The Average Run Length Performance of a Multivariate Exponentially Weighted Moving Average Control Chart Procedure with Application

Abstract

One of the most powerful tools in quality control is the statistical control chart. First developed in the 1920's by Walter Shewhart, the control chart found widespread use during World War II and has been employed, with various modifications ever since. The drawbacks to multivariate charting schemes is their inability to identify which variable was the source of the signal. The multivariate exponentially weighted moving average (MEWMA) developed by Lowry, et al (1992) is an example of a multivariate charting scheme whose monitoring statistic is unable to determine which variable caused the signal. In this paper, the run length performance of multivariate exponentially weighted moving average (MEWMA) chart with application is studied. Industry fertilizers is important one of the chemical industries in Egypt, so that this work concerns the fertilizers industries quality control, especially urea fertilizer with application on Delta fertilizer and chemical industries which is considered on of the leading companies the field of fertilizer production in Middle east with application of multivariate quality control procedures to achieve best one procedure for multivariate quality control.