Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation

[EN] The AIDEAS project targets the development of AI technologies strategically designed to improve European engineering companies' sustainability, agility, and resilience throughout the lifecycle of industrial assets, i.e., in the design, manufacturing, and repair/reuse/recycling phases....

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Autores: Dörner, Marius, Schulz, Alexander, Martínez, Félix, Murn, Damjan, Radolovic, Dragan, Mateo-Casalí, Miguel Ángel|||0000-0001-5086-9378, Poler, R.|||0000-0003-4475-6371
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:dnet:riunet______::19516dfc5431de81636c0f38cec15105
Acceso en línea:https://riunet.upv.es/handle/10251/235100
Access Level:acceso abierto
Palabra clave:Design optimization
Artificial intelligence
Simulation
Digital twin
Machine design
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spelling Manufacturing and AI - Industrial Machine Data Generation and Artificial OptimisationDörner, MariusSchulz, AlexanderMartínez, FélixMurn, DamjanRadolovic, DraganMateo-Casalí, Miguel Ángel|||0000-0001-5086-9378Poler, R.|||0000-0003-4475-6371Design optimizationArtificial intelligenceSimulationDigital twinMachine design[EN] The AIDEAS project targets the development of AI technologies strategically designed to improve European engineering companies' sustainability, agility, and resilience throughout the lifecycle of industrial assets, i.e., in the design, manufacturing, and repair/reuse/recycling phases. In the context of the AIDEAS project, this workshop paper focuses on the early stages of the product development process to accelerate the development process with the help of AI-supported tools. The results of some of these AI solutions will also help at a later stage to decide which machine parameters need to be considered and optimised during product development to optimise the later life cycle according to the current requirements of the repair, reuse, and recycle phases.This paper was funded by European Union s Horizon Europe research and innovation programme under grant agreement No. 101057294, project AIDEAS (AI Driven industrial Equipment product life cycle boosting Agility, Sustainability, and resilience).Sun SITE Central EuropeDepartamento de Organización de EmpresasCentro de Investigación en Gestión e Ingeniería de ProducciónEscuela Politécnica Superior de AlcoyEuropean CommissionRepositorio Institucional de la Universitat Politècnica de València Riunet20262026-02-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/235100reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengEuropean Commission https://doi.org/10.13039/501100000780 HE 101057294 AI Driven industrial Equipment product life cycle boosting Agility, Sustainability and resilienceopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:dnet:riunet______::19516dfc5431de81636c0f38cec151052026-06-13T07:49:27Z
dc.title.none.fl_str_mv Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
title Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
spellingShingle Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
Dörner, Marius
Design optimization
Artificial intelligence
Simulation
Digital twin
Machine design
title_short Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
title_full Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
title_fullStr Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
title_full_unstemmed Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
title_sort Manufacturing and AI - Industrial Machine Data Generation and Artificial Optimisation
dc.creator.none.fl_str_mv Dörner, Marius
Schulz, Alexander
Martínez, Félix
Murn, Damjan
Radolovic, Dragan
Mateo-Casalí, Miguel Ángel|||0000-0001-5086-9378
Poler, R.|||0000-0003-4475-6371
author Dörner, Marius
author_facet Dörner, Marius
Schulz, Alexander
Martínez, Félix
Murn, Damjan
Radolovic, Dragan
Mateo-Casalí, Miguel Ángel|||0000-0001-5086-9378
Poler, R.|||0000-0003-4475-6371
author_role author
author2 Schulz, Alexander
Martínez, Félix
Murn, Damjan
Radolovic, Dragan
Mateo-Casalí, Miguel Ángel|||0000-0001-5086-9378
Poler, R.|||0000-0003-4475-6371
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Organización de Empresas
Centro de Investigación en Gestión e Ingeniería de Producción
Escuela Politécnica Superior de Alcoy
European Commission
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Design optimization
Artificial intelligence
Simulation
Digital twin
Machine design
topic Design optimization
Artificial intelligence
Simulation
Digital twin
Machine design
description [EN] The AIDEAS project targets the development of AI technologies strategically designed to improve European engineering companies' sustainability, agility, and resilience throughout the lifecycle of industrial assets, i.e., in the design, manufacturing, and repair/reuse/recycling phases. In the context of the AIDEAS project, this workshop paper focuses on the early stages of the product development process to accelerate the development process with the help of AI-supported tools. The results of some of these AI solutions will also help at a later stage to decide which machine parameters need to be considered and optimised during product development to optimise the later life cycle according to the current requirements of the repair, reuse, and recycle phases.
publishDate 2026
dc.date.none.fl_str_mv 2026
2026-02-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/235100
url https://riunet.upv.es/handle/10251/235100
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission https://doi.org/10.13039/501100000780 HE 101057294 AI Driven industrial Equipment product life cycle boosting Agility, Sustainability and resilience
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Sun SITE Central Europe
publisher.none.fl_str_mv Sun SITE Central Europe
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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