Th e Non-Central Chi-Square Chart with Double Sampling
Autor(a) principal: | |
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Data de Publicação: | 2010 |
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/BJV2N2_2005_P2 |
Resumo: | In this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not. |
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Brazilian Journal of Operations & Production Management (Online) |
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Th e Non-Central Chi-Square Chart with Double SamplingIn this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not.Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2010-02-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2Brazilian Journal of Operations & Production Management; Vol. 2 No. 2 (2005): December, 2005; 21-382237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2/pdf_32Costa, Antonio F. B.Magalhães, Maysa S. deEpprecht, Eugenio K.info:eu-repo/semantics/openAccess2019-04-04T07:29:08Zoai:ojs.bjopm.org.br:article/35Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2023-03-13T09:45:01.300169Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
Th e Non-Central Chi-Square Chart with Double Sampling |
title |
Th e Non-Central Chi-Square Chart with Double Sampling |
spellingShingle |
Th e Non-Central Chi-Square Chart with Double Sampling Costa, Antonio F. B. |
title_short |
Th e Non-Central Chi-Square Chart with Double Sampling |
title_full |
Th e Non-Central Chi-Square Chart with Double Sampling |
title_fullStr |
Th e Non-Central Chi-Square Chart with Double Sampling |
title_full_unstemmed |
Th e Non-Central Chi-Square Chart with Double Sampling |
title_sort |
Th e Non-Central Chi-Square Chart with Double Sampling |
author |
Costa, Antonio F. B. |
author_facet |
Costa, Antonio F. B. Magalhães, Maysa S. de Epprecht, Eugenio K. |
author_role |
author |
author2 |
Magalhães, Maysa S. de Epprecht, Eugenio K. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Costa, Antonio F. B. Magalhães, Maysa S. de Epprecht, Eugenio K. |
description |
In this article, we consider a non-central chi-square chart with double sampling (DS χ2 chart) to control the process mean and variance. As in the case of Shewhart control charts, samples of fi xed size are taken from the process at regular time intervals; however, the sampling is performed in two stages. Let X be the process quality variable being measured. During the fi rst stage, one item of the sample is inspected; if its X value is closeto the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and anon-central chi-square statistic, say T, is computed taking into account all n items of the sample, that is, their X values. A signal is triggered when the sample point given by theT value falls above the upper control limit of the proposed chart. The DS χ2 chart performs better than the joint X and R charts, except when there is a large change in the process mean. Furthermore, if the DS χ2 chart is used for monitoring diameters, volumes, weights, etc., then the employment of appropriate devices, such as go-no-go gauges can reduce the effort to decide if the sampling should go to the second stage or not. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-02-08 |
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/BJV2N2_2005_P2 |
url |
https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://bjopm.org.br/bjopm/article/view/BJV2N2_2005_P2/pdf_32 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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. 2 No. 2 (2005): December, 2005; 21-38 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_ |
1797051459577053184 |