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Analytical method for optimization of maintenance policy based on available system failure data

Author

Listed:
  • Coria, V.H.
  • Maximov, S.
  • Rivas-Dávalos, F.
  • Melchor, C.L.
  • Guardado, J.L.

Abstract

An analytical optimization method for preventive maintenance (PM) policy with minimal repair at failure, periodic maintenance, and replacement is proposed for systems with historical failure time data influenced by a current PM policy. The method includes a new imperfect PM model based on Weibull distribution and incorporates the current maintenance interval T0 and the optimal maintenance interval T to be found. The Weibull parameters are analytically estimated using maximum likelihood estimation. Based on this model, the optimal number of PM and the optimal maintenance interval for minimizing the expected cost over an infinite time horizon are also analytically determined. A number of examples are presented involving different failure time data and current maintenance intervals to analyze how the proposed analytical optimization method for periodic PM policy performances in response to changes in the distribution of the failure data and the current maintenance interval.

Suggested Citation

  • Coria, V.H. & Maximov, S. & Rivas-Dávalos, F. & Melchor, C.L. & Guardado, J.L., 2015. "Analytical method for optimization of maintenance policy based on available system failure data," Reliability Engineering and System Safety, Elsevier, vol. 135(C), pages 55-63.
    • Handle: RePEc:eee:reensy:v:135:y:2015:i:c:p:55-63
    DOI: 10.1016/j.ress.2014.11.003
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    References listed on IDEAS

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    Cited by:

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    2. de Jonge, Bram & Jakobsons, Edgars, 2018. "Optimizing block-based maintenance under random machine usage," European Journal of Operational Research, Elsevier, vol. 265(2), pages 703-709.
    3. Ágota Bányai, 2021. "Energy Consumption-Based Maintenance Policy Optimization," Energies, MDPI, vol. 14(18), pages 1-33, September.
    4. Sheu, Shey-Huei & Tsai, Hsin-Nan & Sheu, Uan-Yu & Zhang, Zhe George, 2019. "Optimal replacement policies for a system based on a one-cycle criterion," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Martón, I. & Martorell, P. & Mullor, R. & Sánchez, A.I. & Martorell, S., 2016. "Optimization of test and maintenance of ageing components consisting of multiple items and addressing effectiveness," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 151-158.
    6. Francesco Corman & Sander Kraijema & Milinko Godjevac & Gabriel Lodewijks, 2017. "Optimizing preventive maintenance policy: A data-driven application for a light rail braking system," Journal of Risk and Reliability, , vol. 231(5), pages 534-545, October.
    7. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    8. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

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