Intelligent models and simulation to optimise industrial processes

• Roberto Vega Ruiz ^[1] ; Héctor Quintián Pardo ^[1] ; Emilio Corchado Rodríguez ^[1]
  1. [1] Department of Computer Science, University of Salamanca
• Localización: Avances en Informática y Automática. Séptimo Workshop / coord. por Juan Cruz Benito, Alicia García Holgado, S. García, Daniel Hernández Alfageme, María Navarro Cáceres, Roberto Vega Ruiz, 2013, ISBN 84-695-8670-X, págs. 163-176
• Idioma: inglés
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• Resumen

  • This study presents a novel Intelligent System based on theapplication of Soft Computing Models and Identification Systems, whichmakes possible to optimise industrial processes, such as a dental millingprocess. The main goal is the optimization of some parameters as time.This novel intelligent procedure is based on two steps. Firstly, statisticaltechniques and unsupervised learning are used to analyse the internalstructure of the data set and the identification of the most relevant variables. Secondly, the most those variables are used to model the systemusing supervised learning such as artificial neural networks and supportvector machines. The model has been succesfully tested using an industrial real data set.