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Optimal EWMA of linear combination of Poisson variables for multivariate statistical process control

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Optimal EWMA of linear combination of Poisson variables for multivariate statistical process control

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dc.contributor.author García Bustos, Sandra Lorena es_ES
dc.contributor.author Aparisi García, Francisco José es_ES
dc.contributor.author Kahn Epprecht, Eugenio es_ES
dc.date.accessioned 2016-10-17T09:36:45Z
dc.date.available 2016-10-17T09:36:45Z
dc.date.issued 2015-07-18
dc.identifier.issn 0020-7543
dc.identifier.uri http://hdl.handle.net/10251/71904
dc.description.abstract In this paper, we propose a new process control chart for monitoring correlated Poisson variables, the EWMA LCP chart. This chart is the exponentially weighted moving average (EWMA) version of the recently proposed LCP chart. The latter is a Shewhart-type control chart whose control statistic is a linear combination of the values of the different Poisson variables (elements of the Poisson vector) at each sampling time. As a Shewhart chart, it is effective at signalling large process shifts but is slow to signal smaller shifts. EWMA charts are known to be more sensitive to small and moderate shifts than their Shewhart-type counterparts, so the motivation of the present development is to enhance the performance of the LCP chart by the incorporation of the EWMA procedure to it. To ease the design of the EWMA LCP chart for the end user, we developed a user-friendly programme that runs on Windows (c) and finds the optimal design of the chart, that is, the coefficients of the linear combination as well as the EWMA smoothing constant and chart control limits that together minimise the out-of-control ARL under a constraint on the in-control ARL. The optimization is carried out by genetic algorithms where the ARLs are calculated through a Markov chain model. We used this programme to evaluate the performance of the new chart. As expected, the incorporation of the EWMA scheme greatly improves the performance of the LCP chart. es_ES
dc.description.sponsorship This research has been supported by SENESCYT-Ecuador (National Secretary of Higher Education, Science, Technology and Innovation of Equator) and by the CNPq (the Brazilian Council for Scientific and Technological Development), projects numbers 307453/2011-1 and 453054/2014-5. en_EN
dc.language Inglés es_ES
dc.publisher Taylor & Francis es_ES
dc.relation SENESCYT-Ecuador (National Secretary of Higher Education, Science, Technology and Innovation of Equator) es_ES
dc.relation CNPq (the Brazilian Council for Scientific and Technological Development) 307453/2011-1 453054/2014-5 es_ES
dc.relation.ispartof International Journal of Production Research es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject multivariate es_ES
dc.subject genetic algorithm es_ES
dc.subject control chart es_ES
dc.subject EWMA es_ES
dc.subject Poisson es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Optimal EWMA of linear combination of Poisson variables for multivariate statistical process control es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/00207543.2014.975863
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Garcia Bustos, SL.; Aparisi García, FJ.; Kahn Epprecht, E. (2015). Optimal EWMA of linear combination of Poisson variables for multivariate statistical process control. International Journal of Production Research. 53(14):4141-4159. doi:10.1080/00207543.2014.975863 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1080/00207543.2014.975863 es_ES
dc.description.upvformatpinicio 4141 es_ES
dc.description.upvformatpfin 4159 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 53 es_ES
dc.description.issue 14 es_ES
dc.relation.senia 295766 es_ES
dc.identifier.eissn 1366-588X


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