A fuzzy tailored nonlinear fluctuation smoothing rule for job dispatching in a semiconductor manufacturing factory

Tin-Chih Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Job scheduling in a semiconductor manufacturing factory is a difficult task, mainly due to the complexity of the production system and the uncertainty involved in the production activities. Recently, a number of advanced dispatching rules were proposed, which estimate the remaining cycle times of jobs. This predictive nature is conducive to the effectiveness of these rules. However, if the uncertainty in the remaining cycle time can be better considered, then the possibility of incorrect scheduling will be further reduced. To this end, an effective fuzzy aggregation mechanism is established to enhance the performance of the existing fuzzy c-means and back propagation network approach. Subsequently, the two- factor tailored nonlinear fluctuation smoothing rule for mean cycle time (2f-TNFSMCT) is modified in this study, by diversifying the slacks of jobs. The effectiveness of the proposed methodology is illustrated with a simulation study. According to the experimental results, slack diversification was indeed a good idea in improving the scheduling performance of a fluctuation smoothing rule.

Original languageEnglish
Title of host publicationSequencing and Scheduling with Inaccurate Data
PublisherNova Science Publishers, Inc.
Pages139-156
Number of pages18
ISBN (Electronic)9781629487229
ISBN (Print)9781629486772
StatePublished - 1 Jan 2014

Keywords

  • Dispatching rule
  • Diversify
  • Fluctuation smoothing
  • Semiconductor manufacturing
  • Slack

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