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Cited by 374

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

An Adaptive Exponentially Weighted Moving Average Control Chart

Open access
Capizzi, Giovanna, Masarotto, Guido·2003·Technometrics

Abstract

Lucas and Saccucci showed that exponentially weighted moving average (EWMA) control charts can be designed to quickly detect either small or large shifts in the mean of a sequence of independent observations. But a single EWMA chart cannot perform well for small and large shifts simultaneously. Furthermore, in the worst-case situation, this scheme requires a few observations to overcome its initial inertia. The main goal of this article is to suggest an adaptive EWMA (AEWMA) chart that weights the past observations of the monitored process using a suitable function of the current “error.” The resulting scheme can be viewed as a smooth combination of a Shewhart chart and an EWMA chart. A design procedure for the new control schemes is suggested. Comparisons of the standard and worst-case average run length profiles of the new scheme with those of different control charts show that AEWMA schemes offer a more balanced protection against shifts of different sizes.

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Crossref · 10.1198/004017003000000023

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Metadata

Authors
Capizzi, G., & Masarotto, G.
Venue
Technometrics
Published
2003-08
Volume
45
Issue
3
Pages
199-207
ISSN
  • 0040-1706 (ISSN-L)
  • 1537-2723
OpenAlex
W625317573
Cited by
374
References
8
FWCI
3.16
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: An Adaptive Exponentially Weighted Moving Average Control Chart. https://app.cochat.ai/papers/10.1198/004017003000000023
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Capizzi, G., & Masarotto, G. (2003). An Adaptive Exponentially Weighted Moving Average Control Chart. Technometrics. https://doi.org/10.1198/004017003000000023

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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