Advertisement

Knowledge Management for Consumer-Focused Product Design

  • Charu Chandra
  • Ali K. Kamrani

Abstract

As firms adopt a consumer focus for mass customizable product development strategy, it becomes essential for them to conduct early product design and development trade-off analysis among competing objectives of increased product variety, shorter product lifecycles, and smaller lot sizes. A distributed Knowledge Base System is needed for these complex decisions. This chapter proposes a knowledge management approach based on consumer-focused product design philosophy. It integrates capabilities for (a) intelligent information support, and (b) group decision-making, utilizing a common enterprise network model and knowledge interface through shared ontologies.

Keywords

Mass customizable product development knowledge management ontology based supply chain modeling 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bartalanffy, L. V. Perspectives on General system Theory. New York: George Braziller, 1975.Google Scholar
  2. 2.
    Curtis, B., Kellner M. I., and Over J. Process modeling. Communications of the ACM 1992, 35/9: 75–90.CrossRefGoogle Scholar
  3. 3.
    Chandra, C., Enterprise architectural framework for supply-chain integration. Proceedings: 6th Annual Industrial Engineering Research Conference; 1997 May 17–18: pp.873–878, Miami Beach, Florida, Institute of Industrial Engineers, Norcross, Georgia.Google Scholar
  4. 4.
    Chandra, C., Smirnov, A. V., and Chilov, N., Business Process Reengineering of Supply Chain Networks through Simulation Modeling & Analysis. Proceedings: Second International Conference on Simulation, Gaming, Training and Business Process Reengineering in Operations; 2000 September 8–9, Riga, Latvia.Google Scholar
  5. 5.
    Da Silveira, G., Borenstein, D., Fogliatto, F. Mass customization: Literature review and research directions. International Journal of Production Economics 2001; 72/1: 1–13.CrossRefGoogle Scholar
  6. 6.
    Foundation for Intelligent Physical Agents. FIPA 98 Specification, 1998. Part 12 — Ontology Service. http://www. fipa.org.Google Scholar
  7. 7.
    Fikes, R. and Farquhar A., Distributed repositories of highly expressive reusable ontologies. IEEE Intelligent Systems & Their Applications 1999; 14/2, Mar–Apr: 73–79.CrossRefGoogle Scholar
  8. 8.
    Fischer, K., Müller, J. P., Heimig, H., and Scheer, A.-W., Intelligent Agents in Virtual Enterprises. Proceedings: First International Conference and Exhibition on the Practical Application of Intelligent Agents and Multi-Agent Technology; 1996: 205–223; The Westminister Central Hall, London, UK.Google Scholar
  9. 9.
    Fox M. and Gruninger M., Ontologies for Enterprise Integration. Department of Industrial Engineering, University of Ontario, 1999.Google Scholar
  10. 10.
    Gasser, L. Social conceptions of knowledge and action: DAI foundations and open systems semantics. Artificial Intelligence 1991; 47: 107–138.MathSciNetCrossRefGoogle Scholar
  11. 11.
    Gruber, T. Toward principles for the Design of Ontologies Used for Knowledge Sharing. International Journal of Human and Computer Studies 1995; 43/5(6): 907–928.CrossRefGoogle Scholar
  12. 12.
    Gruninger, M. Integrated Ontologies for Enterprise Modelling. Enterprise Engineering and Integration. Building International Consensus; 1997, 368–377; K. Kosanke and J. Nell, Springer.Google Scholar
  13. 13.
    Hirsch, B., Information System Concept for the Management of Distributed Production. Computers in Industry 1995; 26:229–241.CrossRefGoogle Scholar
  14. 15.
    Jennings, N. R., On agent-based software engineering. Artificial Intelligence 2000; 117/2: 277–296.CrossRefGoogle Scholar
  15. 16.
    Jennings, R., Cooperation in Industrial Multi-agent Systems. World Scientific Series in Computer Science 1994; 43, World Scientific Publishing Co. Inc.Google Scholar
  16. 17.
    Jennings, N., Faratin, P., Johnson, M., Brien, P., Wiegand, M. Using Intelligent Agents to Manage Business Processes. Proceedings of the International Conference “The Practical Application of Intelligents and Multi-Agent Technology; 1996, 345–360; London.Google Scholar
  17. 18.
    Johannesson, P. and Perjons, E. Design principles for process modeling in enterprise application integration. Information Systems 2001; 26: 165–184.CrossRefzbMATHGoogle Scholar
  18. 19.
    Lambert, D. M. Cooper, M. C. Issues in supply chain management. Industrial Marketing Management 2000; 29: 65–83.CrossRefGoogle Scholar
  19. 20.
    Landauer, C. Process modeling in conceptual categories. Proceedings: 33rd Hawaii International Conference on System Sciences; 2000.Google Scholar
  20. 21.
    Lee, H. L., and Billington, C. Material management in decentralized supply chains. Operations Research 1993; 41/5: 835–847.CrossRefGoogle Scholar
  21. 22.
    Lesser, V. R. Cooperative Multiagent systems: A personal View of the State of the Art. IEEE Transactions on Knowledge and Data Engineering 1999; 11/1: 133–142.CrossRefGoogle Scholar
  22. 23.
    Manufacturing Enterprise Integration Program (MEIP). National Institute of Standards and Technology (NIST). Gaithersburg, Maryland. http://www.atp.nist.gov/, 1999.Google Scholar
  23. 24.
    MESA International White Paper # 6. MES Explained: A High Level Vision. http://www. mesa.org, 1 998.Google Scholar
  24. 25.
    Martin, I. and Cheung, Y. SAP and business process re-engineering. Business Process Management Journal 2000; 6/2: 113–121.CrossRefGoogle Scholar
  25. 26.
    McCarthy, I. Manufacturing classification. Integrated Manufacturing Systems 1995; 6/6: 37–48.CrossRefGoogle Scholar
  26. 27.
    McCarthy I. Ridgway K. Cladistics: a Taxonomy for manufacturing organizations. Integrated Manufacturing Systems 2000; 11/1, 16–29: 16–29.CrossRefGoogle Scholar
  27. 28.
    McKelvey, B. Organizational Systematics Taxonomy, Evaluation, classification. Berkeley: University of California Press, 1982.Google Scholar
  28. 29.
    National Industrial Information Infrastructure Protocol (NIIIP). www.niiip.org. 1994.Google Scholar
  29. 30.
    Rubenstein-Montano B., Leibovitz J., Buchwalter D., McCaw B., Newman K., Rebeck K. A System thinking framework for Knowledge management. Decision Support Systems 2001; 31: 5–16.CrossRefGoogle Scholar
  30. 31.
    Sandholm, T. Agents in Electronic Commerce: Component Technologies for Automated Negotiation and Coalition Formation. Proceedings: International Conference on Multi Agent Systems; 1998 10–11, Paris, France.Google Scholar
  31. 32.
    Smirnov, A. DESO: GDSS for Virtual Enterprise Configuration Management. Proceedings: 5th International Conference on Concurrent Enterprising ICE’99; 1999; The Hague, The Netherlands.Google Scholar
  32. 33.
    Smimov, A. V. Conceptual Design for Manufacture in Concurrent Engineering. Proceedings: Conference on Concurrent Engineering: Research and Applications; 1994, 461–466; Pittsburgh, Pennsylvania.Google Scholar
  33. 34.
    Smirnov, A. V. Chandra, C. Ontology-based Knowledge Management for Co-operative Supply Chain Configuration. Proceedings: 2000 AAAI Spring Symposium “Bringing knowledge to business Processes”; 2000; March 20–22: 85–92; Stanford, California, AAAI Press.Google Scholar
  34. 35.
    Sousa, P., Heikkila, T., Kollingbaum, M., and Valckenaers, P. Aspects of co-operation in Distributed Manufacturing Systems. Proceedings: Second International Workshop on Intelligent Manufacturing Systems; 1999, September: 685–717; Leuven, Belgium.Google Scholar
  35. 36.
    Uschold, M. Gruninger M. ONTOLOGIES: Principles, Methods and Applications. Knowledge Engineering Review 1996; 11/2.Google Scholar
  36. 37.
    Van Hoek, R. I. The rediscovery of postponement a literature review and directions for research. Journal of Operations Management 2001; 19: 161–184.CrossRefGoogle Scholar
  37. 38.
    Vasconcelos J., Kimble C., Gouveria, R. F. A Design for a group Memory System using Ontologies. UKAIS, University of Wales Institute, Cardiff, 2000.Google Scholar
  38. 39.
    Work Flow Management (WFM) (1996). www. wfmc.orgGoogle Scholar
  39. 40.
    Wooldridge, M. Jennings, N. R. Intelligent Agents —Theories, Architectures, and Languages. Lecture Notes in Artificial Intelligence, Springer-Verlag, 1995.Google Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Charu Chandra
    • 1
  • Ali K. Kamrani
    • 2
  1. 1.University of Michigan-DearbornUSA
  2. 2.University of HoustonUSA

Personalised recommendations