Economic- Statistical Design of MAX EWMAMS Chart under Measurements Error and Multiple Measurements

In this paper, the economic-statistical design of the Max EWMAMS control chart under measurement errors and multiple measurements for joint monitoring of mean and variability of the process is investigated. The traditional approach for monitoring mean and variance of the quality characteristic is using two separate control charts. This approach leads to an increase in the probability of Type I error. To overcome this problem, researchers have proposed control charts for joint monitoring of mean and variability of the process. Also in practice, the measurement errors exist in the sampling process. The sampling with multiple measurements is a way to reduce the deficiency of the measurement error and increasing power of the control chart. However, the multiple measurements cause to increase the sampling costs. Hence, this factor should be considered in the economic-statistical design of control charts as well. In the proposed cost model, the Lorenzen-Vance cost function is developed and a genetic algorithm is applied to obtain model parameters that minimize cost function. Finally, the performance of the proposed model is evaluated by a numerical example.