Numerical Switching Performances of Cumulative Sum Chart for Dispersion Matrix

Abstract

In many cases, the quality of a product is determined by several correlated quality variables. Control charts have been used for a long time widely to control the production process and to quickly detect the assignable causes that may produce any deterioration in the quality of a product. Numerical switching performances of multivariate cumulative sum control chart for simultaneous monitoring all components in the dispersion matrix 􀄰 under multivariate normal process are considered. Numerical performances were evaluated for various shifts of the values of variances and/or correlation coefficients in . Our computational results show that if one wants to quick detect the small shifts in a process, CUSUM control chart with small reference value 􀆉 is more efficient than large 􀆉 in terms of average run length (ARL), average time to signal (ATS), average number of switches (ANSW).