Monitoring the process mean with an ATTRIVAR chart
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1080/03610926.2020.1828463 http://hdl.handle.net/11449/208026 |
Resumo: | In this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed. |
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Repositório Institucional da UNESP |
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Monitoring the process mean with an ATTRIVAR chartattribute/variable-type inspectionsATTRIVAR chartmixed chartprocess meanIn this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed.IEPG Federal University of Itajubá (UNIFEI)Engineering Electric Department São Paulo State University (UNESP)Engineering Electric Department São Paulo State University (UNESP)Federal University of Itajubá (UNIFEI)Universidade Estadual Paulista (Unesp)Costa, Antonio Fernando BrancoFaria Neto, Antonio [UNESP]2021-06-25T11:05:09Z2021-06-25T11:05:09Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1080/03610926.2020.1828463Communications in Statistics - Theory and Methods.1532-415X0361-0926http://hdl.handle.net/11449/20802610.1080/03610926.2020.18284632-s2.0-85092189125Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCommunications in Statistics - Theory and Methodsinfo:eu-repo/semantics/openAccess2024-07-01T20:12:21Zoai:repositorio.unesp.br:11449/208026Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:14:48.571836Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Monitoring the process mean with an ATTRIVAR chart |
title |
Monitoring the process mean with an ATTRIVAR chart |
spellingShingle |
Monitoring the process mean with an ATTRIVAR chart Costa, Antonio Fernando Branco attribute/variable-type inspections ATTRIVAR chart mixed chart process mean |
title_short |
Monitoring the process mean with an ATTRIVAR chart |
title_full |
Monitoring the process mean with an ATTRIVAR chart |
title_fullStr |
Monitoring the process mean with an ATTRIVAR chart |
title_full_unstemmed |
Monitoring the process mean with an ATTRIVAR chart |
title_sort |
Monitoring the process mean with an ATTRIVAR chart |
author |
Costa, Antonio Fernando Branco |
author_facet |
Costa, Antonio Fernando Branco Faria Neto, Antonio [UNESP] |
author_role |
author |
author2 |
Faria Neto, Antonio [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Federal University of Itajubá (UNIFEI) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Costa, Antonio Fernando Branco Faria Neto, Antonio [UNESP] |
dc.subject.por.fl_str_mv |
attribute/variable-type inspections ATTRIVAR chart mixed chart process mean |
topic |
attribute/variable-type inspections ATTRIVAR chart mixed chart process mean |
description |
In this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data–ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the no-go gauge test, the sampling moves on to stage two, where the quality characteristic X of the first m and the remaining n-m items of the sample is measured. Otherwise, the sampling is interrupted and the process is declared to be in control. The number of tested items, if one, or two, or as many as m, is only known after the completion of the first stage. At the second stage, the (Formula presented.) value is computed and used to decide the state of the process. It is worthwhile to stress that the go/no-go gauge test truncates the X distribution and, because of that, the mathematical development to obtain the (Formula presented.) distribution is not trivial. The ATTRIVAR chart signals faster than the Double Sampling (Formula presented.) chart and, more important than that, it is simpler to use because the go/no-go gauge test reduces the frequency with which the quality characteristic X of the sample items is measured. The ATTRIVAR chart is also faster and simpler than the mixed chart. With the mixed chart, the sampling is also performed in two stages; the difference is that all items of the sample are always submitted to the go/no-go gauge test before deciding to go to stage two, where the (Formula presented.) value is computed. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 2021-06-25T11:05:09Z 2021-06-25T11:05:09Z |
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/10.1080/03610926.2020.1828463 Communications in Statistics - Theory and Methods. 1532-415X 0361-0926 http://hdl.handle.net/11449/208026 10.1080/03610926.2020.1828463 2-s2.0-85092189125 |
url |
http://dx.doi.org/10.1080/03610926.2020.1828463 http://hdl.handle.net/11449/208026 |
identifier_str_mv |
Communications in Statistics - Theory and Methods. 1532-415X 0361-0926 10.1080/03610926.2020.1828463 2-s2.0-85092189125 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Communications in Statistics - Theory and Methods |
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 |
|
_version_ |
1808129408846790656 |