ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY

This work is a simulation study to investigate the sensitivity of multivariate control charts for monitoring mean vectors in a bivariate Gaussian process with individual observations. The multivariate cumulative sum (MCUSUM), the multivariate exponentially weighted moving average (MEWMA) and Hotelli...

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Main Authors: D. A. O. Moraes, F. L. P. Oliveira, L. H. Duczmal
Format: Article
Language:English
Published: Associação Brasileira de Engenharia de Produção (ABEPRO) 2015-12-01
Series:Brazilian Journal of Operations & Production Management
Subjects:
Online Access:https://bjopm.emnuvens.com.br/bjopm/article/view/172
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spelling doaj-a90b481845d54d16828a49c9f6bcbae02020-11-24T21:35:54ZengAssociação Brasileira de Engenharia de Produção (ABEPRO)Brazilian Journal of Operations & Production Management2237-89602015-12-0112210.14488/BJOPM.2015.v12.n2.a2ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDYD. A. O. Moraes0F. L. P. Oliveira1L. H. Duczmal2Universidade Federal de Santa MariaUFOP - UFVUFMGThis work is a simulation study to investigate the sensitivity of multivariate control charts for monitoring mean vectors in a bivariate Gaussian process with individual observations. The multivariate cumulative sum (MCUSUM), the multivariate exponentially weighted moving average (MEWMA) and Hotelling’s T charts are selected for analysis due to their common dependency on the noncentrality parameter. The chart performance is evaluated through the average run length (ARL) or the average time to signal. The impact of utilising in-control limits computed from known parameters or Phase I sample estimates is considered for mean vector shifts. Although designed to monitor mean vectors, the sensibility of the control charts is additionally analysed through different variability sources, including the mixing effect of mean vector shifts with increasing variances or positive autocorrelation in the out-of-control process.  https://bjopm.emnuvens.com.br/bjopm/article/view/172quality controlmean vectorsnoncentrality parameteraverage run lengthincreasing variancesincreasing autocorrelations
collection DOAJ
language English
format Article
sources DOAJ
author D. A. O. Moraes
F. L. P. Oliveira
L. H. Duczmal
spellingShingle D. A. O. Moraes
F. L. P. Oliveira
L. H. Duczmal
ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
Brazilian Journal of Operations & Production Management
quality control
mean vectors
noncentrality parameter
average run length
increasing variances
increasing autocorrelations
author_facet D. A. O. Moraes
F. L. P. Oliveira
L. H. Duczmal
author_sort D. A. O. Moraes
title ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
title_short ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
title_full ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
title_fullStr ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
title_full_unstemmed ON THE HOTELLING’S T, MCUSUM AND MEWMA CONTROL CHARTS' PERFORMANCE WITH DIFFERENT VARISBILITY SOURCES: A SIMULATION STUDY
title_sort on the hotelling’s t, mcusum and mewma control charts' performance with different varisbility sources: a simulation study
publisher Associação Brasileira de Engenharia de Produção (ABEPRO)
series Brazilian Journal of Operations & Production Management
issn 2237-8960
publishDate 2015-12-01
description This work is a simulation study to investigate the sensitivity of multivariate control charts for monitoring mean vectors in a bivariate Gaussian process with individual observations. The multivariate cumulative sum (MCUSUM), the multivariate exponentially weighted moving average (MEWMA) and Hotelling’s T charts are selected for analysis due to their common dependency on the noncentrality parameter. The chart performance is evaluated through the average run length (ARL) or the average time to signal. The impact of utilising in-control limits computed from known parameters or Phase I sample estimates is considered for mean vector shifts. Although designed to monitor mean vectors, the sensibility of the control charts is additionally analysed through different variability sources, including the mixing effect of mean vector shifts with increasing variances or positive autocorrelation in the out-of-control process. 
topic quality control
mean vectors
noncentrality parameter
average run length
increasing variances
increasing autocorrelations
url https://bjopm.emnuvens.com.br/bjopm/article/view/172
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AT lhduczmal onthehotellingstmcusumandmewmacontrolchartsperformancewithdifferentvarisbilitysourcesasimulationstudy
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