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dc.contributor.authorde-Felipe, David
dc.contributor.authorBenedito Benet, Ernest
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Organització d'Empreses
dc.date.accessioned2017-12-20T08:45:03Z
dc.date.available2017-12-20T08:45:03Z
dc.date.issued2017-10
dc.identifier.citationde-Felipe, D., Benedito, E. Monitoring high complex production processes using process capability indices. "International journal of advanced manufacturing technology", Octubre 2017, vol. 93, núm. 1-4, p. 1257-1267.
dc.identifier.issn0268-3768
dc.identifier.urihttp://hdl.handle.net/2117/112299
dc.description.abstractThe increasing demand and the globalization of the market are leading to increasing levels of quality in production processes, and thus, nowadays, multiple product characteristics must be tested because they are considered critical. In this context, decision makers are forced to interpret a huge amount of quality indicators, when monitoring production processes. This fact leads to a misunderstanding as a result of information overload. The aim of this paper is to help practitioners when monitoring the capability of processes with a huge amount of product characteristics. We propose a methodology that reduces the amount of data in capability analysis by structuring hierarchically the multiple quality indicators obtained in the quality tests. The proposed methodology may help practitioners and decision makers of the industry in three aspects of statistical process monitoring: to identify the part of a complex production process that presents capability problems, to detect worsening over the time in multivariate production processes, and to compare similar production processes. Some illustrative examples based on different kinds of production processes are discussed in order to illustrate the methodology. A case of study based on a real production process of the automotive industry is analyzed using the proposed methodology. We conclude that the proposed methodology reduces the necessary amount of data in capability analysis; and thus, that it provides an added value of great interest for managers and decision makers.
dc.format.extent11 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject.lcshAutomobile industry and trade
dc.subject.lcshQuality control
dc.subject.lcshMachinery
dc.subject.otherProcess monitoring
dc.subject.otherProcess capability
dc.subject.otherMultivariate statistics Automotive industry
dc.subject.otherMachining process
dc.titleMonitoring high complex production processes using process capability indices
dc.typeArticle
dc.subject.lemacAutomòbils -- Indústria i comerç
dc.subject.lemacLogística (Indústria)
dc.subject.lemacControl de qualitat
dc.contributor.groupUniversitat Politècnica de Catalunya. EOLI - Enginyeria d'Organització i Logística Industrial
dc.identifier.doi10.1007/s00170-017-0591-8
dc.relation.publisherversionhttps://link.springer.com/article/10.1007%2Fs00170-017-0591-8
dc.rights.accessOpen Access
local.identifier.drac21586055
dc.description.versionPostprint (published version)
local.citation.authorde-Felipe, D.; Benedito, E.
local.citation.publicationNameInternational journal of advanced manufacturing technology
local.citation.volume93
local.citation.number1-4
local.citation.startingPage1257
local.citation.endingPage1267


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain