A hybrid neural network and selective allowance approach for internal due date assignment in a wafer fabrication plant

Tin-Chih Chen*, Angus Jeang, Yi Chi Wang

*Corresponding author for this work

Research output: Contribution to journalArticle

36 Scopus citations

Abstract

A hybrid neural network and selective allowance approach is proposed in this study for internal due date assignment in a wafer fabrication plant (wafer fab). In the first part, a look-ahead self-organization map-fuzzy back propagation network (SOM-FBPN) is constructed to estimate the completion time of a job. Subsequently, a selective allowance policy is established to determine the allowance that will be added to the estimated job completion time. Compared with traditional approaches, the look-ahead SOM-FBPN has many features (including incorporating the future release plan, classifying jobs, and incorporating expert opinions), and the selective allowance policy is novel by considering two different production control issues to avoid missing the due date. According to experimental results, the prediction accuracy of the look-ahead SOM-FBPN was significantly better than those of many existing approaches. Besides, the selective allowance policy considerably improved the due date related performance after adding some extra allowance.

Original languageEnglish
Pages (from-to)570-581
Number of pages12
JournalInternational Journal of Advanced Manufacturing Technology
Volume36
Issue number5-6
DOIs
StatePublished - 1 Mar 2008

Keywords

  • Allowance
  • Fuzzy back propagation network
  • Internal due date assignment
  • Self-organization map
  • Wafer fab

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