Use of simulation in optimization of maintenance policies

Selecting an optimum maintenance policy independent of other parameters of the production system does not always yield the overall optimum operating conditions. For instance, high levels of in-process inventories affect the performance of a given maintenance policy by reducing the effects of machine breakdowns. In this study, parameters of the production system, in particular the allowable in-process buffers, and the design parameters of the maintenance plan are considered simultaneously as integral parts of the whole decision process for selection and implementation of a maintenance policy. The results from the simulation experiments show that the response surfaces for these systems are of the forms that yield themselves to an optimization search. However, the optimization problem itself is not trivial, as the performance of the system depends on a combination of qualitative and policy variables (the choice of the maintenance policy) as well as a set of quantitative variables (allowable buffer spaces). In this paper, a methodology is presented for solving this class of problems that is based on a combined computer simulation and optimization integrated with a genetic algorithm search.