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dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.contributor.authorUgarte Querejeta, Miriam
dc.contributor.otherRicondo Iriondo, Itziar
dc.contributor.otherPorto, Alain
dc.date.accessioned2022-02-11T11:56:27Z
dc.date.available2022-02-11T11:56:27Z
dc.date.issued2021
dc.identifier.issn2212-8271en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=166804en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/5460
dc.description.abstractIndustry 4.0 has raised the expectations on productivity, automation, and resource efficiency of manufacturing systems. This paper proposes a digital twin framework for the simulation and optimization of production lines and cells that can be used in the design and operation stages. The framework is supported by an architecture that connects manufacturing and machine tool data (digital shadow), the discrete event simulation model and the optimization engine, allowing for a variety of functionalities to plan and manage the production system. A use case is provided to demonstrate this framework, implemented in an automated line for the manufacturing of railway axles.es
dc.description.sponsorshipComisión Europeaes
dc.language.isoengen
dc.publisherElsevier B.V.en
dc.rights© 2021 by the authors. Published by Elsevier BVen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectdigital twinen
dc.subjectdiscrete-event simulationen
dc.subjectmonitoringen
dc.subjectoptimizationen
dc.subjectServitizationen
dc.titleA digital twin framework for the simulation and optimization of production systemsen
dc.typeinfo:eu-repo/semantics/conferenceObjecten
dcterms.accessRightsinfo:eu-repo/semantics/openAccessen
dcterms.sourceProcedia CIRPen
dc.description.versioninfo:eu-repo/semantics/publishedVersionen
local.contributor.groupRobótica y automatizaciónes
local.contributor.groupIngeniería del software y sistemases
local.description.peerreviewedtrueen
local.description.publicationfirstpage762en
local.description.publicationlastpage767en
local.identifier.doihttps://doi.org/10.1016/j.procir.2021.11.128en
local.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/814078/EU/Digital Manufacturing and Design Training Network/DiManDen
local.contributor.otherinstitutionhttps://ror.org/003qafx79es
local.source.detailsVol. 104. Pp. 762-767, 2021en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore


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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