Designing a Multivariate EWMA Control Chart

Sharad S. Prabhu · George C. Runger

228 citations0/0 files storedJournal of Quality Technology

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Advanced Statistical Process Monitoring Probability and Statistical Research Fault Detection and Control Systems

Abstract

A multivariate exponentially weighted moving average control chart can be used to improve the detection of small shifts in multivariate statistical process control. Recommendations are provided for the selection of parameters for such a chart. The recommendations are based on performance distributions and average run lengths for zero-state, steady-state, and worst-state cases that are obtained from a Markov chain analysis of the scheme.

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References

1954CONTINUOUS INSPECTION SCHEMES 1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements 1959Control Chart Tests Based on Geometric Moving Averages 1992A Multivariate Exponentially Weighted Moving Average Control Chart 1972An Approach to the Probability Distribution of Cusum Run Length 1988Multivariate Generalizations of Cumulative Sum Quality-Control Schemes 1990Comparisons of MultivariateCUSUMCharts 1993Regression Adjustment for Variables in Multivariate Quality Control

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2009Multivariate Statistical Process Control Using LASSO 2002Robustness to Non-Normality of the Multivariate EWMA Control Chart 2011A Multivariate Sign EWMA Control Chart 2013Multivariate Quality Control 2008Control chart based on likelihood ratio for monitoring linear profiles 2003Computer intrusion detection through EWMA for autocorrelated and uncorrelated data

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