A digital twin framework for the simulation and optimization of production systems

Ugarte Querejeta, Miriam

dc.rights.license	Attribution-NonCommercial-NoDerivatives 4.0 International	*
dc.contributor.author	Ugarte Querejeta, Miriam
dc.contributor.other	Ricondo Iriondo, Itziar
dc.contributor.other	Porto, Alain
dc.date.accessioned	2022-02-11T11:56:27Z
dc.date.available	2022-02-11T11:56:27Z
dc.date.issued	2021
dc.identifier.issn	2212-8271	en
dc.identifier.other	https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=166804	en
dc.identifier.uri	https://hdl.handle.net/20.500.11984/5460
dc.description.abstract	Industry 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.sponsorship	Comisión Europea	es
dc.language.iso	eng	en
dc.publisher	Elsevier B.V.	en
dc.rights	© 2021 by the authors. Published by Elsevier BV	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	digital twin	en
dc.subject	discrete-event simulation	en
dc.subject	monitoring	en
dc.subject	optimization	en
dc.subject	Servitization	en
dc.title	A digital twin framework for the simulation and optimization of production systems	en
dcterms.accessRights	http://purl.org/coar/access_right/c_abf2	en
dcterms.source	Procedia CIRP	en
local.contributor.group	Robótica y automatización	es
local.contributor.group	Ingeniería del software y sistemas	es
local.description.peerreviewed	true	en
local.description.publicationfirstpage	762	en
local.description.publicationlastpage	767	en
local.identifier.doi	https://doi.org/10.1016/j.procir.2021.11.128	en
local.relation.projectID	info:eu-repo/grantAgreement/EC/H2020/814078/EU/Digital Manufacturing and Design Training Network/DiManD	en
local.contributor.otherinstitution	https://ror.org/003qafx79	es
local.source.details	Vol. 104. Pp. 762-767, 2021	en
oaire.format.mimetype	application/pdf
oaire.file	$DSPACE\assetstore
oaire.resourceType	http://purl.org/coar/resource_type/c_c94f	en
oaire.version	http://purl.org/coar/version/c_970fb48d4fbd8a85	en