Prabhash Kumar Jha, Prabhash Kumar Jha, Inderdeep Singh, Pradeep Kumar Jha, Pradeep Kumar Jha
Drilling process plays a vital role in numerous industries and represents more than one-third of all machining operations. The prime advantage of conventional drilling operations as compared to other hole making techniques is that these enhance output and productivity efficiently, in less time at a reasonable cost. The current research endeavor seeks to optimize the cutting parameters for drilling of in-situ cast Al-4.5%Cu-1.5%Mg-7%TiB2 composite by employing the desirability function and non-dominated sorting genetic algorithm II approach. Considering the objective, the cast composite was drilled using three machining parameters (input); cutting speed, feed rate, and diameter of twist drill, and drilling response characteristics (output); thrust force, mean cutting time and surface roughness were analyzed. Chip morphology and tool wear characteristics have also been analyzed and reported. The mathematical prediction models for thrust force, mean cutting time, and surface roughness were generated using response surface methodology, and results showed that the anticipated and experimental outcomes were in close agreement, indicating the model’s high accuracy. An analysis of variance approach was employed to assess the influence of drilling parameters on the response variables. Compared to response surface methodology-desirability function and non-dominated sorting genetic algorithm II predicted a lower value of optimal thrust force, mean cutting time, and surface roughness with a desirability of 0.9590.