In highly flexible and integrated manufacturing systems such as those in semiconductor manufacturing, there exist strong dynamic interactions between the equipment condition, operations executed on the equipment and the resulting product quality. These interactions necessitate a methodology that integrates the decisions of maintenance scheduling and production operations. Currently, maintenance and production operations decision-making are two decoupled processes. In this paper we aim to devise an integrated decision making policy for maintenance scheduling and production sequencing with the objective of maximizing an adaptive profit function, while taking into account operation-dependent degradation models and a production target. In order to obtain the optimal decision policy, a metaheuristic method based on the results of discrete-event simulations of the target manufacturing system is used. The new approach is demonstrated in simulations of a generic cluster tool routinely used in semiconductor manufacturing. The results show that jointly making maintenance and production sequencing decisions consistently outperforms the current practice of making these decisions separately.

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