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1 Journal of Achievements in Materials and Manufacturing Engineering

1 2009

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Application of artificial neural networks in modelling of normalised structural steels mechanical properties

Dobrzański L. A., Honysz R.

Journal of Achievements in Materials and Manufacturing Engineering

2009

Vol. 32, nr 1

37-45

Purpose: This paper presents the application of artificial neural networks for mechanical properties prediction of structural steels after heat treatment. Design/methodology/approach: On the basis of such input parameteres, which are the chemical composition, the kind of mechanical and heat treatment and dimensions of elements, mechanical properties, such as strength, impact resistance or hardness are predicted. Findings: Results obtained in the given ranges of input parameters show very good ability of constructed neural networks to predict described mechanical properties for steels after heat treatment. The uniform distribution of descriptive vectors in all, training, validation and testing sets, indicate about the good ability of the networks to results generalisation. Practical implications: Created tool makes possible the easy modelling of described properties and allows the better selection of both chemical composition and the processing parameters of investigated materials. At the same time the obtainment of steels, which are qualitatively better, cheaper and more optimised under customers needs is made possible. Originality/value: The prediction possibility of the material mechanical properties is valuable for manufacturers and constructors. It allows preserving the customers quality requirements and brings also measurable financial advantages.