A fuzzy-neural approach for remaining cycle time estimation in a semiconductor manufacturing factory-a simulation study

Tin-Chih Chen, Yi Chi Wang, Hsin Chieh Wu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

A fuzzy-neural approach is proposed in this study for estimating the remaining cycle time of each job in a semiconductor manufacturing factory, which was seldom investigated in the past studies but is a critical task for semiconductor manufacturing industry. The proposed methodology applies the FCM-FBPN approach with multiple buckets to estimate both the cycle time and the step cycle time of a job, and then derives the remaining cycle time with the proportional adjustment approach. To evaluate the effectiveness of the proposed methodology, production simulation is used to generate some test data. According to the experimental results, the estimation accuracy of the proposed methodology was significantly better than those of many existing approaches.

Original languageEnglish
Pages (from-to)2125-2139
Number of pages15
JournalInternational Journal of Innovative Computing, Information and Control
Volume5
Issue number8
StatePublished - 1 Aug 2009

Keywords

  • Fuzzy-neural
  • Remaining cycle time
  • Semiconductor manufacturing
  • Simulation
  • Step cycle time

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