A new cumulative sum quality control scheme for monitoring the process mean

Abstract

A control chart is a powerful statistical process monitoring tool that is frequently used in many industrial and s ervice organizations to monitor in-control and out-of-control performances of the manufacturing processes. Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts have been recognized as potentially powerful tool in quality and management control. These control charts are sensitive to both small and moderate changes in the process. In this paper, we propose a new CUSUM (NCUSUM) quality control scheme for efficiently monitoring the process mean. It is shown that the classical CUSUM control chart is a special case of the proposed controlling scheme. The NCUSUM control chart is compared with some of the recently proposed control charts by using characteristics of the distribution of run length, i.e. average run length, median run length and standard deviation of run length. It is worth mentioning that the NCUSUM control chart detects the random shifts in the process mean substantially quicker than the classical CUSUM, fast initial response-based CUSUM, adaptive CUSUM with EWMA-based shift, adaptive EWMA and Shewhart-CUSUM control charts. An illustrative example is given to exemplify the implementation of the proposed quality control scheme.