This paper studies the effects of multivariate measurement errors on mul- tivariate capability indices computed using the principal components analysis. This study shows that measurement errors influence the results of a multivariate process capability analysis, resulting in either a decrease or an increase in the capability of the process. To avoid unreliable conclusions a method is proposed for overcom- ing the effects of measurement errors. Furthermore, a statistical test that allows one to determine whether measurement errors alter the process covariance structure is discussed
On the use of principal component analysis for assessing multivariate process capability / M. Scagliarini; S. Evangelisti. - ELETTRONICO. - (2011), pp. 1-4. (Intervento presentato al convegno CLADAG 2011, 8th Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society tenutosi a Pavia nel September 7-9, 2011).
On the use of principal component analysis for assessing multivariate process capability
SCAGLIARINI, MICHELE;
2011
Abstract
This paper studies the effects of multivariate measurement errors on mul- tivariate capability indices computed using the principal components analysis. This study shows that measurement errors influence the results of a multivariate process capability analysis, resulting in either a decrease or an increase in the capability of the process. To avoid unreliable conclusions a method is proposed for overcom- ing the effects of measurement errors. Furthermore, a statistical test that allows one to determine whether measurement errors alter the process covariance structure is discussedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
