RT info:eu-repo/semantics/conferenceObject
T1 A Soft Computing System to Perform Face Milling Operations
A1 Redondo Guevara, Raquel
A1 Santos González, Pedro
A1 Bustillo Iglesias, Andrés
A1 Sedano, Javier
A1 Villar, José R.
A1 Correa, Maritza
A1 Alique, José Ramón
A1 Corchado, Emilio
K1 Fresado
K1 Milling (Metal-work)
K1 Redes neuronales artificiales
K1 Neural networks (Computer science)
AB In this paper we present a soft computing system developed to optimize the face milling operation under High Speed conditions in the manufacture of steel components like molds with deep cavities. This applied research presents a multidisciplinary study 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 milling centre capture the data used in this industrial case study defined under the frame of a machine-tool that manufactures industrial tools. 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. The second phase is focus on identifying a model for the face 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 tools.
PB Springer
SN 978-3-642-02480-1
YR 2009
FD 2009
LK https://hdl.handle.net/10259/11485
UL https://hdl.handle.net/10259/11485
LA eng
NO Comunicación presentada en: 10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Workshops, Salamanca, Spain, June 10-12, 2009. Proceedings, Part II
NO This research has been partially supported through project BU006A08 of Junta de Castilla y León, through projects CIT-020000-2008-2 and TIN2007-62626 of Spanish Ministry of Science and Innovation and the MOCAVE Project under Grant DPI2006- 12736-C02-01. The authors would also like to thank the manufacturer of components for vehicle interiors, Grupo Antolin Ingeniería, S.A. in the framework of the project MAGNO 2008 - 1028.- CENIT Project funded by the Spanish Ministry of Science and Innovation.
DS Repositorio Institucional de la Universidad de Burgos
RD 17-abr-2026