OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 5 4 3 The power consumption and flank wear are plotted using the developed theoretical models, Eqs. 1 and 2, varying the cutting speed, vibration frequency, and amplitude. Fig. 7, a depicts the variation in the power consumption and flank wear with the cutting speed at constant vibration frequency and amplitude of 20 kHz and 20 µm, respectively. a b c Fig. 7. Power consumption and flank wear varying with cutting speed (a), frequency of vibration (b), amplitude of vibration (c) Fig. 7, b depicts the variation in the power consumption and flank wear with the vibration frequency at constant cutting speed and vibration amplitude of 100 m/min and 20 µm, respectively. Fig. 7, c shows the variation in the power consumption and flank wear with the vibration amplitude at constant cutting speed and vibration frequency of 100 m/min and 20 kHz, respectively. The power consumption increases with the cutting speed, vibration frequency, and amplitude. However, an increase in the power consumption can be seen as prominently with the cutting speed followed by vibration frequency, and amplitude. This can be also confirmed from the higher values of the exponent observed for the cutting speed followed by vibration frequency, and amplitude. The flank wear can be seen as increasing with the cutting speed and vibration amplitude and decreasing with the frequency of vibration. Conclusion This study comparatively evaluates the tool wear and power consumption during conventional turning (CT) and ultrasonic vibration-assisted hard turning (UVAHT) of AISI 52100 steel (62 HRC) using a PVD-coated TiAlSiN carbide tool. A theoretical model to predict the tool wear and power consumption is developed using the concept of Dimensional analysis, i.e., the Buckingham Pi theorem considering the effect of cutting speed, frequency, and amplitude of vibrations. Dimensionless groups are created to reveal complex linkages and optimize machining conditions. Tool wear and power consumption are measured experimentally and statistically analysed using the Buckingham Pi theorem. The following conclusion can be drawn from the present study. 1. Tool wear is significantly affected by the cutting speed. How, this effect is more prominent with conventional turning (CT). This could be attributed to an increase in the cutting temperature during cutting.
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