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Performance evaluation of multi-state degraded systems with minimal repairs and imperfect preventive maintenance

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  • Soro, Isaac W.
  • Nourelfath, Mustapha
  • Aït-Kadi, Daoud

Abstract

In this paper, we develop a model for evaluating the availability, the production rate and the reliability function of multi-state degraded systems subjected to minimal repairs and imperfect preventive maintenance. The status of the system is considered to degrade with use. These degradations may lead to decrease in the system efficiency. It is assumed that the system can consecutively degrade into several discrete states, which are characterized by different performance rates, ranging from perfect functioning to complete failure. The latter is observed when the degradation level reaches a certain critical threshold such as the system efficiency may decrease to an unacceptable limit. In addition, the system can fail randomly from any operational or acceptable state and can be repaired. This repair action brings the system to its previous operational state without affecting its failure rate (i.e., minimal repair). The used preventive maintenance policy suggests that if the system reaches the last acceptable degraded state, it is brought back to one of the states with higher efficiency. Considering customer demand as constant, the system is modeled as a continuous-time Markov process to assess its instantaneous and stationary performance measures. A numerical example is given to illustrate the proposed model.

Suggested Citation

  • Soro, Isaac W. & Nourelfath, Mustapha & Aït-Kadi, Daoud, 2010. "Performance evaluation of multi-state degraded systems with minimal repairs and imperfect preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 65-69.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:2:p:65-69
    DOI: 10.1016/j.ress.2009.08.004
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    1. P Vrignat & M Avila & F Duculty & S Aupetit & M Slimane & F Kratz, 2012. "Maintenance policy: degradation laws versus hidden Markov model availability indicator," Journal of Risk and Reliability, , vol. 226(2), pages 137-155, April.
    2. Fitouhi, Mohamed-Chahir & Nourelfath, Mustapha & Gershwin, Stanley B., 2017. "Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 61-72.
    3. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2015. "Optimal loading of system with random repair time," European Journal of Operational Research, Elsevier, vol. 247(1), pages 137-143.
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    7. Belmansour, Ahmed-Tidjani & Nourelfath, Mustapha, 2010. "An aggregation method for performance evaluation of a tandem homogenous production line with machines having multiple failure modes," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1193-1201.
    8. Moghaddass, Ramin & Zuo, Ming J., 2014. "An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 92-104.
    9. Chien, Yu-Hung & Sheu, Shey-Huei & Zhang, Zhe George, 2012. "Optimal maintenance policy for a system subject to damage in a discrete time process," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 1-10.
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    11. Dehayem Nodem, F.I. & Kenné, J.P. & Gharbi, A., 2011. "Simultaneous control of production, repair/replacement and preventive maintenance of deteriorating manufacturing systems," International Journal of Production Economics, Elsevier, vol. 134(1), pages 271-282, November.
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    14. 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.
    15. Nourelfath, Mustapha & Châtelet, Eric & Nahas, Nabil, 2012. "Joint redundancy and imperfect preventive maintenance optimization for series–parallel multi-state degraded systems," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 51-60.
    16. Wang, Chuan & Liu, Yupeng & Wang, Dongbo & Wang, Guorong & Wang, Dingya & Yu, Chao, 2021. "Reliability evaluation method based on dynamic fault diagnosis results: A case study of a seabed mud lifting system," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    17. Yin, Mingang & Liu, Yu & Liu, Shuntao & Chen, Yiming & Yan, Yutao, 2023. "Scheduling heterogeneous repair channels in selective maintenance of multi-state systems with maintenance duration uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    18. Zhang, Aibo & Srivastav, Himanshu & Barros, Anne & Liu, Yiliu, 2021. "Study of testing and maintenance strategies for redundant final elements in SIS with imperfect detection of degraded state," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    20. 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.
    21. Moghaddass, Ramin & Zuo, Ming J., 2012. "A parameter estimation method for a condition-monitored device under multi-state deterioration," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 94-103.
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    23. Kong, Yaonan & Ye, Zhisheng, 2017. "Goodness-of-fit tests in the multi-state Markov model," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 16-24.

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