Quality improvement in the multi-response problem by using clustering characteristic

Hui Mei Yang*, Kun Lin Hsieh, Lee-Ing Tong

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Most previous studies have only addressed a single-response problem. However, more than one correlated response frequently occurs in a manufacturing product. The multi-response problem has received limited attention. In the second part of this project, an approach based on the clustering analysis (CA) is studied to the optimization of the multi-response problem. In CA, the observations can be combined into groups or clusters such that each group or cluster is homogeneous or compact with respect to certain characteristics and each group is different from other groups with respect to the same characteristics. The optimum parameters' settings for a multi-response problem can be determined by three criterions.

Original languageEnglish
Pages (from-to)1088-1093
Number of pages6
JournalWSEAS Transactions on Systems
Volume6
Issue number5
StatePublished - 1 May 2007

Keywords

  • Clustering analysis
  • Parameter optimization
  • Quality improvement

Cite this