dc.rights.license | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.contributor.author | González Tomé, Ander | |
dc.contributor.author | Irigoyen Ceberio, Ibai | |
dc.contributor.author | Ayala, Unai | |
dc.contributor.author | Agirre, Joseba Andoni | |
dc.contributor.author | Arana-Arexolaleiba, Nestor | |
dc.date.accessioned | 2021-02-05T08:47:49Z | |
dc.date.available | 2021-02-05T08:47:49Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 2351-9789 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=159338 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/5204 | |
dc.description.abstract | As 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.sponsorship | Gobierno Vasco | es |
dc.language.iso | eng | en |
dc.publisher | Elsevier Ltd. | en |
dc.rights | © 2020 The Author(s) | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Robotics | en |
dc.subject | Flexible Quality Inspection | en |
dc.subject | Programming | en |
dc.title | FlexRQC: Model for a Flexible Robot-Driven Quality Control Station | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | Procedia Manufacturing | en |
local.contributor.group | Robótica y automatización | es |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 81 | en |
local.description.publicationlastpage | 87 | en |
local.identifier.doi | https://doi.org/10.1016/j.promfg.2020.10.013 | en |
local.relation.projectID | GV/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/IDEFIX | en |
local.source.details | Vol. 51. Pp. 81-87, 2020 | en |
oaire.format.mimetype | application/pdf | |
oaire.file | $DSPACE\assetstore | |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | en |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | en |