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dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.contributor.authorGonzález Tomé, Ander
dc.contributor.authorIrigoyen Ceberio, Ibai
dc.contributor.authorAyala, Unai
dc.contributor.authorAgirre, Joseba Andoni
dc.contributor.authorArana-Arexolaleiba, Nestor
dc.date.accessioned2021-02-05T08:47:49Z
dc.date.available2021-02-05T08:47:49Z
dc.date.issued2020
dc.identifier.issn2351-9789en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=159338en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5204
dc.description.abstractAs the investment on a dedicated quality control stations is not desirable for limited production batches. In general, those systems result in very optimised systems and the lack of flexibility since they are designed for an ad-hoc production. To provide a solution for those cases, a new model to design a flexible quality inspection system is proposed. This paper introduces FlexRQC (Flexible Robotic Quality Control) a model for characterising flexible robot-driven quality control stations. FlexRQC is divided into two domains: The Quality Control Station Domain (QCSD) and the Model Under Inspection Domains (MUID). FlexRQC takes advantage of 3D CAD systems to get spacial information on the quality control station and the quality requirement. The flexibility of the model has been successfully tested in two quality control station setups and various solid rigid objects.en
dc.description.sponsorshipGobierno Vascoes
dc.language.isoengen
dc.publisherElsevier Ltd.en
dc.rights© 2020 The Author(s)en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectRoboticsen
dc.subjectFlexible Quality Inspectionen
dc.subjectProgrammingen
dc.titleFlexRQC: Model for a Flexible Robot-Driven Quality Control Stationen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceProcedia Manufacturingen
local.contributor.groupRobótica y automatizaciónes
local.description.peerreviewedtrueen
local.description.publicationfirstpage81en
local.description.publicationlastpage87en
local.identifier.doihttps://doi.org/10.1016/j.promfg.2020.10.013en
local.relation.projectIDGV/Convocatoria Universidad Empresa 2018-2019/PUE 2018-06/CAPV/Desarrollo de un sistema de inspección inteligente basado en algoritmos de Deep Learning para células robotizadas flexibles multi-puesto 3D/IDEFIXen
local.source.detailsVol. 51. Pp. 81-87, 2020en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501en
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85en


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International