A New Robust Multivariate EWMA Dispersion Control Chart for Individual Observations

A multivariate control chart is proposed to detect changes in the process dispersion of multiple correlated quality characteristics. We focus on individual observations, where we monitor data vector-by-vector rather than (rational) subgroups. The developed by applying logarithm diagonal elements estimated covariance matrix. Then, this vector incorporated an exponentially weighted moving average (EWMA) statistic. This design makes robust non-normality underlying data. compare performance with popular alternatives. simulation studies show that outperforms existing procedures when there overall decrease In addition, most distribution, small deviations which are difficult detect. Finally, compared charts applied two case studies.