IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v56y2018i23p7160-7178.html
   My bibliography  Save this article

Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions

Author

Listed:
  • Chaoqun Duan
  • Chao Deng
  • Abolfazl Gharaei
  • Jun Wu
  • Bingran Wang

Abstract

Many systems are required to perform a series of missions with finite breaks between any two consecutive missions. To improve the probability of system successfully completing the next mission, maintenance action is carried out on components during the breaks. In this work, a selective maintenance model with stochastic maintenance quality for multi-component systems is investigated. At each scheduled break, a set of maintenance actions with different degrees of impact are available for each component. The impact of a maintenance action is assumed to be random and follow an identified probability distribution. The corresponding maintenance cost and time are modelled based on the expected impact of the maintenance action. The objective of selective maintenance scheduling is to find the cost-optimal maintenance action for each component at every scheduled break subject to reliability and duration constraints. A simulated annealing algorithm is used to solve the complicated optimisation problem where both multiple maintenance actions and stochastic quality model are taken into account. Two illustrative numerical examples and a real case study have been solved to demonstrate the performance of the proposed approach. A comparison with deterministic maintenance shows the importance of considering the proposed stochastic quality in selective maintenance scheduling.

Suggested Citation

  • Chaoqun Duan & Chao Deng & Abolfazl Gharaei & Jun Wu & Bingran Wang, 2018. "Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions," International Journal of Production Research, Taylor & Francis Journals, vol. 56(23), pages 7160-7178, December.
  • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:23:p:7160-7178
    DOI: 10.1080/00207543.2018.1436789
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2018.1436789
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2018.1436789?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:56:y:2018:i:23:p:7160-7178. 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.