Preventive maintenance scheduling: a simulation-optimization approach

Darmawan, Agus and Sheu, D. Daniel (2021) Preventive maintenance scheduling: a simulation-optimization approach. Production and Manufacturing Research, 9 (1). 281 – 298. ISSN 21693277

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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. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Item Type: Article
Additional Information: Cited by: 4; All Open Access, Gold Open Access
Uncontrolled Keywords: Discrete event simulation; Particle swarm optimization (PSO); Preventive maintenance; Scheduled maintenance; Scheduling; Semiconductor device manufacture; Silicon wafers; Discrete-event simulations; Maintenance scheduling; Metaheuristic; Optimization approach; Production loss; Re-entrant; Semiconductor industry; Simulation; Simulation optimization; Time windows; Genetic algorithms
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering > Mechanical and Industrial Engineering Department
Depositing User: Sri JUNANDI
Date Deposited: 24 Oct 2024 07:58
Last Modified: 24 Oct 2024 07:58
URI: https://ir.lib.ugm.ac.id/id/eprint/8628

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