A Fuzzy Fluctuation Smoothing Rule for Job Dispatching in a Wafer Fabrication Factory: A Simulation Study

Authors:
Toly Chen
Affiliations:
Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung City, Taiwan
Venue:
International Journal of Fuzzy System Applications
Year:
2012

Citing 7
Cited 0

Using data mining to find patterns in genetic algorithm solutions to a job shop schedule

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A Hybrid SOM-BPN Approach to Lot Output Time Prediction in a Wafer Fab

Neural Processing Letters
A multi-criteria approach for scheduling semiconductor wafer fabrication facilities

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A fuzzy-neural and multiple-bucket approach for estimating lot cycle time in a wafer fab with dynamic product mix

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A fuzzy-neural knowledge-based system for job completion time prediction and internal due date assignment in a wafer fabrication plant

International Journal of Systems Science
An optimized tailored nonlinear fluctuation smoothing rule for scheduling a semiconductor manufacturing factory

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A PCA-FBPN Approach for Job Cycle Time Estimation in a Wafer Fabrication Factory

International Journal of Fuzzy System Applications

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Abstract

Job dispatching in a wafer fabrication factory is a difficult task, mainly due to the complexity of the production system and the uncertainty involved in the production activities. Recently, a number of advanced dispatching rules were proposed, which estimate the remaining cycle times of jobs. This predictive nature is conducive to the effectiveness of these rules. If the uncertainty in the remaining cycle time can be better considered, incorrect scheduling will possibly be reduced. The tailored nonlinear fluctuation smoothing rule for mean cycle time TNFSMCT is fuzzified in this study, by expressing the remaining cycle time with a fuzzy value. The effectiveness of the proposed methodology is illustrated with a simulation study.