A fuzzy-neural approach for supporting three-objective job scheduling in a wafer fabrication factory

Tin-Chih Chen*, Yu Cheng Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study is dedicated to three-objective scheduling in a wafer fabrication factory, which has rarely been discussed in the literature but is a very important task. Optimizing a single objective in a complex production system like a wafer fabrication factory is already quite complicated. Optimizing three objectives at the same time is obviously even more complicated. To this end, this study presents a fuzzy-neural approach that fuses three existing rules in a nonlinear way, and which can be tailored, and even optimized, for a wafer fabrication factory. To assess the effectiveness of the proposed methodology, production simulation is also applied in this study. According to the experimental results, the proposed methodology is better than some existing approaches in reducing the average cycle time, the maximum lateness, and cycle time standard deviation.

Original languageEnglish
Pages (from-to)353-367
Number of pages15
JournalNeural Computing and Applications
Volume23
Issue numberSUPPL1
DOIs
StatePublished - 26 Jul 2013

Keywords

  • Fuzzy
  • Neural
  • Scheduling
  • Wafer fabrication

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