Simulation Modeling Using Agents For Mass Customization

  • Manfredi Bruccoleri


Reconfigurable enterprises and production networks — virtual structures of manufacturing enterprises that coalesce and vanish in response to a dynamic marketplace — are one of the main enabler paradigm for mass customizable production. The design and coordination of production networks to changing market dynamics are challenging tasks. Simulation provides the ability to develop prototypes of such complex systems cost effectively and in shorter duration. This Chapter describes how simulation can be utilized in conjunction with multi agent system techniques to develop realistic prototypes of complex decision support systems for the design of coordination strategies in large-scale mass customization production systems.


Multi agent systems production networks simulation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ahn, H.J., Lee, H., Park, S.J. A flexible agent system for change adaptation in supply chains. Expert Systems with Applications 2003; 25: 603–618.CrossRefGoogle Scholar
  2. 2.
    Belz, R., Mertens, P. Combining knowledge-based systems and simulation to solve rescheduling problems. Decision Support Systems 1996; 17: 141–157.CrossRefGoogle Scholar
  3. 3.
    Brandolese,., Brun, A., Portioli-Staudacher, A. A Multi-Agent Approach for the Capacity Allocation Problem. International Journal of Production Economics 2000; 66: 269–285.CrossRefGoogle Scholar
  4. 4.
    Bruccoleri, M., Amico, M., And Perrone, G. Distributed intelligent control of exceptions in reconfigurable manufacturing systems. International Journal of Production Research 2003; 41/2: 1393–1412.CrossRefGoogle Scholar
  5. 5.
    Bruccoleri, M., Pasek, Z. Operational Issues i n Reconfigurable Manufacturing Systems: Exception Handling. Proceedings of the 5th biannual World Automation Congress 2002; 3; June 9–13; Orlando Florida.Google Scholar
  6. 6.
    Cantamessa, M., Fichera, S., Grieco, A., La Commare, D., Perrone, G., Tolio, T. Process and production planning in manufacturing enterprise networks. Proceedings of the 1st CIRP Conference on Digital Enterprise Technology 2002;: 187–190, Durham.Google Scholar
  7. 7.
    Ferber, J. Multi-Agent Systems. An Introduction t o Distributed Artificial Intelligence. Addison-Wesley, 1999.Google Scholar
  8. 8.
    Fox, M. S., Barbuceanu, M., Teigen, R. Agent-Oriented Supply Chain Management. The International Journal of Flexible Manufacturing Systems 2000; 12: 165–188CrossRefGoogle Scholar
  9. 9.
    Fuji, S., Kaihara, T., Morita, M. A distributed virtual factory i n agile manufacturing environment. International Journal of Production Research 2000; 381/17: 4113–4128.CrossRefGoogle Scholar
  10. 10.
    Goldhar, J., Jelinek, M. Plans for economics of scope. Harvard Business Review 1983; 61/6: 141–148.Google Scholar
  11. 11.
    Heng, L., Li Z., Li L. X., Bin H. A production rescheduling expert simulation system. European Journal of Operational Research 2000; 124: 283–293.CrossRefzbMATHGoogle Scholar
  12. 12.
    Katzy, B. R., Dissel, M. A toolset for building the virtual enterprise. Journal of Intelligent Manufacturing 2001; 12: 121–131.CrossRefGoogle Scholar
  13. 13.
    Kelton, W. D., Sadowsky, R. P., Sadowsky, D. A. Simulation with Arena®. New York: Avenue of Americas, Mc Graw Hill 1998.Google Scholar
  14. 14.
    Koren, Y., Heisel, V., Jovane, F., Moriwaki, T., Pritschow, G., Ulsoy, G., Van Brussel, H. Reconfigurable Manufacturing Systems. Annals of CIRP (Keynote Paper) 1999; 48/2.Google Scholar
  15. 15.
    Lo Nigro, G., Noto La Diega, S., Perrone, G., Renna, P. Coordination policies to support decision making in virtual organization. Proceedings of the International Manufacturing Leaders Forum; 2002; Adelaide Australia, 166–173.Google Scholar
  16. 16.
    Martinez, M. T., Fouletier, P., Park, K. H., Favrel, J. Virtual enterprise — organization, evolution and control. International Journal of Production Economics 2001: 74: 225–238.CrossRefGoogle Scholar
  17. 17.
    Pine, B. J., Victor, B., Boyton, A.C., 1993. Making mass customization work, Harvard Business Review 71, 108–119.Google Scholar
  18. 18.
    Renna, P., Perrone, G., Amico, M., Bruccoleri, M, Noto La Diega, S., 2001, A performance comparison between market like and efficiency based approaches in Agent Based Manufacturing environment. Proceedings of the 34th CIRP International Seminar on Manufacturing Systems; 2001 May: 93–98; Athens.Google Scholar
  19. 19.
    Shen, W., Norrie D., H. Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey. Knowledge and Information System, an International Journal 1999; 1/2: 129-156.Google Scholar
  20. 20.
    Smith, R. G. The contract net protocol: high level communication and control in a distributed problem solver. IEEE Transactions On Computers 1980: 12: 1104–1113.CrossRefGoogle Scholar
  21. 21.
    Swaminathan, J. M., Smith S. F., Sadeh, N. M. Modeling Supply Chain Dynamics: A Multiagent Approach. Decision Sciences 1998; 29/3: 607–632.CrossRefGoogle Scholar
  22. 22.
    Turowski, K., 2002, Agent-based e-commerce in case of mass customization, International Journal of Production Economics, 75, 69–81.CrossRefGoogle Scholar
  23. 23.
    U.S. National Research Council, 1998, Visionary Manufacturing Challenges for 2020, National Academy Press, Washington, Dc, U.S.A.Google Scholar
  24. 24.
    Virtual Manufacturing Technical Workshop — Dayton, Ohio 25-26 October 1994, Technical Report — March 07, 2001.Google Scholar
  25. 25.
    Wiendhal, H. P., Lutz, S. Production i n Networks. Annals of CIRP 2002; 51/2.Google Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Manfredi Bruccoleri
    • 1
  1. 1.University of PalermoItaly

Personalised recommendations