Contour Maps for Simultaneous Increase in Yield Strength and Elongation of Hot Extruded Aluminum Alloy 6082

In this paper, the Conditional Average Estimator artificial neural network (CAE ANN) was used to analyze influence of chemical composition in conjunction with selected process parameters on yield strength and elongation an extruded 6082 aluminum alloy (AA6082) profile. Analysis focused optimization mechanical properties as a function casting temperature, speed, addition rate wire, ram extrusion ratio, number strands one side, different contents elements, i.e., Si, Mn, Mg, Fe, other side. The obtained results revealed very complex non-linear relationships between all these parameters. Using proposed approach, it possible identify combinations well their values for simultaneous increase profiles. These are contribution presented study comparison published research similar studies field. Application either and/or industrial production, suggests further relevant properties.