2026-04-07T11:37:06Zhttps://ebiltegia.mondragon.edu/oai/request

oai:ebiltegia.mondragon.edu:20.500.11984/54602024-03-04T15:06:52Zcom_20.500.11984_1143col_20.500.11984_1148

Ugarte Querejeta, Miriam 2022-02-11T11:56:27Z 2022-02-11T11:56:27Z 2021 2212-8271 https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=166804 https://hdl.handle.net/20.500.11984/5460 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. eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2021 by the authors. Published by Elsevier BV digital twin discrete-event simulation monitoring optimization Servitization A digital twin framework for the simulation and optimization of production systems http://purl.org/coar/resource_type/c_c94f