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Remaining-useful-lifetime and system-remaining-profit based importance measures for decisions on preventive maintenance

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  • Zhu, Xiaoyan
  • Chen, Zhiqiang
  • Borgonovo, Emanuele

Abstract

We propose two types of importance measures for component selection in preventive maintenance. The first type evaluates the relative importance of a component in terms of how much the component restoration increases the remaining useful lifetime of the system. The second type of importance measures evaluates the contribution of a maintenance action on a component with respect to the profit that the system can generate during its remaining useful lifetime, considering system reliability, maintenance cost, and uncertain system profit over the remaining useful lifetime. The proposed importance measures take into account various maintenance actions including imperfect repair and replacement, combine the advantages of time-dependent and time-independent lifetime measures on evaluating component importance and are suitable to aid the preventive maintenance decisions on component selection at any time. A numerical example and an application in the preventive maintenance for a wind turbine system are provided to illustrate the proposed importance measures and to compare various time-dependent and time-independent lifetime importance measures.

Suggested Citation

  • Zhu, Xiaoyan & Chen, Zhiqiang & Borgonovo, Emanuele, 2021. "Remaining-useful-lifetime and system-remaining-profit based importance measures for decisions on preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004646
    DOI: 10.1016/j.ress.2021.107951
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    Citations

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    Cited by:

    1. Hongyan Dui & Yulu Zhang & Yun-An Zhang, 2023. "Grouping Maintenance Policy for Improving Reliability of Wind Turbine Systems Considering Variable Cost," Mathematics, MDPI, vol. 11(8), pages 1-20, April.
    2. Cao, Yingsai & Lu, Chen & Dong, Wenjie, 2024. "Importance measures for multi-state systems with multiple components under hierarchical dependences," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    3. Mohamed Benbouzid & Tarek Berghout & Nur Sarma & Siniša Djurović & Yueqi Wu & Xiandong Ma, 2021. "Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review," Energies, MDPI, vol. 14(18), pages 1-33, September.
    4. Zhao, Xian & He, Zongda & Wu, Yaguang & Qiu, Qingan, 2022. "Joint optimization of condition-based performance control and maintenance policies for mission-critical systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2022. "A reliability-and-cost-based framework to optimize maintenance planning and diverse-skilled technician routing for geographically distributed systems," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. Floreale, Giovanni & Baraldi, Piero & Lu, Xuefei & Rossetti, Paolo & Zio, Enrico, 2024. "Sensitivity analysis by differential importance measure for unsupervised fault diagnostics," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    7. Chen, Rentong & Zhang, Chao & Wang, Shaoping & Zio, Enrico & Dui, Hongyan & Zhang, Yadong, 2023. "Importance measures for critical components in complex system based on Copula Hierarchical Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    8. Dui, Hongyan & Liu, Meng & Song, Jiaying & Wu, Shaomin, 2023. "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    9. Dui, Hongyan & Wei, Xuan & Xing, Liudong, 2023. "A new multi-criteria importance measure and its applications to risk reduction and safety enhancement," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    10. Takeda, Satoshi & Kitada, Takanori, 2023. "Importance measure evaluation based on sensitivity coefficient for probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    11. Song, Wanqing & Duan, Shouwu & Zio, Enrico & Kudreyko, Aleksey, 2022. "Multifractional and long-range dependent characteristics for remaining useful life prediction of cracking gas compressor," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    12. Ma, Chengye & Du, Yongjun & Zhang, Yuchun & Cai, Zhiqiang, 2022. "Marginal and joint failure importance for K-terminal network edges under counting process," Reliability Engineering and System Safety, Elsevier, vol. 223(C).

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