Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/9366
Título
AI for Modelling the Laser Milling of Copper Components
Autor
Publicado en
Lecture Notes in Computer Science. 2008, V. 5326, p. 498-507
Editorial
Springer Nature
Fecha de publicación
2008
ISSN
0302-9743
DOI
10.1007/978-3-540-88906-9_63
Descripción
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)
Resumen
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.
Materia
Informática
Computer science
Inteligencia artificial
Artificial intelligence
Versión del editor
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