Monitoring the covariance matrix of bivariate processes with the DVMAX control charts

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorUniversidade Federal de Minas Gerais (UFMG)-
Autor(es): dc.contributorUniversitá di Catania-
Autor(es): dc.creatorMachado, Marcela A. G.-
Autor(es): dc.creatorLee Ho, Linda-
Autor(es): dc.creatorQuinino, Roberto C.-
Autor(es): dc.creatorCelano, Giovanni-
Data de aceite: dc.date.accessioned2025-08-21T20:47:24Z-
Data de disponibilização: dc.date.available2025-08-21T20:47:24Z-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2022-04-28-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1002/asmb.2651-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/222596-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/222596-
Descrição: dc.descriptionTwo versions of Phase II attribute+variable (DVMAX) control charts are investigated for monitoring the covariance matrix (Formula presented.) of bivariate processes. Monitoring always starts with an attribute chart employing the Max D control chart and, depending on the outcome, a variable control chart named VMAX chart is run at a second stage to check for process stability. In the first version, denoted as the (Formula presented.) chart, two independent samples are used at the two stages of the same inspection; with the second version, denoted as the (Formula presented.) chart, the same sample is used at both the first and second stage of the same inspection. This approach, based on the implementation of two types of charts, can be designed to be more advantageous than a single variable control chart in terms of detection speed of a shift in the covariance matrix. In general, we conclude that the (Formula presented.) control charts not only shows the best statistical performance but also presents a lower average sampling cost. A numerical example illustrates the implementation of the proposed control charts.-
Descrição: dc.descriptionDepartment of Production Engineering UNESP-
Descrição: dc.descriptionDepartment of Production Engineering Universidade de São Paulo-
Descrição: dc.descriptionDepartment of Statistics Universidade Federal de Minas Gerais-
Descrição: dc.descriptionDepartment of Civil Engineering and Architecture Universitá di Catania-
Descrição: dc.descriptionDepartment of Production Engineering UNESP-
Formato: dc.format116-132-
Idioma: dc.languageen-
Relação: dc.relationApplied Stochastic Models in Business and Industry-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectaverage run length-
Palavras-chave: dc.subjectMax D chart-
Palavras-chave: dc.subjectsimulation-
Palavras-chave: dc.subjecttruncated normal distribution-
Palavras-chave: dc.subjectVMAX chart-
Título: dc.titleMonitoring the covariance matrix of bivariate processes with the DVMAX control charts-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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