2026-04-17T08:02:31Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/74112023-03-27T11:44:53Zcom_10259_3847com_10259_5086com_10259_2604col_10259_7409

Bustillo Iglesias, Andrés 81 600 0000-0003-2855-7532 Sedano, Javier 2bf97993-b410-4fe4-9d0b-5cd90272a1b5 600 Curiel Herrera, Leticia Elena 824 500 Villar, José Ramón e18b6fc4-d919-45d6-ae7f-cf9259f6c918 600 Corchado, Emilio 125 600 0000-0001-8560-3991 2023-02-07T12:06:46Z 2023-02-07T12:06:46Z 2009 978-3-540-93905-4 978-3-540-93904-7 1867-5662 http://hdl.handle.net/10259/7411 10.1007/978-3-540-93905-4_70 1867-5670 In this paper we present a soft computing system developed to optimize the laser milling manufacture of high value steel components, a relatively new and interesting industrial technique. This multidisciplinary study is based on the application of 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 study defined under the frame of a machine-tool that manufactures steel components like high value molds and dies. The presented model is based on a two-phase application. The first phase uses a neural projection model capable of determine if the data collected is informative enough based on the existence of internal patterns. 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 algorithm, which calculates the function of a linear system from its input and output samples, is the most appropriate model to control such industrial task for the case of steel components. This research has been partially supported through project BU006A08 of JCyL and through project CIT-020000-2008-2 of Spanish Ministry of Education and Innovation. application/pdf eng Springer Computer Recognition Systems 3, p. 601–609 https://doi.org/10.1007/978-3-540-93905-4_70 info:eu-repo/grantAgreement/Junta de Castilla y León//BU006A08//Arquitectura distribuida inteligente para la gestión de entornos de dependencia y hospitalarios/ info:eu-repo/grantAgreement/MICINN//CIT-020000-2008-2/ES/Desarrollo de un sistema experto para el ajuste automático de fresadoras (QUICK)/ Test Piece Angle Error Wall Angle Steel Component Soft Computing Model Informática Computer science A Soft Computing System for Modelling the Manufacture of Steel Components info:eu-repo/semantics/bookPart info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/openAccess 57 601 609 THUMBNAIL A_soft_computing_system_modelling_manufacture_steel_components.pdf.jpg A_soft_computing_system_modelling_manufacture_steel_components.pdf.jpg IM Thumbnail image/jpeg 3562 https://riubu.ubu.es/bitstream/10259/7411/3/A_soft_computing_system_modelling_manufacture_steel_components.pdf.jpg 601dbf38239c7fc20dce0a36491d0954 MD5 3 LICENSE license.txt license.txt text/plain; charset=utf-8 1362 https://riubu.ubu.es/bitstream/10259/7411/2/license.txt 5d013bfa6e473ff0db22cd82a4d71a70 MD5 2 ORIGINAL A_soft_computing_system_modelling_manufacture_steel_components.pdf A_soft_computing_system_modelling_manufacture_steel_components.pdf application/pdf 154729 https://riubu.ubu.es/bitstream/10259/7411/1/A_soft_computing_system_modelling_manufacture_steel_components.pdf 0068483b15590a3026f48660512a118b MD5 1 10259/7411 oai:riubu.ubu.es:10259/7411 2023-03-27 13:44:53.041 Repositorio Institucional de la Universidad de Burgos bubrep@ubu.es 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