Monitoring variability of multivariate processes
by Amitava Mitra; Mark Clark
International Journal of Quality Engineering and Technology (IJQET), Vol. 4, No. 2, 2014

Abstract: The paper focuses on determining changes in process variability of multivariate processes. The problem is compounded by the fact that any of the elements in the variance-covariance matrix of variables could change, leading to a change in the process variability. While it may not be feasible to maintain individual control charts for each element of the variance-covariance matrix, some aggregate measure of the variability criteria could be monitored to initially determine if a change has occurred in the process variability. A couple of aggregate measures are proposed and the performance of these suggested measures is explored through a simulation procedure. Compared to the traditional method, which monitors the determinant of the variance-covariance matrix, these alternatives perform well. The performance measure used is the mean time to first detection of a change in the process variability.

Online publication date: Sat, 17-May-2014

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