The aim of this study was to optimize machining parameters to obtain the smallest average surface roughness (Ra) and flank wear (Vb) values as a result of the surface milling of a nickel-titanium (NiTi) shape memory alloy (SMA) with uncoated cutting tools with different nose radius (r_ε) under dry cutting conditions. Tungsten carbide cutting tools with different r_ε (0.4 mm and 0.8 mm) were used in milling operations. The milling process was performed as lateral/surface cutting at three different cutting speeds (V_c) (20, 35 and 50 m/min), feed rates (f_z) (0.03, 0.07 and 0.14 mm/tooth) and a constant axial cutting depth (0.7 mm). The effects of machining parameters in milling experiments were investigated based on the Taguchi L18 (2¹ × 3²) orthogonal sequence, and the data obtained were analyzed using the Minitab 17 software. To determine the effects of processing parameters on Ra and Vb, analysis of variance (ANOVA) was used. The analysis results reveal that the dominant factor affecting the Ra is the cutting tool r_ε, while the main factor affecting Vb is the f_z. Since the predicted values and measured values are very close to each other, it can be said that optimization is correct according to the validation test results.

Cryogenic treatment has been used in recent years to improve the performance of cutting tools. This study evaluated the machinability of a nickel–molybdenum-based super alloy using cryogenically treated (–80 ℃ and –145 ℃) ceramic inserts under dry turning conditions. Three cutting speeds (350, 400, and 450 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev), and a 1-mm fixed cutting depth were used in the turning tests. Experiments were conducted using the Taguchi orthogonal array L₂₇ design. The factors affecting the surface roughness (Ra) were determined via analysis of variance. The effect of cryogenic treatment type (shallow and deep), cutting speed, and feed rate on surface roughness was investigated. Results of the analysis determined that the feed rate was the major parameter that affected surface roughness and that the deep cryogenic treatment was more effective. The regression analysis confirmed that the experimental results and the predicted values were within the 95% confidence interval. The most effective parameter affecting the surface roughness was feed rate at a contribution of 57.9%. The contribution of the cutting tool type to the surface roughness was 28.5%. The results obtained showed that the surface roughness can be optimized for turning the Hastelloy c22 super alloy with the Taguchi method.