 

Impacted Areas:

- Developing Models through empirical studies 

- Facilitating Interoperability 

- Optimizing distributed product development 

- Harmonizing Meta-data/ontologies 

Partnership: 

- Grenoble University 

- National Institute of Standards and Technology 

- University of Buffalo 

- Purdue University 

- University of Dijon 

- University of Lyon 

14.Autonomic Product Lifecycle Management System 

In this proposal an open software architecture for self-managing/selfhealing software agents will be developed to address the computational 

(e.g., aggregation, integration, and analysis) activities performed during 

product realization. Semantic web technologies and tools will be 

investigated to improve product information access, search, discovery, 

association, interoperability, and archiving across distributed heterogeneous 

product management software systems. 

In current practice, information captured while managing products is often 

incomplete, unstructured, and is mostly proprietary in nature, making it 

difficult to index, search, refine, reuse, distribute, browse, aggregate, and 

annalyze knowledge across heterogeneous organizational information 

 

 

 

 

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systems. As part of this proposal an overreaching information framework 

will be developed using graph-theoretical modeling of concepts associated 

with product realization to capture, organize, share, analyze, and archive 

the content, concepts, and cotexts of product information across different 

phases of product lifecycle in a distributed environment. As part of the 

proposal autonomic agents will be developed to manage the computational 

activities in a distributed heterogeneous product management software 

system. The objectives of the autonomic agents during product realization 

will be similar to any autonomic agents, i.e., self-configuration, selfhealing, self-optimization, and self-protection. The system will provide 

product designers and manufacturers easy access to relevant product 

information while keeping the complexity of the system hidden from the 

user. 

Relevant methods and tools: 

Multi-agent systems; Ontologies; Semantic Web; Product Platform 

Analysis; Heuristics. 

Projected Outcome: 

The design of a flexible, accessible, and transparent PLM system that will 

help capture, organize, share, analyze, and archive the content, concepts, 

and contexts of product information across different phases of product 

lifecycle in a distributed environment. 

The deliverables will be (1) a semantic framework, and (2) an autonomic 

agent-based computational framework, for product information 

management. 

Impacted Areas: 

- Facilitating Interoperability 

- Applicability of alternative methods for simulation of design 

operation and management 

- Optimizing distributed product development 

- Integrating decision support systems 

- Developing methods and technologies for long term retention 

- Harmonizing Meta-data/ontologies 

Partnership: 

- Penn State University 

- University of Buffalo 

- Purdue University 

- Ecole Centrale of Nantes 

- Troyes University of Technology 

- University of Lyon 

- University of Dijon 
 

 

 

 

 

 

 

 

 

 

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4 -APPENDICES 

A. Meeting Participants 

Governmental representatives & keynote speakers 

Hratch Semerjian Chief Scientist, NIST 

100 Bureau Drive, Stop 1800 

Gaithersburg, MD 20899-1800 

Tel: (301) 975-5555, (301)869-8972 

hratch.semerjian@nist.gov 

Simon Szykman Director, National Coordination Office for 

Networking and Information Technology 

Research and Development (NCO/NITRD) 

4201 Wilson Boulevard, Suite II-405, Arlington, 

VA 22230 

Tel: (703) 292-4873, Fax (703) 292-9097 

szykman@nitrd.gov 

Abhijit Deshmukh MIE Department, ELAB 220 

University of Massachusetts 

Amherst, MA 01003-2210 

Tel: (413) 545-1615, Fax: (413) 545-1027 

deshmukh@ecs.umass.edu 

& 

Program Director, Directorate for Engineering - 

NSF 

4201 Wilson Boulevard, Arlington, VA 

Tel: (703) 292-7061, Fax: (703) 292-9056 

adeshmuk@nsf.gov 

Miriam Heller Program Director, Office for Cyberinfrastructure - 

NSF 

4201 Wilson Boulevard, Arlington, VA. 

Tel : (703) 292-7025, Fax : (703) 292-9060 

mheller@nsf.gov

Susan F. Heller-Zeisler International Affairs Officer, Office of 

International and Academic Affairs - NIST 
 

 

 

 

 

 

 

 

 

 

34 

100 Bureau Drive, 

Stop 1090, Gaithersburg, MD 20899-1090 

(301) 975-3111, Fax (301) 975 3530 

susan.heller-zeisler@nist.gov

Laurent Bochereau Science Counselor 

Delegation of the European Commission to the 

US 

2300 M Street, NW - Washington, DC 20037 

Tel: (202) 862-9500, Fax: (202) 429-1766 

Laurent.Bochereau@cec.int.eu 

Bertrand Braunschweig ICT Programs Manager, Dpt. Matière et 

Information- ANR 

212, rue de Bercy - 75012 Paris 

Tel:01 78 09 80 00 

Bertrand.BRAUNSCHWEIG@agencerecherche.fr

Jean Philippe Lagrange Scientific Attaché 

Embassy of France 

4101 Reservoir Road NW - Washington DC 

20007 

Tel: 202 944 6237, Fax 202 944 6244 

jean-philippe.lagrange@ambafrance-us.org

US Participants 

Prabir K. Bagchi School of Business – G. Washington University 

Duques Hall 660, Washington, DC 20052 

Tel:(202) 994-4988 

bagchi@gwu.edu

Sohyung Cho Dept Industrial Eng. - Univ. of Miami 

281 McArthur Building, Coral Gables, FL 33146 

Ph: 305-284-2370, F: 305-284-4040 

scho@miami.edu

Andreas Craens MSID/MEL Laboratory, NIST 

100 Bureau Dr, Stop 8263, Gaithersburg, MD 

20899-8263 

(301) 975-2989 

andreas.craens@nist.gov 

Magdy Helal Industrial Eng. & Mngt Sys Dep. University of 

Central Florida 

4000 Cl Florida Blvd, Orlando, Florida 32816 
 

 

 

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35 

Cell:321 945 8982, F: 407 823 3413 

mhelal@mail.ucf.edu 

Mark Hepworth Global Supply Management, Delphi Energy and 

Chasis Systems, Technical Center Rochester 

P.O. Box 20366, Rochester, NY 14602-0366 

Ph: 585-359-6138, F:1-866-480-0951 

mark.e.hepworth@delphi.com

Boonserm Kulvatunyou MSID/MEL Laboratory, NIST 

100 Bureau Dr, Stop 8263, Gaithersburg, MD 

20899-8263 

(301) 975-6775 

kulvatun@nist.gov

Sanjay Jain The George Washington University & NIST 

Funger Hall, Suite #415 

2201 G St, N.W., Washington, DC - 20052 

Phone: 202-994-5591, Fax: 202-994-2736 

jain@gwu.edu

Albert T. Jones Enterprise Systems Group, MSID, MEL 

Laboratory - NIST 

100 Bureau Drive, Stop 1800 

Gaithersburg, MD 20899-1800 

 (301) 975-3554, Fax: (301) 258-9749 

jonesa@nist.gov

Nanda Jyotirmaya Penn State University 

332, Leonhard Building, University Park, PA, 

16802 

Phone: 814.861.7908 (H) 

jyotirmaya@gmail.com

Mahesh Mani MSID/MEL Laboratory, NIST 

100 Bureau Dr, Stop 8263, Gaithersburg, MD 

20899-8263 

(301) 975-5219 

mahesh.mani@nist.govnn

Igor Miletic MSID/MEL Laboratory, NIST 

100 Bureau Dr, Stop 8263, Gaithersburg, MD 

20899-8263 

(301) 975-4626 
 

 

 

 

 

 

 

 

 

 

36 

igorm@cme.nist.gov

Lalit Patil University of Michigan 

2350 Hayward St, 2250 G.G. Brown Labs 

Ann Arbor, MI 48109 

(734) 763 4056, (734) 764 2143 

lpatil@umich.edu

Yun Peng Dept of Computer Sc. & Electrical Eng. 

University of Maryland Baltimore County 

1000 Hilltop Circle, Baltimore, Maryland 21250 

Tel: (410) 455-3816, F: (410) 455-3969 

ypeng@umbc.edu

John F. Phillips Enterra Solutions, LLC, Washington Operations 

Center 

1921 Gallows Road, Suite 540, Vienna, VA 

22182 

Tel: 571.336.0072, Fax: 571.336.0073 

jp31442@comcast.net 

Luis Rabelo Industrial Engineering & Management Systems 

Dpt. - University of Central Florida 

4000 Central Florida Blvd Orlando, Florida 

32816 

Tel: 407-882-0285 

lrabelo@mail.ucf.edu

Sudarsan Rachuri MSID/MEL Laboratory - NIST 

100 Bureau Dr, Stop 1800, Gaithersburg, MD 

20899-1800 

(301) 975-4264, Fax: 301-975-8273 

sudarsan@nist.gov

Karthik Ramani School of Mechanical Eng. - Purdue University 

585 Purdue Mall, West Lafayette, IN 47907-2040 

Ph: (765) 494-5725, F: (765) 494-0539 

ramani@purdue.edu

Venkat Rajan ValueCHAiNGE, 

1104 Salado Drive Allen, TX 75013, Tel: (214) 

850-8527 

venkat.rajan@valuechainge.com

Steven R. Ray MSID, MEL Laboratory - NIST 

100 Bureau Dr, Stop 1800, Gaithersburg, MD 

20899-1800 
 

 

 

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 (301) 975-3524/3508, Fax: (301) 258-9749 

ray@nist.gov

Ram Sriram MSID MEL Laboratory - NIST 

100 Bureau Dr, Stop 1800, Gaithersburg, MD 

20899-1800 

 (301) 975-3507, Fax: (301) 975-4482 

sriram@nist.gov

Eswaran Subrahmanian Design and Process Group, MSID/ MEL - NIST 

(301) 975-6083 

eswaran@nist.gov

+ Institute for Complex Engineered Systems 

Carnegie Mellon University - College of Engg 

1201 Hamburg Hall, Pittsburgh, PA 15213-3890 

(412) 268-5221, Fax (412) 268-5229, 

sub@cmu.edu

Kesavadas Thenkurussi Virtual Reality Lab, Mechanical & Aerospace 

Eng. University at Buffalo, 1006 Furnas Hall, 

Buffalo, NY 14260 

Tel: 716 645 2593 x2229, F: 716 645 3668 

kesh@eng.buffalo.edu

Stephen Smith Carnegie Mellon University 

5000 Forbes Av, Pittsburgh, PA 15213 

Phone: (412) 268-8811, Fax: (412) 268-5569 

sfs@cs.cmu.edu

Kurt Wescoe Institute For Software Research Int’l 

Carnegie Mellon University, 

5000 Forbes Av., Pittsburgh, PA 15213 

Tel: 412-268 7077, fax:412-268-2338 

kwescoe@andrew.cmu.edu

French Participants 

Alain Bernard IRCCyN UMR CNRS 6597 Dept Ingénierie des 

Produits et Systèmes Industriels 

1, rue de la Noë, BP 92101, 44321 Nantes Cedex 

03 FR 
 

 

 

 

 

 

 

 

 

 

38 

tel : + 33 2 40 37 69 53, fax : +33 2 40 37 69 30 

Alain.Bernard@irccyn.ec-nantes.fr 

Abdelaziz Bouras LIESP, Université de Lyon (ULL) 

160 boulevard de l'Université, 69676 BRON 

Cedex 11, FR 

Tel: +33/0 4 78 77 31 46, Fax: +33/0 4 78 00 63 

28 

abdelaziz.bouras@univ-lyon2.fr

Benoît Eynard LASMIS - Université de Technologie de Troyes 

12 rue Marie Curie - BP2060, 10010 Troyes 

Cedex, FR 

T: 03.25.71.58.28 - F: 03.25.71.56.75 

benoit.eynard@utt.fr

Sebti Foufou IEM, Le2i, Univ. de Bourgogne, BP 47870 

21078 Dijon, FR, Tel: 33 3 80 73 51 79 

sfoufou@u-bourgogne.fr

Bernard Grabot LERI, ENIT 

47 avenue d'Azreix , 65016 Tarbes Cedex, FR 

Tel: +33 5 62 44 27 21, Fax: +33 5 62 44 27 08 

bernard@enit.fr

France-Anne Gruat-LaForme 

LIESP - INSA, Bat B. Pascale 

20 av Jean Capel - 69621, Villeurbanne Cedex, 

FR 

Tel: 33 4 72 43 62 34 

France-anne.Gruat-la-forme@insa-lyon.fr

Salima Hassas LIESP - Bat Nautibus 

43 Bd du 11 Nov. 1918, 69622 Villeurbanne 

Cedex, FR 

Tel: 04.72.44.58.90 Fax: 04.72.43.15.36 

salima.hassas@liris.cnrs.fr

Mael Hillérau CReSTIC, Institut de Formation Technique 

Supérieur Université de Reims 

7, bd Jean Delautre, 08000 Charleville-Mézières, 

FR 

Tél. : (+33) 3 24 59 64 94 

mael.hillereau@univ-reims.fr

Thomas Klein CRAN - University of Nancy 

15, Avenue Jacques Parisot 
 

 

 

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39 

70800 Saint Loup sur Semouse, FR 

Tel: 33 3 84 93 52 52 

Thomas.Klein@cran.uhp-nancy.fr

Christian Minich CReSTIC, EA 3804 

Université de Reims, Reims, FR 

T: +33.3.87.54.77.99, F: +33.3.87.31.53.09 

minich@univ-metz.fr

Gilles Neubert LIESP , Université de Lyon (ULL) 

160 Bd de l'université - 69676 Bron Cedex, FR 

Tel: +33.478.774.484, Fax: +33.478.006.328 

gilles.neubert@univ-lyon2.fr

Frédéric Noël G-Scop, INPG, Dept. Ingénierie des Fluides & 

Mécanique - ENSHMG 

BP53, 38041 Grenoble Cedex, FR 

tel:+33.476.827.056 fax:+33.476.827.043 

Frederic.Noel@inpg.fr

Yacine Ouzrout LIESP, Université de Lyon (ULL) 

160 Bd de l'université, 69676 Bron Cedex, FR 

Tel: +33.478.774.484, Fax: +33.478.006.328 

yacine.ouzrout@univ-lyon2.fr
 

 

 

 

 

 

B. Meeting Agenda 

Monday Nov. 6th, 2006

09:00 Welcome, Hratch Semerjian, Chief Scientist, NIST

09:15 Inaugural Presentations 

 Simon Szykman, Director for Networking and Information 

Technology Research and Development, NCO 

 Jean-Philippe Lagrange, Science Attaché, French Embassy, 

FR 

09:45 Panel - International collaboration programs and projects in 

US and FR research agencies

 Sue Zeisler, Office of International Affairs, NIST (Moderator)

 Miriam Heller, Office of CyberInfrastructure, NSF 

 Laurent Bochereau, Counselor for Science and Technology, 

EC (US Delegation) 

 Bertrand Braunschweig, ICT Programs Manager, ANR 

11:15 Break 

11:30 French Labs Presentations

 R. D. Sriram (Moderator) 

 Short presentations (10') to introduce the research being done 

and current collaborations

 B. Grabot (Enit, Tarbes), A. Bernard (EC Nantes)

 B. Eynard (UTT Troyes), Ch. Minich (University Metz) 

12:15 Break

01:15 US Labs Presentations

 R. D. Sriram (Moderator) 

 Short presentations (10') to introduce the research being done 

and current collaborations

 L. Rabelo (University C. Florida), Y. Peng (UMBC), K. 

Ramani (Purdue University)

 T. Kesavadas (Buffalo University), S. Smith (CMU), L. Patil

(University Michigan) 

 

 

 

 

40 
 

 

 

 ICT for SCM & PLM: A Research Agenda for French-US collaboration 

 

 

 

 

41 

02:15 Technical Session – Part 1 

 - PLM/SCM Integration: Technology and implementation issues, 

 V. Rajan (& Moderator) 

- Presentation of the research directions of the participants (10' 

each) 

03:15 Break

03:30 Technical Session – Part 2

 V. Rajan ( Moderator) 

 Presentation of the research directions of the participants (10' 

each)

 (with a short break of 10' at 04:30) 

05:30 Adjourn 

 

Tuesday Nov. 7th, 2006

08:30 Keynote Presentations 

- Supply Chain Management and the Role of ICT and Standards 

 Prabir K. Bagchi, George Washington University 

- Net-Centric Logistics

 Maj. Gen. John Phillips, ENTERRA Solutions

09:30 Break-Out Session I Break-Out Session II 

 ICT for PLM ICT for Supply Chain 

 • Identify problems and 

opportunities 

• Identify the ICT needed to 

achieve solutions 

• Prioritize the ICT themes 

to address in a 

collaboration perspective 

• Analyze and detail each 

ICT theme 

• Generate 

recommendations

• Identify problems and 

opportunities 

• Identify the ICT needed to 

achieve solutions 

• Prioritize the ICT themes 

to address in a 

collaboration perspective

• Analyze and detail each 

ICT theme 

• Generate 

recommendations

 Moderators: S. Rachuri Moderators: A. Jones 
 

 

 

 

 

 

 Moderatos: B. Grabot Moderato: E.Subrahmanian 

11:30 Break

11:45 Joint Session 

 Common ICT themes for PLM and Supply Chain

 • Presentation of the Break-Out-Sessions results 

• Analyze and generate common ICT themes 

• Generate joint recommendations

 Moderators: Sudarsan Rachuri , Al Jones

01:00 Break

02:00 Panel - General Wrap-up

 Moderators: Abhijit Deshmukh, NSF 

 Moderators: Bertrand Braunschweig, ANR 

 Jean-Philippe Lagrange, French Embassy

 Moderators: Abdelaziz Bouras, University of Lyon 

• Results from the sessions (Session Moderators) 

• Identification of collaboration mechanisms 

03:30 Closing

 

 

 

 

42 
 

 

 

 ICT for SCM & PLM: A Research Agenda for French-US collaboration 

 

 

C. Break-out Sessions Research Key-Points1

Figure 2: Break-out session Key-Points

 

1 See http://iutcerral.univ-lyon2.fr/fr_us_workshop_06/US_FR_Wshp/us_fr_wshp_structure.html 

 

 

43 
 

 

 

 

 

 

D. References to the research 

1. Pannequin R., Thomas A. Cooperation between business and 

holonic manufacturing decision systems. Communication au 

congres international IFAC-INCOM06, St Etienne- France, 2006. 

2. Klein T., Thomas A. A simulation testbed for decision system 

evaluation in a furniture manufacturing group. Communication au 

congres international IFAC-INCOM06, St Etienne- France, 2006. 

3. El Haouzi H., Thomas A. A Methodological approach to build 

Simulation Models of Manufacturing Systems with Distributed 

Control. IESM05 Internl Conference on Industrial Engineering and 

Systems Management 2005, Marrakech- Morocco,Mai 2005. 

4. Lalit Patil, Debasish Dutta, and Ram Sriram. Ontology 

formalization of product semantics for Product Lifecycle 

Management. In Proceedings of IDETC/CIE 2005 ASME 2005 

International Design Engineering Technical Conferences & 

Computers and Information in Engineering Conference, Longbeach, 

CA, September 2005. 

5. Lalit Patil, Debasish Dutta, and Ram Sriram. Ontology-based 

exchange of product data semantics. IEEE Transactions on 

Automation Science and Engineering, 2(3):213-225, July 2005. 

6. Frédéric Noël and Serge Tichkiewitch. Shared dynamic entities 

technology to support distant coordination in design activity. 

Annals of the CIRP, 53-1:163-166, 2004. 

7. F. Noël and D. Brissaud. Dynamic data sharing in a collaborative 

design environment. International Journal of Integrating 

Manufacturing, 16(7-8):546-556, 2003. 

8. F. Noël, D. Brissaud, and S. Tichkiewitch. Integrative design 

environment to improve collaboration between various experts. 

Annals of the CIRP, 52-1:pp. 109-112, 2003. 

9. Cho, S., Prabhu, V.V., Sliding mode dynamics in continuous 

feedback control for distributed discrete-event scheduling, 

Automatica, 38(9), 2002, 1499-1515. 

10. Cho, S., Distributed time-driven simulation for modeling, analysis, 

and control of manufacturing shop-floor, Computers and Industrial 

Engineering, 49, 2005, 572-590. 

 

 

 

 

44 
 

 

 

 ICT for SCM & PLM: A Research Agenda for French-US collaboration 

 

 

 

 

45 

11. Cho, S., Buitrago, J., Iakovou, E., Design of resilient supply chains: 

effective use of influence matrices in disruption preparedness, 

CARV 2007 Proceedings. 

12. E.H. Nfaoui, O. ElBeqqali, Y. Ouzrout, A. Bouras, An Agent-Based 

distributed simulation for the supply chain: Negotiation protocols 

between collaborative agents, European Simulation and Modeling 

Conference, ESM’06, Toulouse, October 2006, 8 p. 

13. S. Chehbi Gamoura, Y. Ouzrout, A. Bouras, Multi Criteria decision 

making for supply chain partners: A Multi-Agent simulation 

approach, INCOM’06, Saint-Etienne, May 2006, 6 p. 

14. Chehbi, S., Ouzrout, Y., and Bouras, A., "Multi-Layers Supply 

chain modeling based on Multi-Agent Approach," Emerging 

Solutions for Future Manufacturing systems. Ed. L.M. Cam., 

Springer, ISBN 0-387-22828-4, pp. 307-314, 2004. 

15. Smith, S.F., A. Gallagher, T. Zimmerman, L. Barbulescu and Z. 

Rubinstein, “Distributed Management of Flexible Times 

Schedules,” CMU Robotics Institute Technical Report, October 

2006 (submitted for publication). An earlier paper based on this 

work appeared as Smith, S.F., A. Gallagher, T. Zimmerman, L. 

Barbulescu, and Z. Rubinstein, “Multi-Agent Management of Joint 

Schedules”, Proceedings AAAI Spring Symposium on Distributed 

Plan and Schedule Management, Palo Alto, CA, March 2006. 

16. Cicirello, V. and S.F. Smith, “Wasp-based Agents for Distributed 

Factory Coordination,” Journal of Autonomous Agents and MultiAgent Systems, 8(3): 237-266, May 2004 

17. Goldberg, D., V. Cicirello, M.B. Dias, R. Simmons, S.F. Smith and 

T. Stentz, “Market-based Multi-Robot Planning in a Distributed 

layered Architecture,” In Multi-Robot Systems: From Swarms to 

Intelligent Automata- Volume 2, Proceedings of the 2003 

International Workshop on Multi-Robot Systems, Kluwer Academic 

Publishers, 2003, pp 27-38. 

18. Nanda, J., Simpson, T. W., Kumara, S. R. T., and Shooter, S. B., 

2006, "Product Family Ontology Development Using Formal 

Concept Analysis and Web Ontology Language," ASME Journal of 

Computing and Information Science in Engineering, 6(1), pp. 103-

113. 

19. Nanda, J., Thevenot, H., Simpson, T. W., Stone, R. B., and Bohm, 

M., 2006, “Product Family Design Knowledge Representation, 

Aggregation, Reuse, and Analysis,” Artificial Intelligence for 
 

 

 

 

 

 

Engineering Design, Analysis and Manufacturing (AIEDAM), 

Special Issue on Computational Linguistics for Design, 

Maintenance and Manufacturing, accepted for publication. 

20. Nanda, J., Simpson, T. W., Shooter, S. B., and Stone, R. B., 2005, 

“Multi-modal representation of Product Family information using 

Web Ontology Language,” ASME Design Engineering Technical 

Conferences, Long Beach, CA, USA, ASME, DETC2005/DAC84869. 

21. R. Houe, B. Grabot, Knowledge modeling for Eco-design, accepted 

in International Journal of Concurrent Engineering: Research and 

Applications, août 2006. 

22. R. Houe, B. Grabot, A Decision Support System For Recyclability 

Assessment: From Norms To Constraints, INCOM 06, Saint 

Etienne, May 17-19 2006. 

23. R. Houe, B. Grabot, P. Zarate, Un modèle de représentation de 

connaissances en vue de l'évaluation de la recyclabilité, SIMO 06, 

Toulouse, 11-12 Octobre 2006. 

24. V. Rajan. A Perspective on the Interactions between Product 

Development and Value Chain Functions, ValueCHAiNGE White 

Paper, 2005. 

25. V. Rajan. Product Lifecycle and the Supply Chain, NIST Internal 

Report, In Preparation, 2007. 

26. Armetta, F., Hassas, S., Pimont S. and Lefevre, O. Towards the 

control of emergence by the coordination of decentralized agent 

activity for the resource sharing problem (invited paper). in 

Engineering Self-Organising Systems, 4th Int. Workshop, ESOA 

2006, Hakodate, Japan, May 2006, Selected Papers, Brueckner, S., 

et al. ed. Springer Verlag, LNCS/LNAI Vol.4335. 

27. S Hassas. Engineering Complex Adaptive Systems using Situated 

MAS: Some Selected Works and Contributions (Invited 

contribution). in. 6th Int. Workshop on Engineering Societies in the 

Agents' World (ESAW 2005) – oct. 2005 – A. Kusadasi et al. ed., 

LNAI Vol. 3963, Springer Verlag. 

28. Armetta, F., Hassas, S., Pimont, S., Gonon E. Managing dynamic 

flow in production chains through self-organization. In. Brueckner, 

S. et al. ed: Engineering Self-organizing Systems: Methodologies 

and Applications. Vol. 3464 of LNAI, Springer-Verlag, 2005. 

(Selected papers post-proceeding of ESOA'04). 

29. Lubell, J., Rachuri, S., Subrahmanian, E., Regli, W., Long Term 

Knowledge Retention Workshop Summary, NISTIR 7386, (2006) 

 

 

 

 

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 ICT for SCM & PLM: A Research Agenda for French-US collaboration 

 

 

 

 

47 

30. Rachuri, S., Subrahmanian, E., A., Bouras, S. J. Fenves, S. Foufou, 

R. D. Sriram, The Role of Standards in Product Lifecycle 

Management Support, In PLM’06 Int. Conf. on PLM, pp. 122-136, 

Bangalore 2006.

31. Rachuri, S., FouFou, S., Kemmerer, S., “Analysis of Standards for 

Lifecycle Management of Systems for US Army - a preliminary 

investigation,” NISTIR 7339, 2006. 

32. Rachuri, S., Baysal, M.M., Roy, U., Foufou, S., Bock, C, Fenves, 

S., Subrahmanian, E., Lyons, K., Sriram, R.D., Information Models 

for Product Representation: Core and Assembly Models, 

International Journal of Product Development, 2005. 

33. Subrahmanian, E., Rachuri, S., Fenves, S.J., Foufou, S., Sriram, 

R.D. “Product lifecycle management support: a challenge in 

supporting product design and manufacturing in a networked 

economy,” International Journal of Product Lifecycle Management 

(IJPLM), V1(1) – 2005 

34. Subrahmanian, E., Rachuri, S., Bouras, A., Fenves, J.F., S.J., 

Foufou, S., Sriram, R.D. “The role of Standards in Product 

Lifecycle Management Support,” NISTIR 7289, 2006. 

35. Bernard, A. Virtual engineering: methods and tools, Proc. Of the 

Institution of Mechanical Engineers, Part B- Journal of Engineering 

Manufacture- 219 (5): 413-421, 2005 

36. Houssin R, Bernard A, Martin P, Ris G, Cherrier F, Information 

system based on a working situation model for a new design 

approach in concurrent engineering, Journal of Engineering Design, 

17 (1): 35-54, 2006 

37. Du Preez N, Perry N, Candlot A, Bernard A, Uys W, Louw L 

Customized high-value document generation, CIRP Annals, 

Manufacturing Technology, 54 (1): 123-126, 2005 

38. Bernard A, Perry N, Fundamental concepts of 

product/technology/process informational integration for process 

modeling and process planning, IJ of Computer Integrated 

Manufacturing, 16 (7-8):557-565,2003. 

NOTES: