This paper studies the effects of multivariate measurement errors on multivariate 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 overcoming the effects of measurement errors. Furthermore, a statistical test that allows one to determine whether measurement errors alter the process covariance structure is discussed
Principle Component Analysis (PCA) is a tool of many multivariate statistical analysis based on a li...
Different multivariate process capability indices are developed by researchers to evaluate process c...
none2The assessment of the capability of a measurement system is an important aspect of most process...
This paper studies the effects of multivariate measurement errors on multivariate capability indices...
This paper studies the effects of multivariate measurement errors on mul- tivariate capability indic...
This paper studies the effects of multivariate measurement errors on mul- tivariate capability indi...
Various different definitions of multivariate process capability indices have been proposed in the l...
Gauge measurement error is often an important source of variability in manufacturing applications. ...
Alternative definitions of Multivariate Process Capability Indices (MPCIs), based on different appro...
This paper presents a new multivariate process capability index (MPCI) which is based on the princip...
Process capability indices (PCIs) have been widely used in manufacturing industries to provide a qua...
In the context of process capability analysis, the results of most processes are dominated by two or...
Important features of multivariate process capability indices are comparability, interpretability an...
This paper offers a review of univariate and multivariate process capability indices (PCIs). PCIs ar...
The work presented in this thesis considers multivariate process capability indices (MPCIs) with foc...
Principle Component Analysis (PCA) is a tool of many multivariate statistical analysis based on a li...
Different multivariate process capability indices are developed by researchers to evaluate process c...
none2The assessment of the capability of a measurement system is an important aspect of most process...
This paper studies the effects of multivariate measurement errors on multivariate capability indices...
This paper studies the effects of multivariate measurement errors on mul- tivariate capability indic...
This paper studies the effects of multivariate measurement errors on mul- tivariate capability indi...
Various different definitions of multivariate process capability indices have been proposed in the l...
Gauge measurement error is often an important source of variability in manufacturing applications. ...
Alternative definitions of Multivariate Process Capability Indices (MPCIs), based on different appro...
This paper presents a new multivariate process capability index (MPCI) which is based on the princip...
Process capability indices (PCIs) have been widely used in manufacturing industries to provide a qua...
In the context of process capability analysis, the results of most processes are dominated by two or...
Important features of multivariate process capability indices are comparability, interpretability an...
This paper offers a review of univariate and multivariate process capability indices (PCIs). PCIs ar...
The work presented in this thesis considers multivariate process capability indices (MPCIs) with foc...
Principle Component Analysis (PCA) is a tool of many multivariate statistical analysis based on a li...
Different multivariate process capability indices are developed by researchers to evaluate process c...
none2The assessment of the capability of a measurement system is an important aspect of most process...