IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v45y2013i6p617-629.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2012.728729
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0740817X.2012.728729?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:45:y:2013:i:6:p:617-629. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.