IDEAS home Printed from https://ideas.repec.org/a/ids/ijmtma/v18y2009i1p1-14.html
   My bibliography  Save this article

A performance-based Bayesian method for the optimisation of manufacturing resources collaboration

Author

Listed:
  • Jian Zhou
  • Qing Li
  • Qing Wang
  • Dafeng Xu
  • Tianyuan Xiao

Abstract

In this paper, a performance-based Bayesian method, namely a method based on the research of probabilistic relationship between performance influence factors, is put forward and is used to optimise manufacturing resources collaboration. Firstly, a method for probability dependency relationship modelling between the performance values of different manufacturing resource nodes is proposed. Secondly, an extended general method and its application approach are discussed correspondingly. At last, a simulation model based upon system dynamics for the proposed method is established and its validity for the effectiveness and efficiency of the manufacturing resources collaboration has been tested by a case study.

Suggested Citation

  • Jian Zhou & Qing Li & Qing Wang & Dafeng Xu & Tianyuan Xiao, 2009. "A performance-based Bayesian method for the optimisation of manufacturing resources collaboration," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 18(1), pages 1-14.
    • Handle: RePEc:ids:ijmtma:v:18:y:2009:i:1:p:1-14
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=24617
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijmtma:v:18:y:2009:i:1:p:1-14. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=21 .

    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.