IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i19p5829-5841.html
   My bibliography  Save this article

How heterogeneity influences condition-based maintenance for gamma degradation process

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1181282
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2016.1181282?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.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).
    2. Zuo, Jian & Steiner, Nadia Yousfi & Li, Zhongliang & Hissel, Daniel, 2024. "Health management review for fuel cells: Focus on action phase," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    2. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    3. 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.
    4. Mosayebi Omshi, E. & Grall, A. & Shemehsavar, S., 2020. "A dynamic auto-adaptive predictive maintenance policy for degradation with unknown parameters," European Journal of Operational Research, Elsevier, vol. 282(1), pages 81-92.
    5. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    6. Zhu, Qiushi & Peng, Hao & Timmermans, Bas & van Houtum, Geert-Jan, 2017. "A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs," International Journal of Production Economics, Elsevier, vol. 193(C), pages 365-380.
    7. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    9. Guo, Chiming & Wang, Wenbin & Guo, Bo & Si, Xiaosheng, 2013. "A maintenance optimization model for mission-oriented systems based on Wiener degradation," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 183-194.
    10. Yousefi, Nooshin & Coit, David W. & Song, Sanling, 2020. "Reliability analysis of systems considering clusters of dependent degrading components," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    11. Deep, Akash & Zhou, Shiyu & Veeramani, Dharmaraj & Chen, Yong, 2023. "Partially observable Markov decision process-based optimal maintenance planning with time-dependent observations," European Journal of Operational Research, Elsevier, vol. 311(2), pages 533-544.
    12. Wang, Xiaolin & Balakrishnan, Narayanaswamy & Guo, Bo, 2014. "Residual life estimation based on a generalized Wiener degradation process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 13-23.
    13. Ponchet, Amélie & Fouladirad, Mitra & Grall, Antoine, 2010. "Assessment of a maintenance model for a multi-deteriorating mode system," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1244-1254.
    14. Liu, Bin & Pandey, Mahesh D. & Wang, Xiaolin & Zhao, Xiujie, 2021. "A finite-horizon condition-based maintenance policy for a two-unit system with dependent degradation processes," European Journal of Operational Research, Elsevier, vol. 295(2), pages 705-717.
    15. Cai, Yue & Teunter, Ruud H. & de Jonge, Bram, 2023. "A data-driven approach for condition-based maintenance optimization," European Journal of Operational Research, Elsevier, vol. 311(2), pages 730-738.
    16. David T. Abdul‐Malak & Jeffrey P. Kharoufeh & Lisa M. Maillart, 2019. "Maintaining systems with heterogeneous spare parts," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(6), pages 485-501, September.
    17. Huynh, K.T., 2021. "An adaptive predictive maintenance model for repairable deteriorating systems using inverse Gaussian degradation process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    18. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2017. "Joint condition-based maintenance and inventory optimization for systems with multiple components," European Journal of Operational Research, Elsevier, vol. 257(1), pages 209-222.
    19. Peng, Hao & van Houtum, Geert-Jan, 2016. "Joint optimization of condition-based maintenance and production lot-sizing," European Journal of Operational Research, Elsevier, vol. 253(1), pages 94-107.
    20. 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).

    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:54:y:2016:i:19:p:5829-5841. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.