Incorporating the FCM-BPN approach with nonlinear programming for internal due date assignment in a wafer fabrication plant

Tin-Chih Chen*, Yi C. Wang

*Corresponding author for this work

Research output: Contribution to journalArticle

46 Scopus citations

Abstract

To enhance the performance of the internal due date assignment in a wafer fab even further, this study incorporated the fuzzy c-means-back propagation network (FCM-BPN) approach with a nonlinear programming model. In the proposed methodology, the jobs are first classified into several categories by fuzzy c-means. Then, an individual back propagation network is constructed for each category to predict the completion time of the jobs. Subsequently, an individual nonlinear programming model is constructed for each back propagation network to adjust the connection weights in the back propagation network, allowing us to determine the internal due dates of the jobs in the category. The nonlinear programming model is finally converted into a goal programming problem that can be solved with existing optimization software. According to the experimental results, the proposed methodology outperforms the baseline multiple linear regression (MLR) approach by 24% in predicting the job completion/cycle times. In addition, the proposed methodology also guarantees that all jobs can be finished before the established internal due dates, without adding too large a fudge factor, and without sacrificing the accuracy of the completion/cycle time forecasts.

Original languageEnglish
Pages (from-to)83-91
Number of pages9
JournalRobotics and Computer-Integrated Manufacturing
Volume26
Issue number1
DOIs
StatePublished - 1 Feb 2010

Keywords

  • Back propagation network
  • Fuzzy c-means
  • Goal programming
  • Internal due date
  • Nonlinear programming
  • Wafer fabrication

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