Project of neural network for steel grade selection with the assumed CCT diagram

• Autorzy: Dobrzański L. , Malara S. , Trzaska J.
• Języki publikacji: PL

Abstrakty

EN

Purpose: The aim of this paper was developing a project of neural network for selection of steel grade with the specified CCT diagram - structure and of harness after heat treatment. Design/methodology/approach: The goal has been achieved in the following stages: at the first stage characteristic points of CCT diagram have been determined. At the second stage neural network has been developed and optimized. Findings: The neural network was developed in this paper, that allowed selection of steel grade with the assumed CCT diagram. Research limitations/implications: Created method for designing chemical compositions is limited by the established ranges of mass concentrations of elements. The methodology demonstrated in the paper makes it possible to add new steel grades to the system. Practical implications: The method worked out may be used in computer steel selection systems for the machine parts put to heat treatment. Originality/value: Presented computer aided method makes use of neural networks, and may be used for selecting the steel with the required structure after heat treatment.

Słowa kluczowe

PL

komputerowa nauka o materiałach; metody sztucznej inteligencji; wykres CCT

EN

computational material science; artificial intelligence methods; CCT diagram

• Wydawca: International OCSCO World Press
• Czasopismo: Journal of Achievements in Materials and Manufacturing Engineering
• Rocznik: 2008
• Tom: Vol. 27, nr 2
• Strony: 155--158
• Opis fizyczny: Bibliogr. 16 poz., wykr.

Twórcy

autor

Dobrzański L.

autor

Malara S.

autor

Trzaska J.

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

Bibliografia

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