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How heterogeneity influences condition-based maintenance for gamma degradation process

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  • Linmiao Zhang
  • Yong Lei
  • Houcai Shen

Abstract

In many applications, units from the same population exhibit heterogeneity that they degrade with different rates due to random factors. This article studies how this heterogeneity in degradation influences condition-based maintenance (CBM) policy. Many CBM polices are developed based on gamma process because it is popularly used to characterise monotone degradation processes. In this study, we also model the unit’s degradation by gamma process. To account for the heterogeneity among units’ degradation, we incorporate a random effect parameter in the gamma process. Then the optimal policy for CBM is obtained through Markov decision process. We show that when heterogeneity exists, the transition probability of degradation state depends on both unit’s age and observed degradation level. And consequently, the optimal maintenance policy is a monotone control limit policy. We conduct extensive numerical experiments to validate and demonstrate our findings in depth.

Suggested Citation

  • Linmiao Zhang & Yong Lei & Houcai Shen, 2016. "How heterogeneity influences condition-based maintenance for gamma degradation process," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5829-5841, October.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:19:p:5829-5841
    DOI: 10.1080/00207543.2016.1181282
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    References listed on IDEAS

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    1. Wang, Hongzhou, 2002. "A survey of maintenance policies of deteriorating systems," European Journal of Operational Research, Elsevier, vol. 139(3), pages 469-489, June.
    2. Haitao Liao & Zhigang Tian, 2013. "A framework for predicting the remaining useful life of a single unit under time-varying operating conditions," IISE Transactions, Taylor & Francis Journals, vol. 45(9), pages 964-980.
    3. Alaa H. Elwany & Nagi Z. Gebraeel & Lisa M. Maillart, 2011. "Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors," Operations Research, INFORMS, vol. 59(3), pages 684-695, June.
    4. Liao, Haitao & Elsayed, Elsayed A. & Chan, Ling-Yau, 2006. "Maintenance of continuously monitored degrading systems," European Journal of Operational Research, Elsevier, vol. 175(2), pages 821-835, December.
    5. Chen, Nan & Ye, Zhi-Sheng & Xiang, Yisha & Zhang, Linmiao, 2015. "Condition-based maintenance using the inverse Gaussian degradation model," European Journal of Operational Research, Elsevier, vol. 243(1), pages 190-199.
    6. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
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    Cited by:

    1. Mosayebi Omshi, E. & Shemehsavar, S. & Grall, A., 2024. "An intelligent maintenance policy for a latent degradation system," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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