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Communication Dans Un Congrès Année : 2022

Optimal Corrective Maintenance Policy Encountering Competing Risks Using Machine Learning Algorithms

Résumé

In this paper, a series system is considered which is periodically inspected. At inspection times, the failed components are replaced by a new one. Therefore, from the component point of view, maintenance is perfect and from the system point of view, maintenance is imperfect. Three different scenarios related to the components lifetime distribution are considered. Firstly, the lifetime distribution of the components and their parameters are assumed to be known, secondly, the lifetime distributions are assumed to be known with unknown parameters and, thirdly lifetime distributions are considered to be unknown. A cost-based maintenance optimization is carried out. The inspection interval is the decision parameter in all scenarios. The first scenario is considered as a benchmark to other scenarios. For the second and third scenarios, machine learning algorithms are used to estimate the decision parameter and to derive the long-run average total maintenance cost. Different cases are compared through numerical implementations.
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Dates et versions

hal-03773061 , version 1 (08-09-2022)

Identifiants

  • HAL Id : hal-03773061 , version 1

Citer

Hasan Misaii, Mitra Fouladirad, Firoozeh Haghighi. Optimal Corrective Maintenance Policy Encountering Competing Risks Using Machine Learning Algorithms. European Safety and Reliability Conference (ESREL), Dublin, Ireland, Aug 2022, Dublin, Ireland. ⟨hal-03773061⟩
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