Forecasting job cycle time in a wafer fabrication factory by the FPCA-FBPN approach

Tin-Chih Chen*

*Corresponding author for this work

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Principal component analysis (PCA) is a multivariate statistical analysis method. This method constructs a series of linear combinations of the original variables to form a new variable, so that these new variables are unrelated to each other as much as possible to reflect information in a better way. A fuzzy PCA and fuzzy back propagation network (FPCA-FBPN) approach is proposed in this study for forecasting the cycle time of a job in a wafer fabrication factory, which is a critical task to the wafer fabrication factory. For evaluating the effectiveness of the proposed methodology, production simulation is also applied in this study to generate some test data.

Original languageEnglish
Pages (from-to)1050-1054
Number of pages5
JournalInternational Review on Computers and Software
Volume6
Issue number6
StatePublished - 1 Dec 2011

Keywords

  • Back propagation network
  • Cycle time
  • Fuzzy principal component analysis
  • Wafer fabrication factory

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