Investigation and optimization of machining responses in CNC turning of aluminium 6061 T6

Mechanical Engineering

This study investigates and optimizes the machining responses during CNC turning of aluminium 6061-T6, a material favored in industries like aerospace and automotive for its machinability and strength. The research specifically examines the influence of cutting speed, feed rate, and depth of cut on key performance metrics such as surface roughness. Using the Taguchi method, an L9 orthogonal array was employed to design the experiments, reducing the number of trials while ensuring comprehensive analysis. The experimental results indicated that feed rate was the most significant factor affecting surface roughness, with higher feed rates leading to an increase in roughness. For example, at a cutting speed of 370 m/min, feed rate of 0.25 mm/rev, and depth of cut of 1.0 mm, the surface roughness reached 9.48 µm. Conversely, the best surface finish of 0.85 µm was achieved at a cutting speed of 370 m/min, feed rate of 0.05 mm/rev, and depth of cut of 1.5 mm. Further optimization using Teaching-Learning-Based Optimization (TLBO) identified the optimal parameters for minimizing surface roughness: a cutting speed of 370 m/min, feed rate of 0.05 mm/rev, and depth of cut of 0.5 mm, resulting in a surface roughness of 0.7785 µm. This combination of Taguchi method and TLBO effectively enhances the precision and cost-efficiency of CNC turning operations, providing actionable insights for manufacturing industries seeking to optimize machining processes

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