Utilisation of fuzzy logic and genetic algorithm to seek optimal corrugated die design for CGP of AZ31 magnesium alloy

Magnesium alloys are the first choice among other lightweight structural metals like aluminium, titanium and beryllium due to low density and excellent corrosion resistance. However, low slip and cold plastic processing ability limits its applications. Constrained groove pressing (CGP), one among the SPD techniques, is well suited for improving the material properties. Corrugated dies are designed to investigate the deformation behaviour of AZ31 Mg alloy samples. To minimise the number of numerical simulations, Taguchi's L9 orthogonal array is selected for the grooved die dimensions (viz. groove angle, groove width and coefficient of friction). Elasto-plastic finite element analysis is performed by implementing a multi-criterion-based genetic algorithm optimisation tool for obtaining the optimal die geometry. Reduction in total deformation, increase in the equivalent stress and elastic strain of AZ31 sheet were possible with 50° groove angle, 3 mm groove width and 0.22 friction coefficient. Mamdani-based fuzzy logic soft computing tool is implemented for the model to examine the deformation behaviour of AZ31 Mg alloy. 7.86 % deviation is observed in the fuzzy logic model predictions in comparison with simulation results. The suggested die design is well suitable for multiple CGP passes, to improve the grain refinement in the processed sheet.