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Bayesian enhanced decision making for deteriorating repairable systems with preventive maintenance

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  • Yeu‐Shiang Huang
  • Chi‐Chang Hung
  • Chih‐Chiang Fang

Abstract

Since a system and its components usually deteriorate with age, preventive maintenance (PM) is often performed to restore or keep the function of a system in a good state. Furthermore, PM is capable of improving the health condition of the system and thus prolongs its effective age. There has been a vast amount of research to find optimal PM policies for deteriorating repairable systems. However, such decisions involve numerous uncertainties and the analyses are typically difficult to perform because of the scarcity of data. It is therefore important to make use of all information in an efficient way. In this article, a Bayesian decision model is developed to determine the optimal number of PM actions for systems which are maintained according to a periodic PM policy. A non‐homogeneous Poisson process with a power law failure intensity is used to describe the deteriorating behavior of the repairable system. It is assumed that the status of the system after a PM is somewhere between as good as new for a perfect repair and as good as old for a minimal repair, and for failures between two preventive maintenances, the system undergoes minimal repairs. Finally, a numerical example is given and the results of the proposed approach are discussed after performing sensitivity analysis. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008

Suggested Citation

  • Yeu‐Shiang Huang & Chi‐Chang Hung & Chih‐Chiang Fang, 2008. "Bayesian enhanced decision making for deteriorating repairable systems with preventive maintenance," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(2), pages 105-115, March.
    • Handle: RePEc:wly:navres:v:55:y:2008:i:2:p:105-115
    DOI: 10.1002/nav.20268
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    References listed on IDEAS

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    1. Percy, David F., 2002. "Bayesian enhanced strategic decision making for reliability," European Journal of Operational Research, Elsevier, vol. 139(1), pages 133-145, May.
    2. Stadje, Wolfgang & Zuckerman, Dror, 1996. "A generalized maintenance model for stochastically deteriorating equipment," European Journal of Operational Research, Elsevier, vol. 89(2), pages 285-301, March.
    3. Savaş Dayanik & Ülkü Gürler, 2002. "An Adaptive Bayesian Replacement Policy with Minimal Repair," Operations Research, INFORMS, vol. 50(3), pages 552-558, June.
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    Cited by:

    1. Nader Ebrahimi & S.N.U.A. Kirmani & Ehsan S. Soofi, 2011. "Predictability of operational processes over finite horizon," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(6), pages 531-545, September.

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