Joint monitoring of mean and variance under double ranked set sampling using likelihood ratio test statistic

Abstract

Quality control charts are widely used as a process monitoring tool. In this article, an attempt is made to develop a new control chart that integrates the exponentially weighted moving average procedure with the generalized likelihood ratio test statistic for joint monitoring of process mean and dispersion under double ranked set sampling. A Monte Carlo simulation study is conducted to evaluate the proposed control chart based on average run length and the standard deviation of the run length. The performance of the proposed chart is examined as compared to ranked set sampling (RSS) and pair ranked set sampling (PRSS) based control charts when detecting shifts in the process mean and variability. Results showed that the proposed control chart performs better than the existing RSS- and PRSS-based control chart in simultaneous detection of shifts in the process mean and variability. An application to the real data is provided to illustrate the implementations of the proposed and existing control charts.