Optimization of CNC Turning Parameters for Surface Roughness and Tool Wear in Machining Inconel-718 Using Response Surface Methodology (RSM)

Abstract

Inconel-718, a nickel-based superalloy widely used in aerospace and nuclear applications due to its superior mechanical properties, high-temperature resistance, and corrosion resistance. Despite these advantages, the low machinability of Inconel-718 presents challenges in achieving high surface quality and minimizing tool wear. The objective of this research is to optimize the CNC turning process for Inconel-718 by analyzing the effects of cutting speed and feed rate on surface roughness and tool wear. The study aims to identify the optimal machining parameters that produce a smoother surface finish while minimizing tool wear. Using RSM, cutting speed and feed rate were optimized through a systematic experimental design conducted on a Doosan LYNX 220L CNC lathe machine with TiAIN-coated carbide cutting tools. The cutting speeds ranged from 20.0 m/min to 120 m/min, while feed rates varied between 0.03 mm/rev and 0.1 mm/rev. The ANOVA results showed that the models for surface roughness and tool wear were significant, with p-values of 0.0159 and 0.0037, respectively. The R² values were close to 1, confirming the reliability of the model. ANOVA suggested a linear model because the relationship between cutting parameters and the resulting outcomes (surface roughness and tool wear) was almost direct, with no complex interactions requiring a more intricate model.  Numerical optimization revealed the optimal cutting parameters to be a cutting speed of 20.0 m/min and a feed rate of 0.030 mm/rev, achieving a surface roughness of 0.441 µm and tool wear of 2.975 µm. The linear model used in this study showed that feed rate had a more significant influence on surface roughness, while cutting speed had a greater effect on tool wear. This study delivers critical advancements in optimizing the machining of Inconel-718, significantly enhancing process efficiency, minimizing machining errors, and improving surface integrity paving the way for higher precision and productivity in the manufacturing of hard-to-machine materials.