Simulation of complex system based on optimization methods for Maintenance scheduling
Résumé
Industrial systems are subject to faults and failures on their components, which can lead to the unavailability of the systems and increase costs due to interventions. A suitable maintenance strategy is therefore a good solution so to reduce such costs, and also to increase the availability of the system. Combination of different kinds of maintenance policies on components of a system can be a good solution. Nevertheless such a combination has to be finely analyzed, so to get the optimal maintenance strategies on the system according to specified criteria (e.g. availability, cost, etc.).
In this publication, we illustrate how the combination of a simulation tool, based on stochastic discrete event systems, and an optimization algorithm can be used to find (one of) the best strategy of maintenances. The simulations are led by an optimization algorithm. We propose a solution that optimizes system availability, and cost with system-maintenance constraints using an exact mathematical formulation. A stochastic simulator performs calculations according to parameters provided by an optimization algorithm, which plans preventive maintenance schedules. The optimization algorithm provides the optimum maintenance scenario defined by the kind of maintenances to apply and the suitable schedules. The experiments show that the simulation based optimization algorithm gives more flexibility to the decision maker.