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Regression Adjustment for Variables in Multivariate Quality Control

Summary: Multivariate process control problems are inherently more difficult than univariate problems. It is not always clear what type of multivariate statistic should be used, and the most statistically powerful techniques do not indicate the cause(s) of a signal. On the other hand, separate controls on the individual variables are more easily interpretable but may be substantially less powerful, particularly in the face of appreciable correlation between the measures. Previous research has demonstrated the effectiveness of methods that capitalize on the likely nature of a departure from control. If only one variable is likely to undergo a shift in mean or variance then charting of each variable adjusted by regression for all others is particularly effective. In this paper, the issue of other possible regression adjustments is discussed. In particular, a regression of each variable for those driving it is considered. It is shown under what circumstances this adjustment is appropriate, and its diagnostic power is illustrated by examples.

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  • Topics:
  • Keywords: Hotelling's T2 statistic,Control charts,Multivariate control charts
  • Author: Hawkins, Douglas
  • Journal: Journal of Quality Technology