Multivariate control charts for process dispersion

Johan Surtihadi · Madabhushi Raghavachari · George C. Runger

35 citations0/0 files storedInternational Journal of Production Research

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Advanced Statistical Process Monitoring Statistical Methods and Applications Fault Detection and Control Systems

Abstract

The multivariate extension of control charts for process dispersion is not as straightforward as that for the process mean. A general model and techniques that would encompass a wide range of problems encountered in practice is not available. In most cases, particular problems need to be handled in a specific manner. In this paper we consider several special cases of a process displacement affecting the covariance matrix and we develop control charts (both Shewhart-type and CUSUM) to detect these process changes.

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References

1992Introduction to Statistical Quality Control 1991Multivariate Quality Control Based on Regression-Adjusted Variables 1993Regression Adjustment for Variables in Multivariate Quality Control 1987A Note on Multivariate CUSUM Procedures 1987Self-Starting Cusum Charts for Location and Scale 1990Statistical Methods for Quality Improvement 1981A Cusum for a Scale Parameter 2023Georgia Institute of Technology

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2010Using neural networks to detect the bivariate process variance shifts pattern 2008A New Chart for Monitoring the Covariance Matrix of Bivariate Processes 2006Multivariate Control Charts Based on Bayesian State Space Models 2006Multivariate statistical process control charts: an overview 2008The use of principal components and univariate charts to control multivariate processes 2009Control charts for variables to monitor the process mean and dispersion: a literature review

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