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Availability Analysis and Preventive Maintenance Planning for Systems with General Time Distributions

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  • Wang, Naichao
  • Hu, Jiawen
  • Ma, Lin
  • Xiao, Boping
  • Liao, Haitao

Abstract

Steady-state availability is one of the most important performance measures for repairable systems. To improve the steady-state availability of such systems, preventive maintenance (PM) models have been extensively studied. However, these models assume that the distributions of the system lifetime and maintenance duration are exponential. In practice, the probabilistic characteristics of different systems and maintenance actions are so broad making the exponential distribution an inappropriate model. This paper seeks to determine the optimal PM strategy that maximizes the steady-state availability of a system involving general probability distributions. Specifically, PM is scheduled periodically, and a certain number of imperfect maintenance (IM) actions are carried out before each replacement. We develop state-transition equations involving general probability distributions using a supplementary variable method. The stationary distribution is calculated by solving the system of linear equations, through which the steady-state availability of the system is obtained. We prove the existence of the optimal combination of the number of IM actions before each replacement and the scheduled PM interval. Numerical examples are presented to illustrate the effectiveness of our proposed method in handling such practical maintenance problems.

Suggested Citation

  • Wang, Naichao & Hu, Jiawen & Ma, Lin & Xiao, Boping & Liao, Haitao, 2020. "Availability Analysis and Preventive Maintenance Planning for Systems with General Time Distributions," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:reensy:v:201:y:2020:i:c:s0951832020304944
    DOI: 10.1016/j.ress.2020.106993
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    References listed on IDEAS

    as
    1. Hu, Jiawen & Chen, Piao, 2020. "Predictive maintenance of systems subject to hard failure based on proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    2. Jiawen Hu & Zuhua Jiang & Haitao Liao, 2017. "Preventive maintenance of a batch production system under time-varying operational condition," International Journal of Production Research, Taylor & Francis Journals, vol. 55(19), pages 5681-5705, October.
    3. Pham, Hoang & Wang, Hongzhou, 1996. "Imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 94(3), pages 425-438, November.
    4. Hu, Jiawen & Jiang, Zuhua & Liao, Haitao, 2017. "Preventive maintenance of a single machine system working under piecewise constant operating condition," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 105-115.
    5. Xiujie Zhao & Olivier Gaudoin & Laurent Doyen & Min Xie, 2019. "Optimal inspection and replacement policy based on experimental degradation data with covariates," IISE Transactions, Taylor & Francis Journals, vol. 51(3), pages 322-336, March.
    6. Jingyuan Shen & Jiawen Hu & Zhi-Sheng Ye, 2020. "Optimal switching policy for warm standby systems subjected to standby failure mode," IISE Transactions, Taylor & Francis Journals, vol. 52(11), pages 1262-1274, November.
    7. Xia, Tangbin & Jin, Xiaoning & Xi, Lifeng & Ni, Jun, 2015. "Production-driven opportunistic maintenance for batch production based on MAM–APB scheduling," European Journal of Operational Research, Elsevier, vol. 240(3), pages 781-790.
    8. 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.
    9. Zhao, Xiujie & He, Shuguang & Xie, Min, 2018. "Utilizing experimental degradation data for warranty cost optimization under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 108-119.
    10. 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.
    11. 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.
    12. Yang, Li & Ye, Zhi-sheng & Lee, Chi-Guhn & Yang, Su-fen & Peng, Rui, 2019. "A two-phase preventive maintenance policy considering imperfect repair and postponed replacement," European Journal of Operational Research, Elsevier, vol. 274(3), pages 966-977.
    13. Cheng, Yung-Hsiang & Tsao, Hou-Lei, 2010. "Rolling stock maintenance strategy selection, spares parts' estimation, and replacements' interval calculation," International Journal of Production Economics, Elsevier, vol. 128(1), pages 404-412, November.
    14. Shen, Jingyuan & Cui, Lirong & Ma, Yizhong, 2019. "Availability and optimal maintenance policy for systems degrading in dynamic environments," European Journal of Operational Research, Elsevier, vol. 276(1), pages 133-143.
    15. Zhang, Nan & Fouladirad, Mitra & Barros, Anne, 2019. "Reliability-based measures and prognostic analysis of a K-out-of-N system in a random environment," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1120-1131.
    16. Piao Chen & Zhi-Sheng Ye & Qingqing Zhai, 2020. "Parametric analysis of time-censored aggregate lifetime data," IISE Transactions, Taylor & Francis Journals, vol. 52(5), pages 516-527, May.
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    3. Asadi, Majid, 2023. "On a parametric model for the mean number of system repairs with applications," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Jafar-Zanjani, Hamed & Zandieh, Mostafa & Sharifi, Mani, 2022. "Robust and resilient joint periodic maintenance planning and scheduling in a multi-factory network under uncertainty: A case study," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    5. Wang, Kuo-Hsiung & Wu, Chia-Huang & Yen, Tseng-Chang, 2022. "Comparative cost-benefit analysis of four retrial systems with preventive maintenance and unreliable service station," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Wu, Chia-Huang & Yen, Tseng-Chang & Wang, Kuo-Hsiung, 2021. "Availability and Comparison of Four Retrial Systems with Imperfect Coverage and General Repair Times," Reliability Engineering and System Safety, Elsevier, vol. 212(C).

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