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

Author

Listed:
  • Hagag Maher
  • Mohamed F. Aly
  • Islam H. Afefy
  • Tamer F. Abdelmaguid

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 optimisation 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 optimisation approach based on a genetic algorithm is thirdly developed to minimise the long-term mean maintenance cost per unit time. Computational results show that the proposed maintenance optimisation approach provides considerable maintenance cost savings and emphasises the importance of considering the effect of maintenance crew constraints in maintenance scheduling.

Suggested Citation

  • Hagag Maher & Mohamed F. Aly & Islam H. Afefy & Tamer F. Abdelmaguid, 2022. "A maintenance optimisation approach based on genetic algorithm for multi-component systems considering the effect of human error," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 40(1), pages 51-78.
    • Handle: RePEc:ids:ijisen:v:40:y:2022:i:1:p:51-78
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