Title: Application of neural networks for selection of steel grade with required hardenability

Authors: Jacek Trzaska, Wojciech Sitek, Leszek A. Dobrzanski

Addresses: Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, Gliwice 44-100, Poland. ' Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, Gliwice 44-100, Poland. ' Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, Gliwice 44-100, Poland

Abstract: This paper presents the application of artificial neural network for the selection of steels| grades with a required hardenability. The purpose has been achieved in two stages. In the first stage, a neural network model for calculating the Jominy curve on the basis of the chemical composition has been worked out. This model made it possible to prepare, in the second stage, a representative set of data and to work out the neural classifier for the selection of steel grade with the required hardenability. The methodology presented in this paper makes it possible to add new grades of steel to the system. The worked out model may be used in computer systems of steel selection for the heat-treated machine parts. [Received 15 April 2006; Accepted 15 March 2007]

Keywords: analysis; modelling; computational materials science; metallic alloys; artificial intelligence; hardenability; artificial neural networks; ANNs; steel grade selection.

DOI: 10.1504/IJCMSSE.2007.016430

International Journal of Computational Materials Science and Surface Engineering, 2007 Vol.1 No.3, pp.366 - 382

Published online: 28 Dec 2007 *

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