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Delayed reconfigurable manufacturing system

Author

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  • Sihan Huang
  • Guoxin Wang
  • Yan Yan

Abstract

Reconfigurable manufacturing systems (RMS) is a new manufacturing paradigm aiming at providing exactly functionality and capacity needed and exactly when needed. Reconfiguration is the main method to achieve this goal. But, the reconfiguration is an interruption to production activities causing production loss and system ramp-up problem and the ‘exact functionality’ may increase the reconfiguration efforts and aggravate the production loss and the ramp-up time. Therefore, a special RMS – delayed reconfigurable manufacturing system (D-RMS) is proposed to promote the practicality of RMS. Starting from the RMS built around part family with the characteristic of delayed differentiation, whose reconfiguration activities mainly occur in the latter stages of manufacturing system and the former stages have the potential to maintain partial production activities to reduce production loss during reconfiguration. Inspired from this, the basic structure of RMS is divided into two subsystems, subsystem 1 is capable of maintain partial production with a certain more functionality than needed, subsystem 2 reconfigure to provide exactly functionality and capacity of a specific part exactly when needed. And then, the benefits of D-RMS are analysed from inventory and ramp-up time aspects. Finally, a case study is presented to show the implementation process of D-RMS and validates the practicability of D-RMS.

Suggested Citation

  • Sihan Huang & Guoxin Wang & Yan Yan, 2019. "Delayed reconfigurable manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2372-2391, April.
  • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2372-2391
    DOI: 10.1080/00207543.2018.1518605
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    File URL: http://hdl.handle.net/10.1080/00207543.2018.1518605
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    Cited by:

    1. Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
    2. Sihan Huang & Guoxin Wang & Shiqi Nie & Bin Wang & Yan Yan, 2023. "Part family formation method for delayed reconfigurable manufacturing system based on machine learning," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2849-2863, August.
    3. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).

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