Monitoring bivariate processes with synthetic control charts based on sample ranges
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/1806-9649-2022v29e6822 http://hdl.handle.net/11449/248952 |
Resumo: | The RMAX chart was proposed to control the covariance matrix of two quality characteristics. The monitoring statistic of the RMAX chart is the maximum of two standardized sample ranges from bivariate observations of two quality characteristics. In this article, we investigate the performance of two synthetic RMAX charts. The first synthetic chart signals when a second point, not far from the first one, falls beyond the warning limit. The second synthetic chart additionally signals when a sample point falls beyond the control limit. The performance of the synthetic RMAX charts are compared with the performance of the standard RMAX chart and the generalized variance |S| chart. The proposed charts are the best option to detect moderate or even small changes in the covariance matrix. To detect large changes in the covariance matrix, additional run rules are not necessary. |
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Repositório Institucional da UNESP |
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Monitoring bivariate processes with synthetic control charts based on sample rangesGráficos de controle baseado em amplitudes amostrais e regras especiais de decisão para o monitoramento de processos bivariadosBivariate processesRMAX chartSynthetic run rulesThe RMAX chart was proposed to control the covariance matrix of two quality characteristics. The monitoring statistic of the RMAX chart is the maximum of two standardized sample ranges from bivariate observations of two quality characteristics. In this article, we investigate the performance of two synthetic RMAX charts. The first synthetic chart signals when a second point, not far from the first one, falls beyond the warning limit. The second synthetic chart additionally signals when a sample point falls beyond the control limit. The performance of the synthetic RMAX charts are compared with the performance of the standard RMAX chart and the generalized variance |S| chart. The proposed charts are the best option to detect moderate or even small changes in the covariance matrix. To detect large changes in the covariance matrix, additional run rules are not necessary.Universidade Estadual Paulista - UNESP Faculdade de Engenharia e Ciências - FEG Departamento de Produção, SPUniversidade Federal de Itajubá - UNIFEI Instituto de Engenharia de Produção e Gestão - IEPG, MGUniversidade Estadual Paulista - UNESP Faculdade de Engenharia e Ciências - FEG Departamento de Produção, SPUniversidade Estadual Paulista (UNESP)Instituto de Engenharia de Produção e Gestão - IEPGMacHado, Marcela [UNESP]Costa, AntonioSimões, Felipe Domingues [UNESP]2023-07-29T13:58:17Z2023-07-29T13:58:17Z2023-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1590/1806-9649-2022v29e6822Gestao e Producao, v. 30.1806-96490104-530Xhttp://hdl.handle.net/11449/24895210.1590/1806-9649-2022v29e68222-s2.0-85161291584Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengGestao e Producaoinfo:eu-repo/semantics/openAccess2024-07-02T17:37:20Zoai:repositorio.unesp.br:11449/248952Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462024-07-02T17:37:20Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Monitoring bivariate processes with synthetic control charts based on sample ranges Gráficos de controle baseado em amplitudes amostrais e regras especiais de decisão para o monitoramento de processos bivariados |
title |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
spellingShingle |
Monitoring bivariate processes with synthetic control charts based on sample ranges MacHado, Marcela [UNESP] Bivariate processes RMAX chart Synthetic run rules |
title_short |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
title_full |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
title_fullStr |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
title_full_unstemmed |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
title_sort |
Monitoring bivariate processes with synthetic control charts based on sample ranges |
author |
MacHado, Marcela [UNESP] |
author_facet |
MacHado, Marcela [UNESP] Costa, Antonio Simões, Felipe Domingues [UNESP] |
author_role |
author |
author2 |
Costa, Antonio Simões, Felipe Domingues [UNESP] |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Instituto de Engenharia de Produção e Gestão - IEPG |
dc.contributor.author.fl_str_mv |
MacHado, Marcela [UNESP] Costa, Antonio Simões, Felipe Domingues [UNESP] |
dc.subject.por.fl_str_mv |
Bivariate processes RMAX chart Synthetic run rules |
topic |
Bivariate processes RMAX chart Synthetic run rules |
description |
The RMAX chart was proposed to control the covariance matrix of two quality characteristics. The monitoring statistic of the RMAX chart is the maximum of two standardized sample ranges from bivariate observations of two quality characteristics. In this article, we investigate the performance of two synthetic RMAX charts. The first synthetic chart signals when a second point, not far from the first one, falls beyond the warning limit. The second synthetic chart additionally signals when a sample point falls beyond the control limit. The performance of the synthetic RMAX charts are compared with the performance of the standard RMAX chart and the generalized variance |S| chart. The proposed charts are the best option to detect moderate or even small changes in the covariance matrix. To detect large changes in the covariance matrix, additional run rules are not necessary. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T13:58:17Z 2023-07-29T13:58:17Z 2023-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1590/1806-9649-2022v29e6822 Gestao e Producao, v. 30. 1806-9649 0104-530X http://hdl.handle.net/11449/248952 10.1590/1806-9649-2022v29e6822 2-s2.0-85161291584 |
url |
http://dx.doi.org/10.1590/1806-9649-2022v29e6822 http://hdl.handle.net/11449/248952 |
identifier_str_mv |
Gestao e Producao, v. 30. 1806-9649 0104-530X 10.1590/1806-9649-2022v29e6822 2-s2.0-85161291584 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Gestao e Producao |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
repositoriounesp@unesp.br |
_version_ |
1826304679120732160 |