Optimization of multi-response processes using the VIKOR method

Lee-Ing Tong*, Chi Chan Chen, Chung Ho Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

118 Scopus citations

Abstract

Design of experiments and Taguchi methods are extensively adopted as off-line quality improvement techniques in industry. However, these methods were developed to optimize single-response processes. In many situations, multiple responses must be optimized simultaneously, since some product designs, especially in the integrated circuit industry, are becoming increasingly complex to meet customers' demands. Although several procedures for optimizing multi-response processes have been developed in recent years, the associated quality measurement indices do not consider variations in the relative quality losses of multiple responses. These procedures may therefore result in an optimization in which quality losses associated with a few responses are very small but those associated with others are very large, even if the overall average quality loss is small. Such an optimization with a large variation of quality losses among the responses is usually unacceptable to engineers. Accordingly, this study employs the VIKOR method, which is a compromise ranking method used for multicriteria decision making (MCDM), to optimize the multi-response process. The proposed method considers both the mean and the variation of quality losses associated with several multiple responses, and ensures a small variation in quality losses among the responses, along with a small overall average loss. Two case studies of plasma-enhanced chemical vapor deposition and copper chemical mechanical polishing demonstrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1049-1057
Number of pages9
JournalInternational Journal of Advanced Manufacturing Technology
Volume31
Issue number11-12
DOIs
StatePublished - 1 Feb 2007

Keywords

  • Multi-response process
  • Multicriteria decision making
  • Optimization
  • Quality loss
  • Taguchi method
  • VIKOR method

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