Abstract
ABSTRACT This paper presents a framework for preventive maintenance (PM) scheduling in the semiconductor industry. We propose an approach for finding PM’s start time within a PM window to minimize production losses due to maintenance activities. In this study, we consider re-entrant process in which wafers will enter the same equipment location several times, but in different stages and sometimes different processes. Due to the optimization problem’s complexity, we develop meta-heuristics such as a genetic algorithm and particle swarm optimization to solve it and compare with the resource leveling as well as the baseline. In the algorithm, we embed discrete event simulation to mimic a wafer fab process and get its performance. The proposed approach able to identify the best arrangement of PM’s start time within a PM window and provides a way to optimize PM schedules for a complex system by simultaneously utilizing meta-heuristics and discrete event simulation.
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