Process-oriented basis representations for multivariate process diagnostics

Russell Richard Barton, David R. Gonzalez-Barreto

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Statistical methods for multivariate process control do not provide engineering tools for the diagnosis of manufacturing processes. Rather, they characterize and monitor the randomness inherent in manufactured products to identify time periods or production batches which show irregular or atypical characteristics. It is up to the production engineer to diagnose the cause or causes of these irregularities and to define the appropriate action. This article proposes a new diagnostic approach for multivariate process measurement vectors using a process-oriented basis. Many potential production problems have characteristic signatures that can be detected in the multivariate quality vector. Each signature can be used as a basis element in the process-oriented basis. The representation of the multivariate bias or variance using this basis will identify a small set of potential causes, those associated with basis elements (signatures) with the largest coefficients.

Original languageEnglish (US)
Pages (from-to)107-118
Number of pages12
JournalQuality Engineering
Volume9
Issue number1
DOIs
StatePublished - Jan 1 1996

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Process control
Statistical methods
Engineers

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Industrial and Manufacturing Engineering

Cite this

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Process-oriented basis representations for multivariate process diagnostics. / Barton, Russell Richard; Gonzalez-Barreto, David R.

In: Quality Engineering, Vol. 9, No. 1, 01.01.1996, p. 107-118.

Research output: Contribution to journalArticle

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