A novel procedure to improve traditional EWMA control chart performance in detecting both small and large shifts

Different control charts are proposed by many researchers for the aim of detecting process shifts in the mean and assuring quality of the product. Exponentially weighted moving average (EWMA) control charts is one of the famous charts which performs well in detecting small shifts in the process mean. In this paper, a new statistic based on different smoothing parameters is proposed to improve the performance of the exponentially weighted moving average (EWMA) control chart in detecting large shifts as well as small and medium shifts. The performance of the developed scheme based on the proposed smoothing parameter is evaluated in terms of average run length criterion in comparison with the traditional EWMA control chart. The results show the better performance of the proposed scheme rather than the traditional EWMA control charts in most cases.