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  • Rauber_etal_2022

    Rights statement: This is the peer reviewed version of the following article: Rauber, C, Lima-Filho, LA, Bayer, Fábio~M. Residual-based CUSUM beta regression control chart for monitoring double-bounded processes. Qual Reliab Eng Int. 2022; 1– 18. https://doi.org/10.1002/qre.3140 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/qre.3140 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

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Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes. / Rauber, Cristine; Lima‐Filho, Luiz M. A.; Bayer, Fábio M.
In: Quality and Reliability Engineering International, Vol. 38, No. 6, 31.10.2022, p. 3252-3269.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Rauber, C, Lima‐Filho, LMA & Bayer, FM 2022, 'Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes', Quality and Reliability Engineering International, vol. 38, no. 6, pp. 3252-3269. https://doi.org/10.1002/qre.3140

APA

Rauber, C., Lima‐Filho, L. M. A., & Bayer, F. M. (2022). Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes. Quality and Reliability Engineering International, 38(6), 3252-3269. https://doi.org/10.1002/qre.3140

Vancouver

Rauber C, Lima‐Filho LMA, Bayer FM. Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes. Quality and Reliability Engineering International. 2022 Oct 31;38(6):3252-3269. Epub 2022 May 27. doi: 10.1002/qre.3140

Author

Rauber, Cristine ; Lima‐Filho, Luiz M. A. ; Bayer, Fábio M. / Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes. In: Quality and Reliability Engineering International. 2022 ; Vol. 38, No. 6. pp. 3252-3269.

Bibtex

@article{41f188c5292d4bebb888f019a41dea5f,
title = "Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes",
abstract = "This paper proposes a control chart useful for detecting small shifts in the mean of a double-bounded process, such as fractions and proportions, in the presence of control variables. For this purpose, we consider the cumulative sum (CUSUM) control chart applied to different residuals of the beta regression model. We conduct an extensive Monte Carlo simulation study to evaluate and compare the performance of the proposed control chart with two other control charts in the literature in terms of run length analysis. The numerical results show that the proposed control chart is more sensitive to detect changes in the process than its competitors and that the quantile residual is the most suitable residual to be used in our proposal. Finally, based on the quantile residual, we present and discuss applications to real and simulated data to show the applicability of the proposed control chart.",
keywords = "Management Science and Operations Research, Safety, Risk, Reliability and Quality",
author = "Cristine Rauber and Lima‐Filho, {Luiz M. A.} and Bayer, {F{\'a}bio M.}",
note = "This is the peer reviewed version of the following article: Rauber, C, Lima-Filho, LA, Bayer, F{\'a}bio~M. Residual-based CUSUM beta regression control chart for monitoring double-bounded processes. Qual Reliab Eng Int. 2022; 1– 18. https://doi.org/10.1002/qre.3140 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/qre.3140 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.",
year = "2022",
month = oct,
day = "31",
doi = "10.1002/qre.3140",
language = "English",
volume = "38",
pages = "3252--3269",
journal = "Quality and Reliability Engineering International",
issn = "0748-8017",
publisher = "John Wiley and Sons Ltd",
number = "6",

}

RIS

TY - JOUR

T1 - Residual‐based CUSUM beta regression control chart for monitoring double‐bounded processes

AU - Rauber, Cristine

AU - Lima‐Filho, Luiz M. A.

AU - Bayer, Fábio M.

N1 - This is the peer reviewed version of the following article: Rauber, C, Lima-Filho, LA, Bayer, Fábio~M. Residual-based CUSUM beta regression control chart for monitoring double-bounded processes. Qual Reliab Eng Int. 2022; 1– 18. https://doi.org/10.1002/qre.3140 which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/qre.3140 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2022/10/31

Y1 - 2022/10/31

N2 - This paper proposes a control chart useful for detecting small shifts in the mean of a double-bounded process, such as fractions and proportions, in the presence of control variables. For this purpose, we consider the cumulative sum (CUSUM) control chart applied to different residuals of the beta regression model. We conduct an extensive Monte Carlo simulation study to evaluate and compare the performance of the proposed control chart with two other control charts in the literature in terms of run length analysis. The numerical results show that the proposed control chart is more sensitive to detect changes in the process than its competitors and that the quantile residual is the most suitable residual to be used in our proposal. Finally, based on the quantile residual, we present and discuss applications to real and simulated data to show the applicability of the proposed control chart.

AB - This paper proposes a control chart useful for detecting small shifts in the mean of a double-bounded process, such as fractions and proportions, in the presence of control variables. For this purpose, we consider the cumulative sum (CUSUM) control chart applied to different residuals of the beta regression model. We conduct an extensive Monte Carlo simulation study to evaluate and compare the performance of the proposed control chart with two other control charts in the literature in terms of run length analysis. The numerical results show that the proposed control chart is more sensitive to detect changes in the process than its competitors and that the quantile residual is the most suitable residual to be used in our proposal. Finally, based on the quantile residual, we present and discuss applications to real and simulated data to show the applicability of the proposed control chart.

KW - Management Science and Operations Research

KW - Safety, Risk, Reliability and Quality

U2 - 10.1002/qre.3140

DO - 10.1002/qre.3140

M3 - Journal article

VL - 38

SP - 3252

EP - 3269

JO - Quality and Reliability Engineering International

JF - Quality and Reliability Engineering International

SN - 0748-8017

IS - 6

ER -