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Titolo:
A factor-analysis method for diagnosing variability in multivariate manufacturing processes

Autore:

Indirizzi:: Texas A&M Univ, Dept Ind Engn, College Stn, TX 77843 USA Texas A&M Univ College Stn TX USA 77843 d Engn, College Stn, TX 77843 USA Univ Michigan, Dept Ind & Operat Engn, Ann Arbor, MI 48109 USA Univ Michigan Ann Arbor MI USA 48109 Operat Engn, Ann Arbor, MI 48109 USA
Titolo Testata:: TECHNOMETRICS
fascicolo: 1, volume: 43, anno: 2001,
pagine: 84 - 95
SICI:: 0040-1706(200102)43:1<84:AFMFDV>2.0.ZU;2-Q
Fonte:: ISI
Lingua:: ENG
Soggetto:: PRINCIPAL COMPONENTS; MODEL;
Keywords:: fault diagnosis; multivariate analysis; principal components analysis; quality control; statistical process control;
Tipo documento:: Article
Natura:: Periodico
Settore Disciplinare:: Physical, Chemical & Earth Sciences
Citazioni:: 23
Recensione:
Indirizzi per estratti:: Indirizzo: Apley, DW Texas A&M Univ, Dept Ind Engn, College Stn, TX 77843 USA Texas A&M Univ College Stn TX USA 77843 llege Stn, TX 77843 USA



Citazione:: D.W. Apley e J.J. Shi, "A factor-analysis method for diagnosing variability in multivariate manufacturing processes", TECHNOMET, 43(1), 2001, pp. 84-95

Abstract

In many modern manufacturing processes, large quantities of multivariate process-measurement data are available through automated in-process sensing. This article presents a statistical technique for extracting and interpreting information from the data for the purpose of diagnosing root causes of process variability. The method is related to principal components analysisand factor analysis but makes more explicit use of a model describing the relationship between process faults and process variability. Statistical properties of the diagnostic method are discussed, and illustrative examples from autobody assembly are provided.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 20/06/13 alle ore 04:22:10