Influence of the chemical composition and process parameters on the mechanical properties of an extruded aluminium alloy for highly loaded structural parts

• CAE neural network was proposed for modelling the aluminium hot extrusion.
• Simultaneous analyses of many influential parameters revealed clear relationships.
• Areas of influential parameters with a positive influence on the mechanical properties were indicated.
• Optimized test alloys revealed the improvement of mechanical properties.

The aluminium alloy 6082 (AA6082) is used as a material for highly loaded construction parts, which means any improvement in its mechanical properties would be an advantage. The majority of approaches employed so far for increasing the mechanical properties only considered a small number of influential parameters and assumed that they were predominately independent of each other. In contrast, in this investigation a simultaneous increase in the yield stress and ductility (elongation) was achieved by considering a larger number of influencing parameters. For this purpose, a database of mechanical properties, process parameters and chemical compositions for the hot extruded profiles was collected. Individual and spatial analyses using a CAE neural network were performed to determine the influences of the process parameters and the alloying elements, e.g. Mg, Si, Mn, Fe, Cr and Cu, on the mechanical properties. The results of the analyses provided a new view of their influences, and the possibility to increase the mechanical properties if the process parameters in the relation with the chemical elements are closer to the optimum values. The optimum values of the process parameters and the chemical composition were assessed. In practice, the obtained values for the yield stress and the elongation confirmed the optimized values for the influential parameters as being correct, since a simultaneous increase of both properties was achieved.