Title :
Intelligent operating conditions design by means of bio-inspired models
Author :
Villar, J.R. ; Sedano, J. ; Corchado, Emilio ; Vera, Vicente ; Hernando, Blanca ; Redondo, R.
Author_Institution :
Comput. Sci. Dept., Univ. of Oviedo, Gijon, Spain
Abstract :
This study presents a novel hybrid intelligent system, which focuses on the optimisation of machine parameters for dental milling purposes. The basis of this approach is hybridizing two bio-inspired algorithms, as Neural Networks with Genetic Algorithms for choosing and modelling the feature subset that best descript the operation conditions. These operating conditions are given as parameters for a dental drill machine. The aim of this approach is twofold: a feature selection process is carried out while the modelling of the operating conditions is achieved. The reliability of the proposed novel hybrid system is validated with a real industrial use case, based on the optimisation of a high-precision machining centre with five axes for dental milling purposes.
Keywords :
drilling; genetic algorithms; milling; neural nets; production engineering computing; bio-inspired models; dental drill machine; dental milling purposes; feature selection process; genetic algorithms; hybrid intelligent system; intelligent operating conditions; neural networks; Artificial neural networks; Biological system modeling; Computational modeling; Data models; Dentistry; Genetic algorithms; Manufacturing; Bio-inspired Systems; Genetic Algorithms; Neural Networks; Optimising Operating Conditions;
Conference_Titel :
Nature and Biologically Inspired Computing (NaBIC), 2011 Third World Congress on
Conference_Location :
Salamanca
Print_ISBN :
978-1-4577-1122-0
DOI :
10.1109/NaBIC.2011.6089731
