An EWMA for Monitoring a Process Standard Deviation

Abstract

Most applications of the exponentially weighted moving average (EWMA) for process monitoring have concentrated on the problem of detecting shifts in the mean level of a process. Perhaps more important is the problem of detecting increases in process variability, which can also have a major impact on product quality. In this paper we propose using an EWMA based on the log transformation of the sample variance. Properties of this EWMA are given and an optimal design strategy is presented. It is shown that the EWMA is superior to the usual range chart or s² chart in terms of its ability to quickly detect small increases in the standard deviation of a normal process.

• Integral Equation
• Location Parameter
• Log-Gamma Distribution
• Scale Parameter

Additional information

Notes on contributors

Stephen V. Crowder

Dr. Crowder is a Senior Member of the Technical Staff in the Statistics, Computing, and Human Factors Division.

Marc D. Hamilton

Mr. Hamilton is a Consultant in the Manufacturing Management Division.