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Improvement of Process Capability Through Neural Networks and Robust Design: A Case Study

Summary: [This abstract is based on the authors' abstract.] A method integrating neural network and robust design methods is proposed for improving process capability by optimizing multiple characteristics. Optimum parameter settings are obtained by using the neural network to provide a nonlinear relationship between process parameters and corresponding responses, thereby ensuring efficient process control. The method is demonstrated in a polymerization process in a silicon-filter manufacturing facility.

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  • Topics: Process Capability
  • Keywords: Taguchi method, Estimation, Case study, Analysis of variance (ANOVA), Orthogonal array (OA)
  • Author: Chiang, Tai-Lin; Su, Chao-Ton; Li, Te-Sheng; Huang, Robert C.C.
  • Journal: Quality Engineering