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Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks

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  • Zhang, Nailong
  • Si, Wujun

Abstract

Condition-Based Maintenance (CBM) planning for multi-component systems has been receiving increasing attention in recent years. Most existing research on CBM assumes that preventive maintenances should be conducted when the degradations of system components reach specific threshold levels upon inspection. However, the search of optimal maintenance threshold levels is often efficient for low-dimensional CBM but becomes challenging if the number of components gets large, especially when those components are subject to complex dependencies. To overcome the challenge, in this paper we propose a novel and flexible CBM model based on a customized deep reinforcement learning for multi-component systems with dependent competing risks. Both stochastic and economic dependencies among the components are considered. Specifically, different from the threshold-based decision making paradigm used in traditional CBM, the proposed model directly maps the multi-component degradation measurements at each inspection epoch to the maintenance decision space with a cost minimization objective, and the leverage of deep reinforcement learning enables high computational efficiencies and thus makes the proposed model suitable for both low and high dimensional CBM. Various numerical studies are conducted for model validations.

Suggested Citation

  • Zhang, Nailong & Si, Wujun, 2020. "Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
  • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s0951832020305950
    DOI: 10.1016/j.ress.2020.107094
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    References listed on IDEAS

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    1. Tian, Zhigang & Jin, Tongdan & Wu, Bairong & Ding, Fangfang, 2011. "Condition based maintenance optimization for wind power generation systems under continuous monitoring," Renewable Energy, Elsevier, vol. 36(5), pages 1502-1509.
    2. 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.
    3. Nailong Zhang & Qingyu Yang, 2015. "Optimal maintenance planning for repairable multi-component systems subject to dependent competing risks," IISE Transactions, Taylor & Francis Journals, vol. 47(5), pages 521-532, May.
    4. Li, Heping & Deloux, Estelle & Dieulle, Laurence, 2016. "A condition-based maintenance policy for multi-component systems with Lévy copulas dependence," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 44-55.
    5. 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.
    6. Liu, Bin & Wu, Shaomin & Xie, Min & Kuo, Way, 2017. "A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost," European Journal of Operational Research, Elsevier, vol. 263(3), pages 879-887.
    7. 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.
    8. Van Horenbeek, Adriaan & Pintelon, Liliane, 2013. "A dynamic predictive maintenance policy for complex multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 39-50.
    9. Wu, Jingda & He, Hongwen & Peng, Jiankun & Li, Yuecheng & Li, Zhanjiang, 2018. "Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus," Applied Energy, Elsevier, vol. 222(C), pages 799-811.
    10. Do, Phuc & Assaf, Roy & Scarf, Phil & Iung, Benoit, 2019. "Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 86-97.
    11. Olde Keizer, Minou C.A. & Flapper, Simme Douwe P. & Teunter, Ruud H., 2017. "Condition-based maintenance policies for systems with multiple dependent components: A review," European Journal of Operational Research, Elsevier, vol. 261(2), pages 405-420.
    12. Verbert, K. & De Schutter, B. & Babuška, R., 2017. "Timely condition-based maintenance planning for multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 310-321.
    13. Cheng, Tianjin & Pandey, Mahesh D. & van der Weide, J.A.M., 2012. "The probability distribution of maintenance cost of a system affected by the gamma process of degradation: Finite time solution," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 65-76.
    14. Shahraki, Ameneh Forouzandeh & Yadav, Om Prakash & Vogiatzis, Chrysafis, 2020. "Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    15. Tian, Zhigang & Liao, Haitao, 2011. "Condition based maintenance optimization for multi-component systems using proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 581-589.
    16. Ding, Fangfang & Tian, Zhigang, 2012. "Opportunistic maintenance for wind farms considering multi-level imperfect maintenance thresholds," Renewable Energy, Elsevier, vol. 45(C), pages 175-182.
    17. Rasmekomen, Nipat & Parlikad, Ajith Kumar, 2016. "Condition-based maintenance of multi-component systems with degradation state-rate interactions," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 1-10.
    18. Dieulle, L. & Berenguer, C. & Grall, A. & Roussignol, M., 2003. "Sequential condition-based maintenance scheduling for a deteriorating system," European Journal of Operational Research, Elsevier, vol. 150(2), pages 451-461, October.
    19. 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.
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