ASSESSING THE EFFICACY OF ADVANCED OPTIMIZATION TECHNIQUES FOR TITANIUM CUTTING SURFACE OPTIMIZATION

Abstract

This study investigates the effectiveness of advanced optimization techniques in enhancing the cutting surface quality of titanium, a material known for its high strength-to-weight ratio and corrosion resistance. The research evaluates various optimization methods, including genetic algorithms, simulated annealing, and particle swarm optimization, to determine their impact on cutting surface parameters such as roughness, wear resistance, and tool life. Experimental trials were conducted using state-of-the-art machining processes, where parameters were systematically varied to identify the optimal cutting conditions. Results indicated significant improvements in surface quality and tool performance when applying these advanced techniques compared to conventional methods. The findings contribute valuable insights into the optimization of titanium machining processes, enabling manufacturers to enhance product quality and reduce production costs.