Two Charts: Not One

George E. P. Box · Carmen Paniagua-Quiñones

22 citations0/0 files storedQuality Engineering

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Advanced Statistical Process Monitoring Fault Detection and Control Systems Management Systems and Quality Improvement

Abstract

Difficulties can occur in the operation of traditional control charts. A principal reason for this is that the data coming from a typical operating process do not vary about a fixed mean. It is shown how by using a nonstationary model a continuously updated local mean level is provided. This can be used to produce (a) a bounded adjustment chart that tells you when to adjust the process to achieve maximum economy and (b) a Shewhart monitoring chart seeking assignable causes of trouble applied to the deviations from the local mean. Estimation of the mean and “standard deviation” are not required.

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References

1977Time Series Analysis: Forecasting and Control 1982Out of the Crisis 1977Time Series Analysis: Forecasting and Control 1971Time Series Analysis, Forecasting and Control.1960Optimal Properties of Exponentially Weighted Forecasts 1991Some Statistical Process Control Methods for Autocorrelated Data 1959Control Charts and Stochastic Processes 1997Statistical control by monitoring and feedback adjustment

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2011Nonstationarity in statistical process control — issues, cases, ideas 2008EWMA control chart limits for first‐ and second‐order autoregressive processes 2009Identifying the time of polynomial drift in the mean of autocorrelated processes 2009Identifying the time of step change in the mean of autocorrelated processes 2007Quality Quandaries: Using a Time Series Model for Process Adjustment and Control

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