QUALITY CONTROL WITH MULTIVARIATE DATA

Ross Stewart Sparks

33 citations0/0 files storedAustralian Journal of Statistics

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

Abstract

Summary The paper examines statistical process control of bivariate and multivariate data, using in particular the multivariate equivalents of the univariate Shewhart chart, CUSUM chart and the Exponentially Weighted Moving Average chart. This illustrates the usefulness of Principal Component methods in statistical process control with multivariate data.

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References

1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements 1988Multivariate Generalizations of Cumulative Sum Quality-Control Schemes 1987A Simple Method for Studying Run – Length Distributions of Exponentially Weighted Moving Average Charts 1985Multivariate CUSUM Quality-Control Procedures 1987A Note on Multivariate CUSUM Procedures 1959Quality Control Methods for Several Related Variables 1957An Application of Multivariate Quality Control to Photographic Processing

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2019A survey on multivariate adaptive control charts: Recent developments and extensions 2006Multivariate statistical process control charts: an overview 1994STATISTICAL PROCESS CONTROL OF MULTIVARIATE PROCESSES 2005The state of conservation of painted surfaces in the presence of accelerated ageing processes monitored by use of FT-Raman spectroscopy and multivariate control charts 2020Monitoring and root-cause diagnostics of high-dimensional data streams 2017ARL Numerics for MEWMA Charts

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