5A1 SCHEDULING A WAFER FABRICATION FACTORY WITH A FUZZY-NEURO APPROACH

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概要

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• To improve the performance of scheduling jobs in a wafer fabrication factory, a fuzzy-neural approach is proposed in this study. The fuzzy-neural approach is modified from the well-known FSVCT rule with three innovative treatments. At first, the remaining cycle time of a job is estimated by applying a fuzzy-neural approach to improve the estimation accuracy. Second, the components of FSVCT are normalized, and then the division operator is applied instead of the traditional subtraction operator to enhance the responsiveness of the rule. Thrid, the content of the fuzzy-neural approach can be tailored for the wafer fabrication factory to be scheduled with two adjustment factors. To evaluate the effectiveness of the proposed methodology, production simulation is also applied in this study. According to experimental results, the proposed methodology out-performed nine existing approaches in reducing the average cycle time and cycle time standard deviation. Besides, the fuzzy-neural approach was also a Pareto optimal solution for scheduling jobs in a wafer fabrication factory.

• 2009-07-04

著者

• Wu Ming

  Department Of Chemistry National Sun Yat Sen University

• Wu Ming

  Department Of Industrial Engineering And Systems Management Feng Chia University

• Chen Toly

  Department of Industrial Engineering and Systems Management Feng Chia University

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• 5A1 SCHEDULING A WAFER FABRICATION FACTORY WITH A FUZZY-NEURO APPROACH

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