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A multivariate control chart is designed to monitor process parameters ofmultiple correlated quality characteristics. Often data on multivariateprocesses are collected as individual observations, i.e. as vectors one at thetime. Various control charts have been proposed in the literature to monitorthe covariance matrix of a process when individual observations are collected.In this study, we review this literature; we find 30 relevant articles from theperiod 1987-2019. We group the articles into five categories. We observe thatless research has been done on CUSUM, high-dimensional and non-parametric typecontrol charts for monitoring the process covariance matrix. We describe eachproposed method, state their advantages, and limitations. Finally, we givesuggestions for future research.

A Review of Dispersion Control Charts for Multivariate Individual Observations