Exploring the Impact of the Turning of AISI 4340 Steel on Tool Wear, Surface Roughness, Sound Intensity, and Power Consumption under Dry, MQL, and Nano-MQL Conditions

Optimizing input parameters not only improves production efficiency and processing quality but also plays a crucial role in the development of green manufacturing engineering practices. The aim of the present study is to conduct a comparative evaluation of the cutting performance and machinability process during the turning of AISI 4340 steel under different cooling conditions. The study analyzes cutting operations during turning using dry, minimum quantity lubrication, and nano- minimum quantity lubrication. As control parameters in the experiments, three different cooling types, cutting speeds (100, 150, 200 m/min), and feed rate (0.1, 0.15, 0.20 mm/rev) levels were applied. The experimental results show that the optimal output values are found to be Vb = 0.15 mm, Ra = 0.81 mu m, 88.1 dB for sound intensity and I = 4.18 A for current. Moreover, variance analysis was performed to determine the effects of input parameters on response values. Under dry, minimum quantity lubrication, and nano-minimum quantity lubrication processing conditions, parameters affecting tool wear, surface roughness, current by the motor shaft, and sound level were examined in detail, along with the chip morphology. The responses obtained were optimized according to the Taguchi S/N method. As a result of optimization, it was concluded that the optimum values for cutting conditions were nano-minimum quantity lubrication cooling and V = 100 m/min, f = 0.1 mm/rev cutting. Finally, it was observed that there was a 13% improvement in tool wear, 7% in current, 9% in surface roughness, and 8% in sound intensity compared to the standard conditions. In conclusion, it was determined that nano-minimum quantity lubrication with the lowest level of cutting and feed rate values provided the optimum results.