Authors: Toly Chen YiChi Wang
Publish Date: 2009/11/20
Volume: 49, Issue: 5-8, Pages: 709-721
Abstract
This paper proposes a bicriteria nonlinear fluctuation smoothing rule to further improve the performance of job scheduling in a wafer fabrication factory wafer fab The rule is based on the wellknown fluctuation smoothing rules First the remaining cycle time of a job is estimated by applying the selforganization map–fuzzy back propagation network approach to improve the estimation accuracy Second two nonlinear forms of the fluctuation smoothing rules are obtained to enhance the balance and responsiveness Third the two nonlinear fluctuation smoothing rules are merged into a bicriteria rule for considering two performance measures average cycle time and cycle time variation at the same time Finally the content of the bicriteria rule can be tailored for the wafer fab and be scheduled with an adjustable factor To evaluate the effectiveness of the proposed methodology a production simulation was conducted According to the experimental results the proposed methodology outperformed some of the existing approaches by reducing the average cycle time and cycle time variation at the same time In addition the experimental results showed that the bicriteria rule made it possible to improve one performance measure without raising the expense of another one
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