IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v58y2020i13p4071-4085.html
   My bibliography  Save this article

Joint decision-making of production and maintenance in mixed model assembly systems with delayed differentiation configurations

Author

Listed:
  • Weihong Guo
  • Xi Gu

Abstract

Mixed model assembly systems (MMASs) can simultaneously manufacture multiple product variants and are developed to satisfy customers’ increasing desire for products with a high variety. This paper investigates the joint decision-making of production and maintenance policies in MMASs with delayed differentiation configurations, where common operations are performed before differentiated processes. The problem is formulated as a Markov Decision Process (MDP) problem that minimises the average cost per unit time. Monte Carlo simulation is used to evaluate the system performance measures (e.g. volume mix ratio, product quality) under the optimal policy. Numerical examples are presented to illustrate the structure of the optimal policy and the impact of different factors on the system performance in an MMAS that produces two types of product variants. Techniques that can potentially solve the problem in large-sized MMASs are also discussed.

Suggested Citation

  • Weihong Guo & Xi Gu, 2020. "Joint decision-making of production and maintenance in mixed model assembly systems with delayed differentiation configurations," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4071-4085, July.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:13:p:4071-4085
    DOI: 10.1080/00207543.2019.1641641
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2019.1641641
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2019.1641641?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.

    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:tprsxx:v:58:y:2020:i:13:p:4071-4085. 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/TPRS20 .

    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.