RT info:eu-repo/semantics/conferenceObject
T1 AI for Modelling the Laser Milling of Copper Components
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
AB Laser milling is a relatively new micromanufacturing technique in the production of copper and other metallic components. This study presents multidisciplinary research, which is based on unsupervised connectionist architectures in conjunction with modelling systems, on the determination of the optimal operating conditions in this industrial process. Sensors on a laser milling centre relay the data used in this industrial case study of a machine-tool that manufactures copper components for high value micro-coolers. The two-phase application of the connectionist architectures is capable of identifying a model for the laser-milling process based on low-order models such as Black Box. The final system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples, is the most appropriate model to control these industrial tasks.
PB Springer Nature
SN 0302-9743
YR 2008
FD 2008
LK http://hdl.handle.net/10259/9366
UL http://hdl.handle.net/10259/9366
LA eng
NO Trabajo presentado en: Intelligent Data Engineering and Automated Learning – IDEAL 2008, realizado del 2 al 5 de noviembre de 2008, en Daejeon (Corea del Sur)
NO This research has been partially supported through project BU006A08 of the JCyL.
DS Repositorio Institucional de la Universidad de Burgos
RD 12-feb-2025