Quality evaluation using geometric distance approach

Fu Kwun Wang*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

20 Scopus citations

Abstract

Quantitatively assessing quality and using this assessment for competitive benchmarking and diagnostics of manufactured part failure are very important for continuous improvement in modern manufacturing industries. Process capability analysis often entails characterizing or assessing process specification or quality characteristics. When these quality characteristics are related, the analysis should be based on a multivariate statistical technique. A current problem in multivariate quality control is that there is no consensus about a methodology for assessing capability. Thus, the critical first step in instituting a multivariate control scheme is not well defined. While numerous authors have recently proposed alternative definitions of multivariate capability indices, those methods may not be practical in some cases. In this research, a new process control variable, geometric distance (GD), for assessing or evaluating the quality of manufactured product is developed and investigated for reducing dimensionality. The theoretical distribution of the geometric distance is investigated and a suitable performance metric of the multivariate process data is proposed. Finally, some real data are used to demonstrate the capability of the proposed method.

Original languageEnglish
Pages (from-to)139-153
Number of pages15
JournalInternational Journal of Reliability, Quality and Safety Engineering
Volume6
Issue number2
DOIs
StatePublished - 1999
Externally publishedYes

Keywords

  • Capability index
  • Geometric distance
  • Multivariate data
  • Process control variable

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