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Attribute control charts for monitoring the covariance matrix of bivariate processes
Author(s) -
Machado M.A.G.,
Ho L.L.,
Costa A.F.B.
Publication year - 2018
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2253
Subject(s) - control chart , bivariate analysis , covariance matrix , statistics , chart , covariance , mathematics , \bar x and r chart , variance (accounting) , x bar chart , statistical process control , matrix (chemical analysis) , estimation of covariance matrices , control limits , econometrics , computer science , process (computing) , chemistry , economics , accounting , chromatography , operating system
In this article, we consider the use of 3 attribute charts—the n p x y , the n p w and the Max D charts—to control the covariance matrix of bivariate processes. In comparison with the generalized variance |S| chart, the 3 attribute charts signal faster, with smaller samples, all kind of disturbances, except when the 2 variables are highly correlated. To compete with the VMAX chart, the Max D chart needs larger samples, but no more than twice bigger. An example illustrates the monitoring of the covariance matrix using the Max D and n p w .