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Optimal imperfect preventive maintenance policies for a used system

Author

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  • Xufeng Zhao
  • Toshio Nakagawa
  • Cunhua Qian

Abstract

In some practical situations, it may be more economical to work a used system than do a new one. From this viewpoint, this article considers three basic preventive maintenance (PM) policies for a used system: the system with initial variable damage Y0 begins to operate at time 0, and suffers damage due to shocks. It fails when the total damage exceeds a failure level K and corrective maintenance is made immediately. To prevent such failure, it undergoes PM at a planned time T, a shock number N and a damage level k, but maintenances are imperfect. However, failure rate of a used system maybe higher than that of a new one, so some maintenance is applied to the policies at each shock in the extended models. Using the theory of cumulative processes, expected cost rate models are obtained, optimal policies which minimise them are derived analytically and discussed numerically.

Suggested Citation

  • Xufeng Zhao & Toshio Nakagawa & Cunhua Qian, 2012. "Optimal imperfect preventive maintenance policies for a used system," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(9), pages 1632-1641.
    • Handle: RePEc:taf:tsysxx:v:43:y:2012:i:9:p:1632-1641
    DOI: 10.1080/00207721.2010.549583
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    Citations

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    Cited by:

    1. Juan Eloy Ruiz-Castro, 2015. "A preventive maintenance policy for a standby system subject to internal failures and external shocks with loss of units," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(9), pages 1600-1613, July.
    2. Hamidi, Maryam & Szidarovszky, Ferenc & Szidarovszky, Miklos, 2016. "New one cycle criteria for optimizing preventive replacement policies," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 42-48.
    3. Liu, Bin & Xu, Zhengguo & Xie, Min & Kuo, Way, 2014. "A value-based preventive maintenance policy for multi-component system with continuously degrading components," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 83-89.
    4. Junyuan Wang & Jimin Ye & Liang Wang, 2022. "Extended age maintenance models and its optimization for series and parallel systems," Annals of Operations Research, Springer, vol. 312(1), pages 495-517, May.
    5. Fu, Yuqiang & Zhu, Xiaoyan & Ma, Xiaoyang, 2020. "Optimum component reallocation and system replacement maintenance for a used system with increasing minimal repair cost," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    6. Sheu, Shey-Huei & Liu, Tzu-Hsin & Zhang, Zhe-George & Tsai, Hsin-Nan, 2018. "The generalized age maintenance policies with random working times," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 503-514.
    7. Yen-Luan Chen & Chin-Chih Chang & Dwan-Fang Sheu, 2016. "Optimum random and age replacement policies for customer-demand multi-state system reliability under imperfect maintenance," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(5), pages 1130-1141, April.
    8. Mohammad Doostparast & Farhad Kolahan & Mahdi Doostparast, 2015. "Optimisation of PM scheduling for multi-component systems – a simulated annealing approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1199-1207, May.
    9. Shey-Huei Sheu & Tzu-Hsin Liu & Zhe-George Zhang & Hsin-Nan Tsai & Jung-Chih Chen, 2016. "Optimal two-threshold replacement policy in a cumulative damage model," Annals of Operations Research, Springer, vol. 244(1), pages 23-47, September.

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