Exponentially weighted moving average control chart using auxiliary variable with measurement error

Control chart is one of the important industrial tools used for monitoring the stability of manufacturing processes. Measurement error plays an important role in quality control process and adversely affects the shift detection ability of control charts. In this article, we examined the effect of measurement error on auxiliary variable based exponentially weighted moving average (EWMA-Z) control chart by using three different techniques (i) covariate method (ii) multiple measurements (iii) linearly increasing variance. The performance of EWMA-Z control chart is measured through ARL and SDRL by using Monte-Carlo simulation method. An example is provided with real data set for the implementation of EWMA-Z control chart in the presence of measurement error.