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An agent-based approach to concurrent cable harness design

Published online by Cambridge University Press:  27 February 2009

Hisup Park ,
Mark R. Cutkosky ,
Andrew B. Conru  and
Soo-Hong Lee
Hisup Park
Affiliation:
Lockheed Missiles and Space Company, Advanced Technology Group, O/86–60 B/153, Sunnyvale, CA94089–3504
Mark R. Cutkosky
Affiliation:
Center for Design Research, Stanford University, Stanford, CA94305–4026
Andrew B. Conru
Affiliation:
Center for Design Research, Stanford University, Stanford, CA94305–4026
Soo-Hong Lee
Affiliation:
Center for Design Research, Stanford University, Stanford, CA94305–4026
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Abstract

An approach to providing computational support for concurrent design is discussed in the context of an industrial cable harness design problem. Key issues include the development of an architecture that supports collaboration among specialists, the development of hierarchical representations that capture different characteristics of the design, and the decomposition of tasks to achieve a trade-off between efficiency and robustness. An architecture is presented in which the main design tasks are supported by agents – asynchronous and semiautonomous modules that automate routine design tasks and provide specialized interfaces for working on particular aspects of the design. The agent communication and coordination mechanisms permit members of an engineering team to work concurrently, at different levels of detail and on different versions of the design. The design is represented hierarchically, with detailed models maintained by the participating agents. Abstractions of the detailed models, called “agent model images,” are shared with other agents. In conjunction with the architecture and design representations, issues pertaining to the exchange of information among different views of the design, management of dependencies and constraints, and propagation of design changes are discussed.

Keywords

agentscable harness designconcurrent engineeringconfiguration designfeatures
Type
Research Article
Information
AI EDAM , Volume 8 , Issue 1 , Winter 1994 , pp. 45 - 61
Copyright
Copyright © Cambridge University Press 1994

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References

REFERENCES

Bond, A.H., & Ricci, R.J. (1991). Collaboration in aircraft design. In Computer-Aided Cooperative Product Development (Sriram, D., & Logcher, R., Eds.), pp. 152–182. Springer-Verlag, New York.CrossRefGoogle Scholar
Collet, C., Huhns, M.N., & Shen, W.-M. (1991). Resource integration using a large knowledge base in Carnot. IEEE Computer (December), 55–62.CrossRefGoogle Scholar
Conru, A., & Cutkosky, M. (1993). Computational support for interactive cable harness routing and design. Technical Report 19930919. Center for Design Research, Stanford University, Stanford, CA.CrossRefGoogle Scholar
Cutkosky, M.R., & Tenenbaum, J.M. (1990). A methodology and computational framework for concurrent product and process design. Mechanism and Machine Theory 25(3), 365–381.CrossRefGoogle Scholar
Cutkosky, M.R., & Tenenbaum, J.M. (1991). Providing computational support for concurrent engineering. Int. J. Sys. Automat. Res. Appl. 1(3), 239–261.Google Scholar
Cutkosky, M.R., Brown, D., & Tenenbaum, J.M. (1992). Working with multiple representations in a concurrent design system. ASME J. Mech. Des. 114(3), 515–524.CrossRefGoogle Scholar
Cutkosky, M., Engelmore, R., Fikes, R., Gruber, T., Genesereth, M., & Mark, W. (1993). PACT: An experiment in integrating concurrent engineering systems. IEEE Computer 26(1), 28–37.CrossRefGoogle Scholar
Eppinger, S.D., Whitney, D.E., Smith, R.P., & Gebala, D.A. (1991). Organizing the tasks in complex design projects. In Computer-Aided Cooperative Product Development. (Sriram, D., & Logcher, R., Eds.), pp. 229–252. Springer-Verlag, New York.CrossRefGoogle Scholar
Genesereth, M. (1989). A comparative analysis of some simple architectures for autonomous agents. Technical Report Logic-89–2. Logic Group, Computer Science Dept., Stanford University, Stanford, CA.Google Scholar
Glicksman, J., Hitson, B.L., Pan, J.Y.-C., & Tenenbaum, J.M. (1991). MKS: A conceptually centralized knowledge service for distributed CIM environment. J. Intell. Manuf. 2(1), 27–42.CrossRefGoogle Scholar
Gruber, T.R., Tenenbaum, J.M., & Weber, J.C. (1992). Toward a knowledge medium for collaborative product development. In Artificial Intelligence in Design (Gero, J.S., Ed.), pp. 413–432. Kluwer Academic Publishers, Pittsburgh.Google Scholar
Hayes-Roth, B. (1985). A blackboard architecture for control. Art. Intell. 26, 251–321.CrossRefGoogle Scholar
Kaiser, G.E., Feiler, P.H., & Popovich, S.S. (1988). Intelligent assistance for software development and maintenance. IEEE Software 5, 40–49.CrossRefGoogle Scholar
Krishnan, V., Eppinger, S.D., & Whitney, D.E. (1992). Ordering crossfunctional decision making in product development. Technical Report WP 3299–91 MS. Massachusetts Institute of Technology, Cambridge.Google Scholar
Latombe, J.C. (1991). Robot Motion Planning. Kluwer Academic Publishers, Boston, MA.CrossRefGoogle Scholar
Lu, S.C.-Y. (1992). Knowledge processing tools for concurrent engineering tasks. Proc. 2nd Int. Conf. Automation Technol., 37–46.Google Scholar
Nii, H.P. (1986 a). Blackboard systems: Blackboard application systems, blackboard systems from a knowledge engineering perspective. AI Magazine (Summer), 82–106.Google Scholar
Nii, H.P. (1986 b). Blackboard systems: The blackboard model of problem solving and the evolution of blackboard architectures. AI Magazine (Summer), 38–53.Google Scholar
Pan, J.Y.-C., Tenenbaum, J.M., & Glicksman, J. (1989). A framework for knowledge-based computer-integrated manufacturing. IEEE Trans. Semiconductor Manuf. 2(2), 33–46.CrossRefGoogle Scholar
Park, H., Lee, S.-H., & Cutkosky, M.R. (1992). Paper given at conference. Computational Support for Concurrent Engineering of Cable Harnesses. Computers in Engineering, San Francisco, August, ASME, 261–268.Google Scholar
Petrie, C. (1992). Constrained decision revision. Proc. 10th Nat. Conf. Artificial Intell. (AAAI-92), 393–400.Google Scholar
Sriram, D., Logcher, R., Wong, A., & Ahmed, S. (1991). An objectoriented framework for collective engineering design. In Computer-Aided Cooperative Product Development (Sriram, D., & Logcher, R., Eds.), pp. 51–92. Springer-Verlag, New York.CrossRefGoogle Scholar
Sriram, R., Livezey, B.K., & Perkins, W.A. (1992). A Distributed Shared Database for Concurrent Engineering. CE & CALS Conference, Washington, DC, 27–43.Google Scholar
Steward, D.V. (1981). The design structure system: A method for managing the design of complex systems. IEEE Trans. Eng. Mgmt. EM-28, 71–74.CrossRefGoogle Scholar
Sturges, R.H. (1992). A computational model for conceptual design based on function logic. In Artificial Intelligence in Design (Gero, J.S., Ed.), pp. 757–772. Kluwer Academic Publishers, Pittsburgh.Google Scholar
Sycara, K.P. (1991). Cooperative negotiation in concurrent engineering design. In Computer-Aided Cooperative Product Development (Sriram, D., & Logcher, R., Eds.), pp. 269–297. Springer-Verlag, New York.CrossRefGoogle Scholar
Talukdar, S., Ramesh, V.C., Quadrel, R., & Christie, R. (1992). Multiagent organizations for real-time operations. Proceedings of the IEEE 80(5), 765–778.CrossRefGoogle Scholar
Tichy, W.F. (1985). RCS – A system for version control. Software – Practice & Experience 15(7), 637–654.CrossRefGoogle Scholar
Welch, R.V., & Dixon, J.R. (1989). Extending the Iterative Redesign Model to Configuration Design: Sheet Metal Brackets as an Example. Design Theory and Methodology - DTM 1989, Montreal, Quebec, Canada, ASME, 81–88.CrossRefGoogle Scholar
Werkman, K.J. (1992). Multiple agent cooperative design evaluation using negotiation. In Artificial Intelligence in Design (Gero, J.S., Ed.), pp. 161–180. Kluwer Academic Publishers, Pittsburgh.Google Scholar