Optimal Designs of the Multivariate Synthetic Chart for Monitoring the Process Mean Vector Based on Median Run Length

The average run length (ARL) is usually used as a sole measure of performance of a multivariate control chart. The Hotelling's T(2), multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) charts are commonly optimally designed based on the ARL. Similar to the case of univariate quality control, in multivariate quality control, the shape of the run length distribution changes in accordance to the magnitude of the shift in the mean vector, from highly skewed when the process is in-control to nearly symmetric for large shifts. Because the shape of the run length distribution changes with the magnitude of the shift in the mean vector, the median run length (MRL) provides additional and more meaningful information about the in-control and out-of-control performances of multivariate charts, not given by the ARL. This paper provides a procedure for optimal designs of the multivariate synthetic T(2) chart for the process mean, based on MRL, for both the zero and steady-state modes. Two Mathematica programs, each for the zero state and steady-state modes are given for a quick computation of the optimal parameters of the synthetic T(2) chart, designed based on MRL. These optimal parameters are provided in the paper, for the bivariate case with sample sizes, n is an element of {4,7,10}. The MRL performances of the synthetic T(2), MEWMA and Hotelling's T(2) charts are also compared. Copyright (C) 2011 John Wiley & Sons, Ltd.