Economic-Statistical design of Adaptive T^2 control charts: Markov Chain Approach

This paper presents an economic-statistical design of T^2 control charts with variable parameters (VP). We optimize this model using a genetic algorithm (GA) approach. Furthermore, variable sample size and control limits (VSSC) and variable sample size (VSS), variable sampling interval (VSI), variable sampling interval and control limits (VSIC) and VP T^2 charts are compared with respect to the expected cost per unit time. The Hotelling’s T^2 control chart with variable parameters (VP T^2) has been proved to have a very good performance on detecting small shifts when it is compared to the other T^2 control chart.