Some aspects of the theory of statistical control schemes

Emmanuel Yashchin

84 citations0/0 files storedIBM Journal of Research and Development

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Advanced Statistical Process Monitoring Management and Optimization Techniques Fault Detection and Control Systems

Abstract

Control schemes (charts) are widely used in industrial quality control as means of monitoring the quality of manufactured products. These schemes provide a set of criteria for testing whether a given sequence of observations corresponds to an “on-target” state of the production process. In the present work, we consider some graphical, computational, and statistical aspects of control charting—criteria of performance, methods of derivation, analysis, design, etc. We introduce the class of “Markov-type” control schemes and discuss some of its properties.

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References

1971Procedures for Reacting to a Change in Distribution 2000Control Chart Tests Based on Geometric Moving Averages 1986The Exponentially Weighted Moving Average 1972An Approach to the Probability Distribution of Cusum Run Length 1970Inference About the Change-Point in a Sequence of Random Variables 1956The Economic Design of X Charts Used to Maintain Current Control of a Process 1986The Economic Design of Control Charts: A Unified Approach 1966A Comparison of Some Control Chart Procedures

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2018Optimal design of the adaptive EWMA chart for the mean based on median run length and expected median run length 1989Weighted Cumulative Sum Technique 2001MULTIVARIATE CUMULATIVE SUM CONTROL CHARTS BASED ON PROJECTION PURSUIT 2004Joint statistical design of double sampling and s charts 2010A Multivariate Adaptive Exponentially Weighted Moving Average Control Chart 2018The effect of measurement errors on the adaptive EWMA chart

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