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The Industrial Digital Energy Twin as a Tool for the Comprehensive Optimization of Industrial Processes

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The Industrial Digital Energy Twin as a Tool for the Comprehensive Optimization of Industrial Processes

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dc.contributor.author Rubio-Rico, Alejandro es_ES
dc.contributor.author Mengod-Bautista, Fernando es_ES
dc.contributor.author Lluna Arriaga, Andres es_ES
dc.contributor.author Arroyo-Torres, Belén es_ES
dc.contributor.author Fuster Roig, Vicente Luis es_ES
dc.date.accessioned 2024-10-08T18:10:01Z
dc.date.available 2024-10-08T18:10:01Z
dc.date.issued 2023-08 es_ES
dc.identifier.uri http://hdl.handle.net/10251/209536
dc.description.abstract [EN] Industrial manufacturing processes have evolved and improved since the disruption of the Industry 4.0 paradigm, while energy has progressively become a strategic resource required to maintain industrial competitiveness while maximizing quality and minimizing environmental impacts. In this context of global changes leading to social and economic impact in the short term and an unprecedented climate crisis, Digital Twins for Energy Efficiency in manufacturing processes provide companies with a tool to address this complex situation. Nevertheless, already existing Digital Twins applied for energy efficiency in a manufacturing process lack a flexible structure that easily replicates the real behavior of consuming machines while integrating it in complex upper-level environments. This paper presents a combined multi-paradigm approach to industrial process modeling developed and applied during the GENERTWIN project. The tool allows users to predict energy consumption and costs and, at the same time, evaluates the behavior of the process under certain productive changes to maximize consumption optimization, production efficiency and process flexibility. es_ES
dc.description.sponsorship GENERTWIN Sistema Digital de Análisis de procesos industriales para GENERación de escenarios alternativos bajo consideraciones productivas y de eficiencia energética , IMDEEA/2022/16, has been co-financed by IVACE (Instituto Valenciano de Competitividad Empresarial) and ERDF funds (European Regional Development Fund). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Processes es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Digital twin es_ES
dc.subject Smart manufacturing es_ES
dc.subject Energy es_ES
dc.subject Energy efficiency es_ES
dc.subject Productive flexibility es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title The Industrial Digital Energy Twin as a Tool for the Comprehensive Optimization of Industrial Processes es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/pr11082353 es_ES
dc.relation.projectID info:eu-repo/grantAgreement//IVACE//IMDEEA%2F2022%2F16/ES/Sistema Digital de Análisis de procesos industriales para Generación de escenarios alternativos bajo consideraciones productivas y de eficiencia energética/GENERTWIN es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Tecnología Eléctrica - Institut de Tecnologia Elèctrica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Rubio-Rico, A.; Mengod-Bautista, F.; Lluna Arriaga, A.; Arroyo-Torres, B.; Fuster Roig, VL. (2023). The Industrial Digital Energy Twin as a Tool for the Comprehensive Optimization of Industrial Processes. Processes. 11(8). https://doi.org/10.3390/pr11082353 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/pr11082353 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.description.issue 8 es_ES
dc.identifier.eissn 2227-9717 es_ES
dc.relation.pasarela S\509022 es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder Institut Valencià de Competitivitat Empresarial es_ES


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