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Maintenance cost assessment for heterogeneous multi-component systems incorporating perfect inspections and waiting time to maintenance

Author

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  • Lucía Bautista
  • Inma T Castro
  • Luis Landesa

Abstract

Most existing research about complex systems maintenance assumes they consist of the same type of components. However, systems can be assembled with heterogeneous components (for example degrading and non-degrading components) that require different maintenance actions. Since industrial systems become more and more complex, more research about the maintenance of systems with heterogeneous components is needed. For this reason, in this paper, a system consisting of two groups of components: degrading and non-degrading components is analyzed. The main novelty of this paper is the evaluation of a maintenance policy at system-level coordinating condition-based maintenance for the degrading components, delay time to the maintenance and an inspection strategy for this heterogeneous system. To that end, an analytic cost model is built using the semi-regenerative processes theory. Furthermore, a safety constraint related to the reliability of the degrading components is imposed. To find the optimal maintenance strategy, meta-heuristic algorithms are used.

Suggested Citation

  • Lucía Bautista & Inma T Castro & Luis Landesa, 2022. "Maintenance cost assessment for heterogeneous multi-component systems incorporating perfect inspections and waiting time to maintenance," Journal of Risk and Reliability, , vol. 236(5), pages 797-815, October.
    • Handle: RePEc:sae:risrel:v:236:y:2022:i:5:p:797-815
    DOI: 10.1177/1748006X211038804
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    References listed on IDEAS

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    1. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    2. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper & Babai, M. Zied, 2018. "Condition-based maintenance for systems with economic dependence and load sharing," International Journal of Production Economics, Elsevier, vol. 195(C), pages 319-327.
    3. Poppe, Joeri & Boute, Robert N. & Lambrecht, Marc R., 2018. "A hybrid condition-based maintenance policy for continuously monitored components with two degradation thresholds," European Journal of Operational Research, Elsevier, vol. 268(2), pages 515-532.
    4. MERCIER, Sophie & CASTRO, I.T., 2019. "Stochastic comparisons of imperfect maintenance models for a gamma deteriorating system," European Journal of Operational Research, Elsevier, vol. 273(1), pages 237-248.
    5. Castro, Inma T. & Basten, Rob J.I. & van Houtum, Geert-Jan, 2020. "Maintenance cost evaluation for heterogeneous complex systems under continuous monitoring," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    6. Compare, M. & Martini, F. & Zio, E., 2015. "Genetic algorithms for condition-based maintenance optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 244(2), pages 611-623.
    7. Huynh, K.T., 2020. "Modeling past-dependent partial repairs for condition-based maintenance of continuously deteriorating systems," European Journal of Operational Research, Elsevier, vol. 280(1), pages 152-163.
    8. Zhang, Xiaohong & Zeng, Jianchao, 2015. "A general modeling method for opportunistic maintenance modeling of multi-unit systems," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 176-190.
    9. Aven, Terje & Castro, I.T., 2008. "A minimal repair replacement model with two types of failure and a safety constraint," European Journal of Operational Research, Elsevier, vol. 188(2), pages 506-515, July.
    10. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    11. Zhu, Qiushi & Peng, Hao & Timmermans, Bas & van Houtum, Geert-Jan, 2017. "A condition-based maintenance model for a single component in a system with scheduled and unscheduled downs," International Journal of Production Economics, Elsevier, vol. 193(C), pages 365-380.
    12. Dieulle, L. & Berenguer, C. & Grall, A. & Roussignol, M., 2003. "Sequential condition-based maintenance scheduling for a deteriorating system," European Journal of Operational Research, Elsevier, vol. 150(2), pages 451-461, October.
    13. Zhang, Nan & Fouladirad, Mitra & Barros, Anne & Zhang, Jun, 2020. "Condition-based maintenance for a K-out-of-N deteriorating system under periodic inspection with failure dependence," European Journal of Operational Research, Elsevier, vol. 287(1), pages 159-167.
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    Cited by:

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