Prediction of technological parameters during polymer material grinding

  • Authors:

  • David Samek;Ondrej Bilek;Jakub Cerny

  • Affiliations:

  • Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Zlin, Czech Republic;Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Zlin, Czech Republic;Department of Production Engineering, Faculty of Technology, Tomas Bata University in Zlin, Zlin, Czech Republic

  • Venue:
  • ACMOS'11 Proceedings of the 13th WSEAS international conference on Automatic control, modelling & simulation
  • Year:
  • 2011

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Abstract

This article introduces an application of artificial neural network with radial basis function in modeling of polymer materials grinding. This real technological process has many input parameters that influence results of grinding. In this paper the two key parameters were selected -- feed rate and depth of cut. The task of the artificial neural network based predictor is to provide resulting surface roughness (Ra and Rz).