The Max EWMAMS control chart for joint monitoring of process mean and variance with individual observations

Ahmad Ostadsharif Memar · Seyed Taghi Akhavan Niaki

32 citations0/0 files storedQuality and Reliability Engineering International

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Management Systems and Quality Improvement

Abstract

Abstract A traditional approach to monitor both the location and the scale parameters of a quality characteristic is to use two separate control charts. These schemes have some difficulties in concurrent tracking and interpretation. To overcome these difficulties, some researchers have proposed schemes consisting of only one chart. However, none of these schemes is designed to work with individual observations. In this research, an exponentially weighted moving average (EWMA)‐based control chart that plots only one statistic at a time is proposed to simultaneously monitor the mean and variability with individual observations. The performance of the proposed scheme is compared with one of the two other existing combination charts by simulation. The results show that in general the proposed chart has a significantly better performance than the other combination charts. Copyright © 2010 John Wiley & Sons, Ltd.

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References

1992Introduction to Statistical Quality Control 2005Introduction to Statistical Quality Control 2001Monitoring Process Mean and Variability with One EWMA Chart 1993The Exponentially Weighted Moving Variance 1991Some Omnibus Exponentially Weighted Moving Average Statistical Process Monitoring Schemes 2001Monitoring the Process Mean and Variance Using Individual Observations and Variable Sampling Intervals 2004Control Charts and the Efficient Allocation of Sampling Resources 2004Should Observations Be Grouped for Effective Process Monitoring?

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