A Direct-solution Fuzzy Collaborative Intelligence Approach for Yield Forecasting in Semiconductor Manufacturing

Yi Chi Wang*, Tin-Chih Chen

*Corresponding author for this work

Research output: Contribution to journalConference article

6 Scopus citations

Abstract

Yield forecasting is a critical task to every semiconductor manufacturer. However, the existing methods for yield forecasting often deal with the logarithmic or log-sigmoid value, rather than the original value, of yield. To resolve this problem, in this study, the fuzzy collaborative intelligence (FCI) method proposed by Chen and Lin (2008) is modified, so that it can consider the original value of yield directly. The modified FCI method is called the direct-solution (DS)-FCI approach. The effectiveness of the DS-FCI approach was validated with a real case. The experimental results showed that the DS-FCI approach outperformed Chen and Lin's FCI method in improving the forecasting accuracy and precision.

Original languageEnglish
Pages (from-to)110-117
Number of pages8
JournalProcedia Manufacturing
Volume17
DOIs
StatePublished - 1 Jan 2018
Event28th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2018 - Columbus, United States
Duration: 11 Jun 201814 Jun 2018

Keywords

  • direct-solve
  • forecasting
  • semiconductor
  • yield

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