CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Operations & Production Management (Online) |
Texto Completo: | https://bjopm.org.br/bjopm/article/view/V12N2A4 |
Resumo: | Process capability analysis is extremely important for optimization and quality improvement. It verifies whether the process under analysis is capable of producing items within engineering and customers’ specifications. The use of capability indices when assumptions are not satisfied leads to erroneous conclusions, compromising the study and analysis of the process, jeopardizing the fulfillment of requirements from management or external customers. Aiming at filling a gap identified in the literature, the main contributions of this work are: (i) proposition of capability indices for processes monitored through control charts based on regression models, for symmetric and asymmetric specifications; and (ii) comparison of the proposed indices with traditional capability indices through a simulated process. |
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Brazilian Journal of Operations & Production Management (Online) |
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CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELSProcess controlRegression modelsCapability indicesProcess capability analysis is extremely important for optimization and quality improvement. It verifies whether the process under analysis is capable of producing items within engineering and customers’ specifications. The use of capability indices when assumptions are not satisfied leads to erroneous conclusions, compromising the study and analysis of the process, jeopardizing the fulfillment of requirements from management or external customers. Aiming at filling a gap identified in the literature, the main contributions of this work are: (i) proposition of capability indices for processes monitored through control charts based on regression models, for symmetric and asymmetric specifications; and (ii) comparison of the proposed indices with traditional capability indices through a simulated process.Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2015-12-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://bjopm.org.br/bjopm/article/view/V12N2A410.14488/BJOPM.2015.v12.n2.a4Brazilian Journal of Operations & Production Management; Vol. 12 No. 2 (2015): December, 2015; 234-2472237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/V12N2A4/BJOPMV12N2A4http://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSouza, Fernanda SiqueiraPedrini, Danilo Cuzzuolten Caten, Carla Schwengber2022-11-28T20:28:28Zoai:ojs.bjopm.org.br:article/192Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2023-03-13T09:45:07.382363Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
title |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
spellingShingle |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS Souza, Fernanda Siqueira Process control Regression models Capability indices |
title_short |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
title_full |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
title_fullStr |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
title_full_unstemmed |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
title_sort |
CAPABILITY INDICES FOR CONTROL CHARTS BASED ON REGRESSION MODELS |
author |
Souza, Fernanda Siqueira |
author_facet |
Souza, Fernanda Siqueira Pedrini, Danilo Cuzzuol ten Caten, Carla Schwengber |
author_role |
author |
author2 |
Pedrini, Danilo Cuzzuol ten Caten, Carla Schwengber |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Souza, Fernanda Siqueira Pedrini, Danilo Cuzzuol ten Caten, Carla Schwengber |
dc.subject.por.fl_str_mv |
Process control Regression models Capability indices |
topic |
Process control Regression models Capability indices |
description |
Process capability analysis is extremely important for optimization and quality improvement. It verifies whether the process under analysis is capable of producing items within engineering and customers’ specifications. The use of capability indices when assumptions are not satisfied leads to erroneous conclusions, compromising the study and analysis of the process, jeopardizing the fulfillment of requirements from management or external customers. Aiming at filling a gap identified in the literature, the main contributions of this work are: (i) proposition of capability indices for processes monitored through control charts based on regression models, for symmetric and asymmetric specifications; and (ii) comparison of the proposed indices with traditional capability indices through a simulated process. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12-28 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://bjopm.org.br/bjopm/article/view/V12N2A4 10.14488/BJOPM.2015.v12.n2.a4 |
url |
https://bjopm.org.br/bjopm/article/view/V12N2A4 |
identifier_str_mv |
10.14488/BJOPM.2015.v12.n2.a4 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://bjopm.org.br/bjopm/article/view/V12N2A4/BJOPMV12N2A4 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Brazilian Association for Industrial Engineering and Operations Management (ABEPRO) |
publisher.none.fl_str_mv |
Brazilian Association for Industrial Engineering and Operations Management (ABEPRO) |
dc.source.none.fl_str_mv |
Brazilian Journal of Operations & Production Management; Vol. 12 No. 2 (2015): December, 2015; 234-247 2237-8960 reponame:Brazilian Journal of Operations & Production Management (Online) instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Brazilian Journal of Operations & Production Management (Online) |
collection |
Brazilian Journal of Operations & Production Management (Online) |
repository.name.fl_str_mv |
Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
bjopm.journal@gmail.com |
_version_ |
1797051460069883904 |