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

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  • Weng, Wei
  • Fujimura, Shigeru

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.

Suggested Citation

  • Weng, Wei & Fujimura, Shigeru, 2012. "Control methods for dynamic time-based manufacturing under customized product lead times," European Journal of Operational Research, Elsevier, vol. 218(1), pages 86-96.
    • Handle: RePEc:eee:ejores:v:218:y:2012:i:1:p:86-96
    DOI: 10.1016/j.ejor.2011.10.014
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    References listed on IDEAS

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    2. Sagawa, Juliana Keiko & Nagano, Marcelo Seido, 2015. "Modeling the dynamics of a multi-product manufacturing system: A real case application," European Journal of Operational Research, Elsevier, vol. 244(2), pages 624-636.

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