The CUSUM and the EWMA Head-to-Head

Douglas M. Hawkins · Qifan Wu

76 citations0/0 files storedQuality Engineering

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

Abstract

The cumulative sum (CUSUM) and the exponentially weighted moving average (EWMA) control charts are alternatives to the Xbar chart. The CUSUM's theoretical optimality suggests that it should outperform the EWMA for detecting persistent shifts, but practitioners have long thought that the two perform about equally. Each also involves design decisions on the likely shift in the process. This article quantifies the effect of these choices and concludes that, though the CUSUM outperforms the EWMA at the shift for which each was designed, if the actual shift is smaller than that used in the design, the EWMA may respond faster.

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References

1992Introduction to Statistical Quality Control 1990Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements 1998Cumulative Sum Charts and Charting for Quality Improvement 2000Statistical Methods for Quality Improvement 2000Controversies and Contradictions in Statistical Process Control 1987Exact Results for Shewhart Control Charts With Supplementary Runs Rules 1982Combined Shewhart-CUSUM Quality Control Schemes 2003An Adaptive Exponentially Weighted Moving Average Control Chart

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2016The efficiency of CUSUM schemes for monitoring the coefficient of variation 2016Monitoring the ratio of population means of a bivariate normal distribution using CUSUM type control charts 2019An EWMA control chart for categorical processes with applications to social network monitoring 2018A modified CUSUM control chart for monitoring industrial processes 2020On the design of control charts with guaranteed conditional performance under estimated parameters

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