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Latent Structures based-Multivariate Statistical Process Control: a paradigm shift

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Latent Structures based-Multivariate Statistical Process Control: a paradigm shift

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dc.contributor.author Ferrer, Alberto es_ES
dc.date.accessioned 2016-02-11T12:51:26Z
dc.date.available 2016-02-11T12:51:26Z
dc.date.issued 2014-01-02
dc.identifier.issn 0898-2112
dc.identifier.uri http://hdl.handle.net/10251/60805
dc.description.abstract The basic fundamentals of statistical process control (SPC) were proposed by Walter Shewhart for data-starved production environments typical in the 1920s and 1930s. In the 21st century, the traditional scarcity of data has given way to a data-rich environment typical of highly automated and computerized modern processes. These data often exhibit high correlation, rank deficiency, low signal-to-noise ratio, multistage and multiway structures, and missing values. Conventional univariate and multivariate SPC techniques are not suitable in these environments. This article discusses the paradigm shift to which those working in the quality improvement field should pay keen attention. We advocate the use of latent structure based multivariate statistical process control methods as efficient quality improvement tools in these massive data contexts. This is a strategic issue for industrial success in the tremendously competitive global market. es_ES
dc.description.sponsorship This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2011-28112-C04-02. en_EN
dc.language Inglés es_ES
dc.publisher Taylor & Francis es_ES
dc.relation Spanish Ministry of Economy and Competitiveness DPI2011-28112-C04-02 es_ES
dc.relation.ispartof Quality Engineering es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Control charts es_ES
dc.subject Latent structures es_ES
dc.subject Multivariate statistical process control (MSPC) es_ES
dc.subject Partial least squares (PLS) es_ES
dc.subject Principal component analysis (PCA) es_ES
dc.subject Quality improvement es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Latent Structures based-Multivariate Statistical Process Control: a paradigm shift es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/08982112.2013.846093
dc.rights.accessRights Abierto 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 Ferrer, A. (2014). Latent Structures based-Multivariate Statistical Process Control: a paradigm shift. Quality Engineering. 26(1):72-91. doi:10.1080/08982112.2013.846093 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1080/08982112.2013.846093 es_ES
dc.description.upvformatpinicio 72 es_ES
dc.description.upvformatpfin 91 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 26 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 282468 es_ES
dc.identifier.eissn 1532-4222


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