Abstract
Nonrandom or systematic patterns occurring in a univariate Shewhart control chart have often been used as indicators of extraneous sources of process variation. Proper diagnosis of these patterns can lead to process improvement by reducing the overall system variation. Similarly, in multivariate statistical process control, many different systematic patterns may occur in the control charts used to monitor the process. The purpose of this paper is to examine the process conditions that lead to the occurrence of certain nonrandom patterns in a T2 control chart. Examples resulting from cycles, mixtures, trends, process shifts, and autocorrelated data are identified and presented. Results are applicable to a Phase I operation or a Phase II operation where the T2 statistic is based on the most common covariance matrix estimator.
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