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    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
    Bustillo Iglesias, AndrésAutoridad UBU Orcid
    Sedano, Javier
    Ramón Villar, José
    Curiel Herrera, Leticia ElenaAutoridad UBU Orcid
    Corchado, EmilioAutoridad UBU Orcid
    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)
    Abstract
    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
    URI
    http://hdl.handle.net/10259/9366
    Versión del editor
    https://doi.org/10.1007/978-3-540-88906-9_63
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