2026-04-17T20:34:57Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/93642024-07-12T00:05:24Zcom_10259_3847com_10259_5086com_10259_2604col_10259_7109

Bustillo Iglesias, Andrés Sedano, Javier Ramón Villar, José Curiel Herrera, Leticia Elena Corchado, Emilio 2024-07-11T09:34:03Z 2024-07-11T09:34:03Z 2008-09-16 978-0-7695-3325-4 http://hdl.handle.net/10259/9364 10.1109/EMS.2008.106 Trabajo presentado en: Second UKSIM European Symposium on Computer Modeling and Simulation - EMS 2008, realizado el 08, 09 y 10 de septiembre de 2008, en Liverpool (Reino Unido) This study presents a research that identifies and applies unsupervised connectionist models in conjunction with modelling systems, in order todetermine optimal conditions to perform laser milling of metallic components. This industrial problem is defined by a data set relayed through sensors situated on a laser milling centre that is a machine-tool used to manufacture high value micro-molds and micro-dies. The results of the study and the application of the connectionist architectures allow the identification, in a second phase, of a model for the milling machine process based on low-order models such as Black Box, which are capable of approximating the optimal form of the model. Finally, it is shown that the most appropriate model to control these industrial tasks is the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples. This research has been partially supported by the project BU006A08.- JCyL. application/pdf eng Institute of Electrical and Electronics Engineers (IEEE) Second UKSIM European Symposium on Computer Modeling and Simulation, p. 317-322 https://ieeexplore.ieee.org/document/4625293 Informática Inteligencia artificial Industria Computer science Artificial intelligence Industry Conventional Methods and AI models for Solving an Industrial an Industrial Problem info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/openAccess 317 322