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2006 | Vol. 17, nr 1-2 | 289--292
Tytuł artykułu

Selection method of steel grade with required hardenability

Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: The purpose of this paper is to work out the computer aided method for selecting grades of steel with a required hardenability. Design/methodology/approach: 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 possible to prepare, in the second stage, a representative set of data and to work out the neural classifier that would aid the selection of steel grade with the required hardenability. Findings: The calculations made in the paper have confirmed the purposefulness of applying artificial neural networks for aiding the selection of steel with the required hardenability. Research limitations/implications: The presented system may be used in the range of the accepted in the paper mass concentrations of elements. The methodology demonstrated in the paper makes it possible to add new grades of steel to the system. Practical implications: The worked out model may be used in computer systems of steel selection for the parts of machines exposed to the heat treatment. Originality/value: The use of the artificial neural networks as an aiding tool for selecting the steel with the required hardenability.
Wydawca

Rocznik
Strony
289--292
Opis fizyczny
Bibliogr. 8 poz., tab., wykr.
Twórcy
autor
  • Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, Poland, jacek.trzaska@polsl.pl
autor
  • Division of Materials Processing Technology and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology, ul. Konarskiego 18a, 44-100 Gliwice, 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, 44-100 Gliwice, Poland
Bibliografia
  • [1] L.A. Dobrzański, J. Madejski, W. Malina, W. Sitek, The prototype of an expert system for the selection of high-speed steels for cutting tools, Journal of Materials Processing Technology, v.56, 1-4 (1996) 873-881.
  • [2] L.A. Dobrzański, W. Sitek, Computer Aided Materials Selection System as the Engineering Tool for Machine Part Design, Proceedings of International Conference "Design Tool and Methods in Industrial Engineering, Florence, Italy, 1997, 279-288.
  • [3] L.A. Dobrzański, W. Sitek, J. Madejski Some aspects of materials selection in machine design, International Scientific Conference ”Mechanics in Design” MID’98, Notthingham, Great Britain, 1998, 10-17.
  • [4] L.A. Dobrzański, J. Trzaska, Application of neural networks for prediction of critical values of temperatures and time of the supercooled austenite transformations, Journal of Materials Processing Technology, 155-156 (2004) 1950.
  • [5] L.A. Dobrzański, J. Trzaska, Application of neural networks for prediction of hardness and volume fractions of structural components in constructional steels cooled from the austenitizing temperature, Material Science Forum, 437–438 (2003) 359-362.
  • [6] L.A. Dobrzański, W. Sitek, Designing of the chemical composition of constructional alloy steels, Journal of Materials Processing Technology, 89-90 (1999) 467-472
  • [7] L.A. Dobrzański, W. Sitek, Comparison of hardenability calculation methods of the heat treatable constructional steels Journal of Materials Processing Technology, v.64 (1997) 117-126
  • [8] L.A. Dobrzański, W. Sitek, Application of neural network in modelling of hardenability of constructional steels, Journal of Materials Processing Technology, 78 (1998) 59-66.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-50f009e9-b587-4890-a37b-fb43d8368f9b
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