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Control methods for dynamic time-based manufacturing under customized product lead times

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  • Weng, Wei
  • Fujimura, Shigeru
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    Abstract

    For manufacturers, the integration of high performance manufacturing with customer-oriented practices plays an important role in improving the performance of their business system. The benefits from such integration can only be maximized when the two parts are designed to work cooperatively. Though previous research has contributed much to manufacturing control algorithms and customer service practices, there has been little consideration of the two parts as a whole; consequently, the methods proposed may not be well supported by the other practices adopted in the system. This study develops production control methods that support a customer-oriented lead time policy, and aims to increase the performance of both manufacturing and customer service. The control methods are proposed for hybrid flow shops handling orders arriving dynamically. Computer simulations are conducted on a large number of problem instances, and the results show that the designed distributed feedback and decision-making functions enable the proposed methods to significantly outperform existing methods in achieving just-in-time (JIT) job completion under customized product lead times. Even taking into account the possible tradeoff between JIT job completion and flow time length, the proposed methods still deliver competitive performance.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711009337
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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 218 (2012)
    Issue (Month): 1 ()
    Pages: 86-96

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    Handle: RePEc:eee:ejores:v:218:y:2012:i:1:p:86-96

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Time-based manufacturing; Hybrid flow shop; Dynamic scheduling; Customer order flexibility; Distributed control;

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    1. Moursli, O. & Pochet, Y., 2000. "A branch-and-bound algorithm for the hybrid flowshop," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 113-125, March.
    2. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    3. Kyparisis, George J. & Koulamas, Christos, 2006. "Flexible flow shop scheduling with uniform parallel machines," European Journal of Operational Research, Elsevier, vol. 168(3), pages 985-997, February.
    4. Mark L. Spearman & Rachel Q. Zhang, 1999. "Optimal Lead Time Policies," Management Science, INFORMS, vol. 45(2), pages 290-295, February.
    5. Kis, Tamas & Pesch, Erwin, 2005. "A review of exact solution methods for the non-preemptive multiprocessor flowshop problem," European Journal of Operational Research, Elsevier, vol. 164(3), pages 592-608, August.
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    7. Agnetis, A. & Pacifici, A. & Rossi, F. & Lucertini, M. & Nicoletti, S. & Nicolo, F. & Oriolo, G. & Pacciarelli, D. & Pesaro, E., 1997. "Scheduling of flexible flow lines in an automobile assembly plant," European Journal of Operational Research, Elsevier, vol. 97(2), pages 348-362, March.
    8. Allahverdi, Ali & Ng, C.T. & Cheng, T.C.E. & Kovalyov, Mikhail Y., 2008. "A survey of scheduling problems with setup times or costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 985-1032, June.
    9. Kurz, Mary E. & Askin, Ronald G., 2004. "Scheduling flexible flow lines with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 159(1), pages 66-82, November.
    10. Slater, Stanley F. & Narver, John C., 2000. "The Positive Effect of a Market Orientation on Business Profitability: A Balanced Replication," Journal of Business Research, Elsevier, vol. 48(1), pages 69-73, April.
    11. Nahm, Abraham Y. & Vonderembse, Mark A. & Subba Rao, S. & Ragu-Nathan, T.S., 2006. "Time-based manufacturing improves business performance--results from a survey," International Journal of Production Economics, Elsevier, vol. 101(2), pages 213-229, June.
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