A maintenance optimization approach based on genetic algorithm for multi-component systems considering the effect of human error

Citation:
Maher, H., M. F. Aly, A. H. Islam, and T. Abdelmaguid, "A maintenance optimization approach based on genetic algorithm for multi-component systems considering the effect of human error", International Journal of Industrial and Systems Engineering, vol. 40, issue 1, pp. 51-78, 2022.

Abstract:

The total maintenance cost can be reduced by grouping maintenance actions of several components. This paper contributes to the existing literature by introducing an enhanced maintenance optimization approach that considers the effect of maintenance crew loading due to grouping on the maintenance decisions of multi-component systems. A modified mathematical model is firstly developed for evaluating the failure probability function of each component, the remaining useful life and the maintenance cost. Economic and structural dependencies are taken into consideration. A simulation is secondly implemented to provide estimates of the associated costs with changes in the decision variables. Using the simulation model, an optimization approach based on a genetic algorithm is thirdly developed to minimize the long-term mean maintenance cost per unit time. Computational results show that the proposed maintenance optimization approach provides considerable maintenance cost savings and emphasizes the importance of considering the effect of maintenance crew constraints in maintenance scheduling.

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