In some manufacturing settings, such as during process start-up and in the case of short production runs, process parameters are unknown, and Phase I samples cannot be gathered to accurately estimate control limits for prospective monitoring. Self-starting charts can be applied to these low-volume applications. In this article, two new self-starting multivariate control charts, both based on a CUSCORE-type procedure, are proposed for monitoring the unknown mean of a multivariate normal distribution. These charting procedures, which weight current observations according to the information contained in the fault signature, are able to outperform the previously suggested self-starting charts, which neglect the dynamic pattern of the mean change.
Self-Starting CUSCORE Control Charts for Individual Multivariate Observations
CAPIZZI, GIOVANNA;MASAROTTO, GUIDO
2010
Abstract
In some manufacturing settings, such as during process start-up and in the case of short production runs, process parameters are unknown, and Phase I samples cannot be gathered to accurately estimate control limits for prospective monitoring. Self-starting charts can be applied to these low-volume applications. In this article, two new self-starting multivariate control charts, both based on a CUSCORE-type procedure, are proposed for monitoring the unknown mean of a multivariate normal distribution. These charting procedures, which weight current observations according to the information contained in the fault signature, are able to outperform the previously suggested self-starting charts, which neglect the dynamic pattern of the mean change.
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