In highly flexible and integrated manufacturing systems, such as semiconductor manufacturing, the strong dynamic interactions between the equipment condition, operations executed on the equipment, and the resulting product quality necessitate a methodology that integrates the decision-making process across the domains of maintenance scheduling and production operations. Currently, maintenance and production operations decision-making are two decoupled processes. In this paper, we devise an integrated decision-making policy for maintenance scheduling and production sequencing, with the objective of optimizing a customizable objective function, while taking into account operation-dependent degradation models and a production target. Optimization was achieved using a metaheuristic method based on the results of discrete-event simulations of the target manufacturing system. 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 and often significantly outperforms the current practice of making these decisions separately.