RT info:eu-repo/semantics/conferenceObject T1 Conventional Methods and AI models for Solving an Industrial an Industrial Problem A1 Bustillo Iglesias, Andrés A1 Sedano, Javier A1 Ramón Villar, José A1 Curiel Herrera, Leticia Elena A1 Corchado, Emilio K1 Informática K1 Computer science K1 Inteligencia artificial K1 Artificial intelligence K1 Industria K1 Industry AB 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. PB Institute of Electrical and Electronics Engineers (IEEE) SN 978-0-7695-3325-4 YR 2008 FD 2008-09-16 LK http://hdl.handle.net/10259/9364 UL http://hdl.handle.net/10259/9364 LA eng NO 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) NO This research has been partially supported by the project BU006A08.- JCyL. DS Repositorio Institucional de la Universidad de Burgos RD 08-ene-2025