Decision support system (DSS) for manufacturing engineering of cans rolling
| dc.contributor.author | Martín, Ander | |
| dc.contributor.author | Penalva Oscoz, Mariluz | |
| dc.contributor.author | Veiga Suárez, Fernando | |
| dc.contributor.author | Ruiz Palencia, Cristina | |
| dc.contributor.author | Martínez, Víctor | |
| dc.contributor.department | Ingeniería | es_ES |
| dc.contributor.department | Ingeniaritza | eu |
| dc.date.accessioned | 2025-08-13T09:05:52Z | |
| dc.date.available | 2025-08-13T09:05:52Z | |
| dc.date.issued | 2025 | |
| dc.date.updated | 2025-08-13T08:58:11Z | |
| dc.description.abstract | Decision Support Systems (DSS) can help factory workers in the decision-making step of multiple tasks. In digital factories, these systems make use of data towards a human-centered manufacturing. Rolling of large and thick plates into cans is a common practice in the metal forming industry to fabricate pipes or tanks. The process is adjusted by trial and error with a high level of operator intervention. Furthermore, only a small number of cans are identical. The objective of this work is to prescribe, by means of a DSS, the process parameters to be applied by the operator in the machine to optimize the can fabrication. The development of the DSS involved several steps, including firstly signal preprocessing and classification and then data extraction, aggregation, and regression in a multi-stage prediction framework. A significant use of domain knowledge for a data-centric solution contributes to the quality of the recommendations and the ability to organize and transfer know-how among operators. | en |
| dc.description.sponsorship | The authors acknowledge the funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 958303. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Martín, A., Penalva, M., Veiga, F., Ruiz, C., Martínez, V. (2025) Decision support system (DSS) for manufacturing engineering of cans rolling. In Alexopoulos, K., Makris, S., Stavropoulos P. (Eds.), Advances in artificial intelligence in manufacturing II: Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, October 16, 2024, Athens, Greece (pp. 171-179). Springer. https://doi.org/10.1007/978-3-031-86489-6_18 | |
| dc.identifier.doi | 10.1007/978-3-031-86489-6_18 | |
| dc.identifier.isbn | 978-3-031-86488-9 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/54708 | |
| dc.language.iso | eng | |
| dc.publisher | Springer | |
| dc.relation.ispartof | In Alexopoulos, K.; Makris, S.; Stavropoulos, P. (Eds.). Advances in artificial intelligence in manufacturing II: Proceedings of the 2nd European Symposium on Artificial Intelligence in Manufacturing, October 16, 2024, Athens, Greece. Cham: Springer; 2025. p. 171-179 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/European Commission/Horizon 2020 Framework Programme/958303/ | |
| dc.relation.publisherversion | https://doi.org/10.1007/978-3-031-86489-6_18 | |
| dc.rights | © The Author(s) 2025. This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Classification | en |
| dc.subject | Data aggregation | en |
| dc.subject | Data-centric regression | en |
| dc.subject | Decision Support System | en |
| dc.subject | Domain knowledge-based feature extraction | en |
| dc.subject | Machine learning | en |
| dc.subject | Metal forming | en |
| dc.title | Decision support system (DSS) for manufacturing engineering of cans rolling | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 2b7b0dc3-53e2-4710-b104-17eea797eeff | |
| relation.isAuthorOfPublication.latestForDiscovery | 2b7b0dc3-53e2-4710-b104-17eea797eeff |