Purpose: This paper presents Neuro-Lab. It is an authorship programme, which use algorithms of artificial intelligence for structural steels mechanical properties estimation. Design/methodology/approach: On the basis of chemical composition, parameters of heat and mechanical treatment and elements of geometrical shape and size this programme has the ability to calculate the mechanical properties of examined steel and introduce them as raw numeric data or in graphic as influence charts. Possible is also to examine the dependence among the selected steel property and chosen input parameters, which describes this property. Findings: There is no necessity of carrying out any additional material tests. The results correlations between calculated and measured values are very good and achieve even the level of 98%. Practical implications: Presented programme can be an effective replace of the real experimental methods of properties determination in laboratory examinations. It can be applied as the enlargement of experimental work. Possible is also the investigation of models coming from new steel species, that wasn’t produced yet. Originality/value: The ability of the mechanical properties estimation of the ready, or foreseen to the use, material is unusually valuable for manufacturers and constructors. This signifies the fulfilment of customer’s quality requirements as well as measurable financial advantages for material manufacturers.
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