A new sampling strategy to reduce the effect of autocorrelation on a control chart

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorLUNAM Université, IRCCyN UMR CNRS 6597-
Autor(es): dc.contributorLUNAM Université, Université de Nantes and IRCCyN UMR CNRS 6597-
Autor(es): dc.creatorFranco, Bruno Chaves-
Autor(es): dc.creatorCastagliola, Philippe-
Autor(es): dc.creatorCelano, Giovanni-
Autor(es): dc.creatorCosta, Antonio Fernando Branco-
Data de aceite: dc.date.accessioned2025-08-21T17:11:52Z-
Data de disponibilização: dc.date.available2025-08-21T17:11:52Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2014-01-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1080/02664763.2013.871507-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/227734-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/227734-
Descrição: dc.descriptionOn-line monitoring of quality characteristics is essential to limit scrap and rework costs due to bad quality in a manufacturing process. In several manufacturing environments, during production process data can be massively collected with high sampling rates and tight sampling frequencies. As a consequence, natural autocorrelation may arise among consecutive measures within a sample. Autocorrelation significantly inflates the average run length of a control chart and deteriorates its sensitivity to the occurrence of assignable causes. In this paper, we propose a new mixed sampling strategy for the Shewhart chart monitoring the sample mean in a process where temporal autocorrelation between two consecutive observations can be represented by means of a first order autoregressive model AR(1). With this strategy, the sample mean at each inspection time is computed by merging measures of a generic quality characteristic from two consecutive samples taken h hours apart. The statistical properties of a Shewhart control chart implementing the proposed strategy are compared to those implementing a skipping strategy recently proposed in literature. A numerical analysis shows that the mixed sampling outperforms the skipping sampling strategy for high levels of autocorrelation. © 2013 © 2013 Taylor & Francis.-
Descrição: dc.descriptionProduction Department, São Paulo State University, Guaratinguetá, SP-
Descrição: dc.descriptionLUNAM Université, IRCCyN UMR CNRS 6597, Nantes-
Descrição: dc.descriptionLUNAM Université, Université de Nantes and IRCCyN UMR CNRS 6597, Nantes-
Descrição: dc.descriptionDepartment of Industrial Engineering, University of Catania, Catania-
Descrição: dc.descriptionProduction Department, São Paulo State University, Guaratinguetá, SP-
Formato: dc.format1408-1421-
Idioma: dc.languageen-
Relação: dc.relationJournal of Applied Statistics-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAR(1)-
Palavras-chave: dc.subjectARL-
Palavras-chave: dc.subjectautocorrelation-
Palavras-chave: dc.subjectsampling strategy-
Palavras-chave: dc.subjectShewhart control chart-
Título: dc.titleA new sampling strategy to reduce the effect of autocorrelation on a control chart-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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