Application of Desirability Approach for Muti-response Optimization of Machining Parameters of an Age-hardened AA2024 Hybrid Composite using RSM

Abstract

Composite materials have been confronted for machining because hybrid composite materials contain the hard particles of reinforcement, culminating in the failure of cutting tools during the machining process with large cutting forces. The machining of these novel materials to achieve better design includes lower cutting forces, roughness, and more metal removal rate. The present research work shows cutting forces, metal removal rate (MRR), and surface roughness values while turning age-hardened AA2024 hybrid composites. The optimized age-hardened AA2024 hybrid composite consists of 15% fly ash and 4.2865% nano red mud. Dry machining conditions are followed, and the required parametric studies have been carried. The turning process is carried out with a cutting speed of 200 m/min to 460 m/min, feed of 0.5 mm/rev to 1mm/rev in the step of 0.5mm/rev using a depth of cut from 0.75 mm to 1.25mm with a step of 0.25 mm. During machining, cutting forces on the workpiece are examined, MRR and Surface roughness are calculated for the machined component at different machining conditions. A Muti-response optimization was carried out for this machining characteristic with α value of ± 1 with user-defined runs. A 3D plot examined the interactive and individual effect of machining parameters on the responses. Feed rate had a notable influence on the surface roughness (Ra), with a contribution percentage of 96.59 percentage. For material removal rate (MRR), the feed rate has a meager influence compared with cutting speed and depth of cut with a contribution percentage of 52.69 and 38.68 percent, respectively.