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A Soft Computing System for Modelling the Manufacture of Steel Components
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Author(s): Javier Sedano (University of Burgos, Spain), José Ramón Villar (University of Oviedo, Spain), Leticia Curiel (University of Burgos, Spain), Emilio Corchado (University of Burgos, Spain)and Andrés Bustillo (University of Burgos, Spain)
Copyright: 2010
Pages: 16
Source title:
Soft Computing Methods for Practical Environment Solutions: Techniques and Studies
Source Author(s)/Editor(s): Marcos Gestal Pose (University of A Coruna, Spain)and Daniel Rivero Cebrián (University of A Coruna, Spain)
DOI: 10.4018/978-1-61520-893-7.ch009
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Abstract
This chapter presents a soft computing system developed to optimize the laser milling manufacture of high value steel components, a relatively new and interesting industrial technique. This applied research presents a multidisciplinary study based on the application of unsupervised neural projection models in conjunction with identification systems, in order to find the optimal operating conditions in this industrial issue. Sensors on a laser milling centre capture the data used in this industrial case of study defined under the frame of a machine-tool that manufactures steel components for high value molds and dies. Then a detailed study of the laser milling manufacture of high value steel components is presented based mainly on the analysis of four features: angle error, depth error, surface roughness and material removal rate. The presented model is based on a two-phases application. The first phase uses an unsupervised neural projection model capable of determine if the data collected is informative enough. The second phase is focus on identifying a model for the laser-milling process based on low-order models such as Black Box ones. The whole system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins and Output Error algorithms, which calculate the function of a linear system based on its input and output variables, are the most appropriate models to control such industrial task for the case of the analysed steel tools. The model can be applied to laser milling optimization of other materials of industrial interest and also to other industrial multivariable processes like High Speed Milling or Laser Cladding.
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