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An agent-based approach for integrating manufacturing operations

Author

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  • Anosike, A.I.
  • Zhang, D.Z.

Abstract

To remain competitive in today's global market, manufacturing organisations must be able to respond to unpredictable changes that occur in the market rapidly and cost-effectively. To facilitate such responsiveness, this paper presents an agent-based approach that would enable manufacturers to achieve optimised utilisation of resources within their existing manufacturing systems' structures and constraints while simultaneously considering systems' reconfiguration and restructure options to accommodate changing demand distributions and product mix. The approach is based on an integrated decision platform on which planning and control decisions can be considered concurrently with system reconfiguration/restructure decisions.

Suggested Citation

  • Anosike, A.I. & Zhang, D.Z., 2009. "An agent-based approach for integrating manufacturing operations," International Journal of Production Economics, Elsevier, vol. 121(2), pages 333-352, October.
    • Handle: RePEc:eee:proeco:v:121:y:2009:i:2:p:333-352
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    References listed on IDEAS

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    1. Reaidy, Jihad & Massotte, Pierre & Diep, Daniel, 2006. "Comparison of negotiation protocols in dynamic agent-based manufacturing systems," International Journal of Production Economics, Elsevier, vol. 99(1-2), pages 117-130, February.
    2. Anussornnitisarn, Pornthep & Nof, Shimon Y. & Etzion, Opher, 2005. "Decentralized control of cooperative and autonomous agents for solving the distributed resource allocation problem," International Journal of Production Economics, Elsevier, vol. 98(2), pages 114-128, November.
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    Cited by:

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    2. Zhang, David Z., 2011. "Towards theory building in agile manufacturing strategies--Case studies of an agility taxonomy," International Journal of Production Economics, Elsevier, vol. 131(1), pages 303-312, May.
    3. Chong, You Quan & Wang, Bin & Yue Tan, Gladys Li & Cheong, Siew Ann, 2014. "Diversified firms on dynamical supply chain cope with financial crisis better," International Journal of Production Economics, Elsevier, vol. 150(C), pages 239-245.
    4. Böhnlein, Dominik & Schweiger, Katharina & Tuma, Axel, 2011. "Multi-agent-based transport planning in the newspaper industry," International Journal of Production Economics, Elsevier, vol. 131(1), pages 146-157, May.
    5. Kucukkoc, Ibrahim & Zhang, David Z., 2014. "Mathematical model and agent based solution approach for the simultaneous balancing and sequencing of mixed-model parallel two-sided assembly lines," International Journal of Production Economics, Elsevier, vol. 158(C), pages 314-333.
    6. Li, Xinyu & Shao, Xinyu & Gao, Liang & Qian, Weirong, 2010. "An effective hybrid algorithm for integrated process planning and scheduling," International Journal of Production Economics, Elsevier, vol. 126(2), pages 289-298, August.
    7. Moncayo-Martínez, Luis A. & Zhang, David Z., 2011. "Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design," International Journal of Production Economics, Elsevier, vol. 131(1), pages 407-420, May.
    8. Mizgier, Kamil J. & Wagner, Stephan M. & Holyst, Janusz A., 2012. "Modeling defaults of companies in multi-stage supply chain networks," International Journal of Production Economics, Elsevier, vol. 135(1), pages 14-23.

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