An Efficient Dispersion Control Chart

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 170)


Control chart is the most important Statistical Process Control tool used to monitor reliability and performance of industrial processes. For monitoring process dispersion, \(R\) and \(S\) charts are widely used. These control charts perform better under the ideal assumption of normality but are well known to be very inefficient in presence of outliers or departures from normality. In this study we propose a new control chart for monitoring process dispersion, namely the \(D\) chart, and compared its performance with \(R\) and \(S\) charts using probability to signal as a performance measure. It has been observed that the newly proposed chart is superior to \(R\) chart and is a close competitor to S chart under normality of quality characteristic. When the assumption of normality is violated, \(D\) chart is more powerful than both \(R\) and \(S\) charts. This study will help quality practitioners to choose an efficient and robust alternative to \(R\) and \(S\) charts for monitoring dispersion of industrial processes.


Control Chart Monte Carlo Simulations Non-Normality Probability to Signal Process Dispersion Process Monitoring 


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of StatisticsThe University of AucklandAucklandNew Zealand

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