Effect of measurement errors on double sampling S² control chart
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Tese |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/18116 |
Resumo: | Product quality can be understood as inversely proportional to the variability in its production process. The control chart is a well-established statistical tool for quantifying and analyzing this process' variability based on observed information about some of its measurable characteristics. To simplify the control chart application, some researchers and users assume that the data used to evaluate the process is accurate. However, since the construction and use of control charts are based on measurement and no measurement system is perfect, errors in the measured data are inevitable. Recent studies indicate that the Double Sampling control chart can be an alternative for process monitoring. However, there is still a lack of studies that investigate the impact of measurement errors on Double Sampling control chart to monitor process variability. Based on the preceding, the present work aims to study how the performance of the Double Sampling S² control chart is affected by the presence of measurement errors. Initially, a systematic review of the literature is proposed in order to explore studies on the subject. The main methodology of the research is mathematical modeling and simulation. A design modeling for considering measurement errors in the Double Sampling S² control chart is proposed. The impact on the average run length (ARL) for different measurement error values is verified through simulation. Using a genetic algorithm, we propose an optimization study of the Double Sampling S² control chart for operation with measurement errors. Finally, a simulation example is presented to verify using the Double Sampling S² chart with the optimized parameters. The results indicate that measurement error deteriorates the performance of the Double Sampling S² chart, and the impact rises as measurement error increases. The simulation analysis showed the advantage of using the optimized Double Sampling S² chart, particularly for larger measurement errors. The present study contributes to the practical application knowledge of the Double Sampling S² control chart, providing parameters for its use in the presence of measurement errors. |
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Couto, Giselle EliasOprime, Pedro Carloshttp://lattes.cnpq.br/9291517431456908http://lattes.cnpq.br/3061782528251400https://orcid.org/0000-0001-9248-6447https://orcid.org/0000-0002-6213-222387490df3-0732-44de-859d-e3a7c0df48982023-06-07T13:06:14Z2023-06-07T13:06:14Z2023-06-02COUTO, Giselle Elias. Effect of measurement errors on double sampling S² control chart. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de São Carlos, São Carlos, 2023. Disponível em: https://repositorio.ufscar.br/handle/ufscar/18116.https://repositorio.ufscar.br/handle/ufscar/18116Product quality can be understood as inversely proportional to the variability in its production process. The control chart is a well-established statistical tool for quantifying and analyzing this process' variability based on observed information about some of its measurable characteristics. To simplify the control chart application, some researchers and users assume that the data used to evaluate the process is accurate. However, since the construction and use of control charts are based on measurement and no measurement system is perfect, errors in the measured data are inevitable. Recent studies indicate that the Double Sampling control chart can be an alternative for process monitoring. However, there is still a lack of studies that investigate the impact of measurement errors on Double Sampling control chart to monitor process variability. Based on the preceding, the present work aims to study how the performance of the Double Sampling S² control chart is affected by the presence of measurement errors. Initially, a systematic review of the literature is proposed in order to explore studies on the subject. The main methodology of the research is mathematical modeling and simulation. A design modeling for considering measurement errors in the Double Sampling S² control chart is proposed. The impact on the average run length (ARL) for different measurement error values is verified through simulation. Using a genetic algorithm, we propose an optimization study of the Double Sampling S² control chart for operation with measurement errors. Finally, a simulation example is presented to verify using the Double Sampling S² chart with the optimized parameters. The results indicate that measurement error deteriorates the performance of the Double Sampling S² chart, and the impact rises as measurement error increases. The simulation analysis showed the advantage of using the optimized Double Sampling S² chart, particularly for larger measurement errors. The present study contributes to the practical application knowledge of the Double Sampling S² control chart, providing parameters for its use in the presence of measurement errors.A qualidade de um produto pode ser entendida como inversamente proporcional à variabilidade presente em seu processo produtivo. Nesse sentido, o gráfico de controle é uma ferramenta estatística bem estabelecida para quantificar e analisar a variabilidade de um processo com base em informações observadas sobre algumas de suas características mensuráveis. Para simplificar a aplicação dos gráficos de controle, alguns pesquisadores e usuários assumem que os dados usados para avaliar o processo são exatos. No entanto, visto que a construção e a utilização dos gráficos de controle baseiam-se em resultados de medições e que nenhum sistema de medição é perfeito, a presença de erros de medição nos dados monitorados é inevitável. Estudos recentes indicam que o gráfico de controle do tipo Double Sampling pode ser uma alternativa favorável para o monitoramento de processos. No entanto, ainda há uma lacuna sobre estudos que investiguem o impacto dos erros de medição sobre gráficos Double Sampling voltados para o monitoramento da variância. Com base no exposto, o presente trabalho visa estudar como o desempenho do gráfico de controle Double Sampling S² é afetado pela presença dos erros de medição. Inicialmente, propõem-se uma revisão sistemática da literatura visando explorar estudos sobre o tema. Como metodologia principal de pesquisa tem-se a modelagem matemática e a simulação. Estuda-se a modelagem necessária para consideração dos erros de medição no design do gráfico de controle Double Sampling S² . Por meio de simulação, verifica-se o impacto sobre o número médio de amostras até se obter um sinal (ARL) para diferentes valores de erro de medição. Utilizando algoritmo genético, propõe-se um estudo de otimização do gráfico de controle Double Sampling S² para operação com erros de medição. Por fim, um exemplo de simulação é apresentado para verificar a utilização do gráfico Double Sampling S² com os parâmetros otimizados. Os resultados obtidos indicam que a presença do erro de medição deteriora o desempenho do gráfico Double Sampling S² e que o impacto é maior quanto maior o erro de medição. Por meio do estudo de simulação, verificou-se a vantagem de se utilizar o gráfico Double Sampling S² otimizado, principalmente para erros de medição de maior magnitude. O presente estudo contribui com o conhecimento necessário para aplicação prática do gráfico de controle Double Sampling S² à medida que fornece parâmetros para sua utilização quando na presença de erros de medição.Não recebi financiamentoengUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Engenharia de Produção - PPGEPUFSCarAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessProcess monitoringDouble Sampling control chartMeasurement errorsMonitoramento de processosGráfico de controle Double SamplingErros de mediçãoENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAOEffect of measurement errors on double sampling S² control chartEfeito dos erros de medição sobre o gráfico de controle S² de dupla amostrageminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesis600600de92d2f0-73e9-4496-a431-c252ce3e9a12reponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALTese - versao final.pdfTese - versao final.pdfTeseapplication/pdf3599828https://repositorio.ufscar.br/bitstream/ufscar/18116/1/Tese%20-%20versao%20final.pdf41711ebb8ea13d65375c87669dc75017MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8810https://repositorio.ufscar.br/bitstream/ufscar/18116/3/license_rdff337d95da1fce0a22c77480e5e9a7aecMD53TEXTTese - versao final.pdf.txtTese - versao final.pdf.txtExtracted texttext/plain194551https://repositorio.ufscar.br/bitstream/ufscar/18116/4/Tese%20-%20versao%20final.pdf.txtd4ed286ef9a9df9b41b4d51ad3799977MD54THUMBNAILTese - versao final.pdf.jpgTese - versao final.pdf.jpgIM Thumbnailimage/jpeg5974https://repositorio.ufscar.br/bitstream/ufscar/18116/5/Tese%20-%20versao%20final.pdf.jpg0561e9c42285cfa8bbd4f972f5cd5b36MD55ufscar/181162023-09-18 18:32:39.264oai:repositorio.ufscar.br:ufscar/18116Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:32:39Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.eng.fl_str_mv |
Effect of measurement errors on double sampling S² control chart |
dc.title.alternative.por.fl_str_mv |
Efeito dos erros de medição sobre o gráfico de controle S² de dupla amostragem |
title |
Effect of measurement errors on double sampling S² control chart |
spellingShingle |
Effect of measurement errors on double sampling S² control chart Couto, Giselle Elias Process monitoring Double Sampling control chart Measurement errors Monitoramento de processos Gráfico de controle Double Sampling Erros de medição ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO |
title_short |
Effect of measurement errors on double sampling S² control chart |
title_full |
Effect of measurement errors on double sampling S² control chart |
title_fullStr |
Effect of measurement errors on double sampling S² control chart |
title_full_unstemmed |
Effect of measurement errors on double sampling S² control chart |
title_sort |
Effect of measurement errors on double sampling S² control chart |
author |
Couto, Giselle Elias |
author_facet |
Couto, Giselle Elias |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/3061782528251400 |
dc.contributor.authororcid.por.fl_str_mv |
https://orcid.org/0000-0001-9248-6447 |
dc.contributor.advisor1orcid.por.fl_str_mv |
https://orcid.org/0000-0002-6213-2223 |
dc.contributor.author.fl_str_mv |
Couto, Giselle Elias |
dc.contributor.advisor1.fl_str_mv |
Oprime, Pedro Carlos |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9291517431456908 |
dc.contributor.authorID.fl_str_mv |
87490df3-0732-44de-859d-e3a7c0df4898 |
contributor_str_mv |
Oprime, Pedro Carlos |
dc.subject.eng.fl_str_mv |
Process monitoring Double Sampling control chart Measurement errors |
topic |
Process monitoring Double Sampling control chart Measurement errors Monitoramento de processos Gráfico de controle Double Sampling Erros de medição ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO |
dc.subject.por.fl_str_mv |
Monitoramento de processos Gráfico de controle Double Sampling Erros de medição |
dc.subject.cnpq.fl_str_mv |
ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO |
description |
Product quality can be understood as inversely proportional to the variability in its production process. The control chart is a well-established statistical tool for quantifying and analyzing this process' variability based on observed information about some of its measurable characteristics. To simplify the control chart application, some researchers and users assume that the data used to evaluate the process is accurate. However, since the construction and use of control charts are based on measurement and no measurement system is perfect, errors in the measured data are inevitable. Recent studies indicate that the Double Sampling control chart can be an alternative for process monitoring. However, there is still a lack of studies that investigate the impact of measurement errors on Double Sampling control chart to monitor process variability. Based on the preceding, the present work aims to study how the performance of the Double Sampling S² control chart is affected by the presence of measurement errors. Initially, a systematic review of the literature is proposed in order to explore studies on the subject. The main methodology of the research is mathematical modeling and simulation. A design modeling for considering measurement errors in the Double Sampling S² control chart is proposed. The impact on the average run length (ARL) for different measurement error values is verified through simulation. Using a genetic algorithm, we propose an optimization study of the Double Sampling S² control chart for operation with measurement errors. Finally, a simulation example is presented to verify using the Double Sampling S² chart with the optimized parameters. The results indicate that measurement error deteriorates the performance of the Double Sampling S² chart, and the impact rises as measurement error increases. The simulation analysis showed the advantage of using the optimized Double Sampling S² chart, particularly for larger measurement errors. The present study contributes to the practical application knowledge of the Double Sampling S² control chart, providing parameters for its use in the presence of measurement errors. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-06-07T13:06:14Z |
dc.date.available.fl_str_mv |
2023-06-07T13:06:14Z |
dc.date.issued.fl_str_mv |
2023-06-02 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
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doctoralThesis |
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publishedVersion |
dc.identifier.citation.fl_str_mv |
COUTO, Giselle Elias. Effect of measurement errors on double sampling S² control chart. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de São Carlos, São Carlos, 2023. Disponível em: https://repositorio.ufscar.br/handle/ufscar/18116. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/18116 |
identifier_str_mv |
COUTO, Giselle Elias. Effect of measurement errors on double sampling S² control chart. 2023. Tese (Doutorado em Engenharia de Produção) – Universidade Federal de São Carlos, São Carlos, 2023. Disponível em: https://repositorio.ufscar.br/handle/ufscar/18116. |
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https://repositorio.ufscar.br/handle/ufscar/18116 |
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eng |
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eng |
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600 600 |
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de92d2f0-73e9-4496-a431-c252ce3e9a12 |
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Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
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openAccess |
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Universidade Federal de São Carlos Câmpus São Carlos |
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Programa de Pós-Graduação em Engenharia de Produção - PPGEP |
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UFSCar |
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Universidade Federal de São Carlos Câmpus São Carlos |
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