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Multimode variation modeling and process monitoring for serial-parallel multistage manufacturing processes

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  • Ran Jin
  • Kaibo Liu

Abstract

A Serial-Parallel Multistage Manufacturing Process (SP-MMP) may have multiple variation propagation modes in its production runs when process routes vary from part to part. Conventional methods that ignore such multimode variation may not be able to effectively model and monitor the variation streams. It is also very challenging to model such a process when the available engineering domain knowledge is insufficient to characterize the variation streams. This article proposes a data-driven method, piecewise linear regression trees, to interrelate the variables for an SP-MMP with multimode variation. A unified control chart system is developed to monitor the process considering modeling uncertainty. The application to a more generic multistage multimode process is discussed. Finally, the effectiveness of the proposed procedure is demonstrated in an application involving a wafer manufacturing process.

Suggested Citation

  • Ran Jin & Kaibo Liu, 2013. "Multimode variation modeling and process monitoring for serial-parallel multistage manufacturing processes," IISE Transactions, Taylor & Francis Journals, vol. 45(6), pages 617-629.
    • Handle: RePEc:taf:uiiexx:v:45:y:2013:i:6:p:617-629
    DOI: 10.1080/0740817X.2012.728729
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    Cited by:

    1. Chang-Ho Lee & Dong-Hee Lee & Young-Mok Bae & Seung-Hyun Choi & Ki-Hun Kim & Kwang-Jae Kim, 2022. "Approach to derive golden paths based on machine sequence patterns in multistage manufacturing process," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 167-183, January.
    2. Lu, Biao & Zhou, Xiaojun, 2017. "Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 116-127.

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