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The multi-directional forging process of aluminium alloy 7075 (AA 7075) is studied using Deform 3D Version 11.0 simulation software. This process results in grain refinement in the bulk material. The 7075 aluminium alloy is used widely in the aerospace and automobile industries. Thermomechanical processing affects the mechanical properties of this alloy. This study focuses on optimising process parameters that affect the multi-directional forging using simulation. In the Taguchi design of experiment, four-factors and five levels are selected. The process input parameters considered are temperature, the strain per pass, the plunger speed, and the friction coefficient (μ). From Taguchi’s orthogonal array, forging simulations are undertaken and analysed. The significance of the process output parameters: material damage, stress and strain are analysed by analysis of variance. The results show that the friction coefficient and strain per pass highly affect the stress/strain distribution. Grey relational analysis is adopted to determine the optimum process parameters. The results show that the optimal combination of parameters is: temperature (200 °C), plunger speed (5 mm/s), friction coefficient (0.6), and strain per pass (0.6). Confirmation of simulation is carried out using the optimum input parameters. From the simulation results, the grey relational grade's optimal parameters have the highest maximum effective strain of 5.57, maximum effective stress of 665 MPa, and maximum damage of 0.416 compared to other simulated results.

The Taguchi optimization technique was utilized to determine the optimal milling parameters that can be used in end face CNC milling operation of polypropylene+5wt.% quarry dust using high-speed steel (HSS) tool. Three milling input parameters i.e. the feed rate (f), the cutting speed of the spindle (N) and the depth of cut (dc) were optimized while considering the surface roughness (Ra) of the machined composite material and the material removal rate (MRR) during machining as the responses of the experimental design. From the results, the cutting speed (100 rpm) and the feed rate (120 mm/min) were the most important control parameters which greatly influence the surface roughness at 41.4% and 28.8% contribution respectively. In the case of the material removal rate, the depth of cut (0.8 mm) was the dominating factor at 98% contribution.

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