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Mathematical Problems in Engineering
Volume 2012, Article ID 875641, 16 pages
Research Article

Genetic Algorithm for Job Scheduling with Maintenance Consideration in Semiconductor Manufacturing Process

Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA

Received 26 March 2012; Accepted 14 September 2012

Academic Editor: Joao B. R. Do Val

Copyright © 2012 Seungchul Lee and Jun Ni. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents wafer sequencing problems considering perceived chamber conditions and maintenance activities in a single cluster tool through the simulation-based optimization method. We develop optimization methods which would lead to the best wafer release policy in the chamber tool to maximize the overall yield of the wafers in semiconductor manufacturing system. Since chamber degradation will jeopardize wafer yields, chamber maintenance is taken into account for the wafer sequence decision-making process. Furthermore, genetic algorithm is modified for solving the scheduling problems in this paper. As results, it has been shown that job scheduling has to be managed based on the chamber degradation condition and maintenance activities to maximize overall wafer yield.