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Abstract

The present work focuses on the modeling and analysis of mechanical properties of structural steel. The effect of major alloying elements namely carbon, manganese and silicon has been investigated on mechanical properties of structural steel. Design of experiments is used to develop linear models for the responses namely Yield strength, Ultimate tensile strength and Elongation. The experiments have been conducted as per the full factorial design where all process variables are set at two levels. The main effect plots showed that the alloying elements Manganese and Silicon have positive contribution on Ultimate tensile strength and Yield strength. However, Carbon and Manganese showed more contribution as compared to Silicon. All three alloying elements are found to have negative contribution towards the response- Elongation. The present work is found to be useful to control the mechanical properties of structural steel by varying the major alloying elements. Minitab software has been used for statistical analysis. The linear regression models have been tested for the statistical adequacy by utilizing ANOVA and statistical significance test. Further, the prediction capability of the developed models is tested with the help of test cases. It is found that all linear regression models are found to be statistically adequate with good prediction capability. The work is useful to foundrymen to choose alloying elements composition to get desirable mechanical properties.
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Abstract

This work presents the project of the application of Case-based reasoning (CBR) methodology to an advisory system. This system should give an assistance by selection of proper alloying additives in order to obtain a material with predetermined mechanical properties. The considered material is silumin EN AC-46000 (hypoeutectic Al-Si alloy) that is modified by the addition of Cr, Mo, V and W elements in the range from 0% to 0.5% in the modified alloy. The projected system should indicate to the user the content of particular additives so that the obtained material is in the chosen range of parameters: tensile strength Rm, yield strength Rp0.2, elongation A and hardness HB. The CBR methodology solves new problems basing on the solutions of similar problems resolved in the past. The advantage of the CBR application is that the advisory system increases knowledge base as the subsequent use of the system. The presented design of the advisory system also considers issues related to the ergonomics of its operation.
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