Experimental investigation and optimization on machinability aspects of aluminium alloy AA7068 in dry turning using deep learning technique
Findings revealed that increasing cutting speed led to significant escalation in flank and crater wear, while chip thickness and surface roughness decreased, and an increase in machining parameters resulted in heightened tool vibration, cutting temperature, power consumption, and sound intensity.