1.1 Comparison of cryogenic cutting with flooded and dry machining
The objective of this section is to determine any difference in variation of cutting force, flank wear and surface roughness with cutting speed and feed rate when LN2 is applied to the cutting edge in comparison to conventional flooded cutting. In addition, since cryogenic cutting is considered as a type of dry cutting method, the results were also compared to dry machining.
1.1.1 Effect of cutting parameters on cutting force under different cutting conditions
Figure 4a, b shows the variation of cutting force values in terms of cutting speed and feed rate under cryogenic, flooded and dry conditions. A minimum value of cutting force (90 N) was seen at 70 m/min cutting speed (Figure 4a). This is because of the fact that by increasing the cutting speed to a specific value, flow stress of the workpiece material decreases as a result of increase in the cutting temperature which outperforms the strain hardening effect that increases with cutting speed. Pawade et al.  investigated the turning of Inconel 718 and showed that after a critical speed (60 m/min), the effect of increase in cutting temperature on the flow stress is more significant than strain hardening. However, further increase in the cutting speed led to higher cutting force. This can be attributed to increase in strain rate hardening when cutting speed is increased. This was confirmed by Iturbe et al.  in their study on the machining behaviour of Inconel 718 in which they showed that high strain rate hardening coupled with high cutting temperatures at higher cutting speeds results in high cutting forces.
Figure 4b shows that by increasing feed rate, cutting force constantly increased. This is due to increase in uncut chip thickness by increasing feed rate, which in turn, increases the normal load on the tool rake face, resulting in higher friction force and consequently higher cutting force . Variation of cutting force with cutting time at different feed rates under cryogenic and flooded cutting is shown in Figure 5. At the feed rate of 0.01 mm/rev under cryogenic cutting (Figure 5a), there was a large variation in cutting force values which was resulted from the fracture of the tool nose and occurrence of large chipping in the minor cutting edge (Section 3.1.2), which in turn, resulted in high surface roughness (Section 3.1.3) at this condition. Cutting force value was smaller (90 N) and more stable at feed rate of 0.05 mm/rev (Figure 5b) under cryogenic cutting, compared to 0.01 and 0.09 rev/min. On the contrary, cutting force had an increasing trend at the feed rate of 0.09 mm/rev (Figure 5c) and after 4s cutting tool started to vibrate which is shown by fluctuation in the cutting force values in Figure 5c. Generally, flooded cutting had more stability in the variation of cutting force with time and tool vibration was less than that of cryogenic cutting.
1.1.2 Effect of cutting parameters on flank wear under different cutting conditions
Figure 6a, b shows the variation of average flank wear values with cutting speed and feed rate under cryogenic, in comparison with flooded and dry cutting conditions. Flank wear values were recorded according to ISO 3685:1993 standard by measuring the average and maximum flank wear land in the region B and minor flank face . The measurements were done at least in 10 spots and the average values are reported. Flank wear increased with increase in cutting speed as shown in Figure 6a. This is because of increase in cutting temperature which reduces the strength of the tool material promoting abrasion which facilitates the adhesion of workpiece material and formation of built-up edge (BUE) .
Figure 6b shows that at the feed rate of 0.01 mm/rev under cryogenic condition, wear value was high due to tool failure in the side cutting edge because of high chipping (Figure 7 a, b). Under dry cutting at low feed rate of 0.01 mm/rev (Figure 6b), high flank wear in the form of chipping could also be observed (Figure 7 e, f). Catastrophic failure of the cutting edge during cryogenic cutting was also reported in previous studies; Pusavec et al.  observed catastrophic failure on the cutting edge during the cryogenic cutting of Inconel 718 when comparing it with dry, MQL and CryoMQL conditions.
By increasing the feed rate to 0.05 mm/rev, At a higher feed rate of 0.09 mm/rev, flank wear value dropped significantly to 60 which was as low as that of flooded cutting, while dry cutting still resulted in high flank wear value of 100 (Figure 6b). Chipping was still observed under cryogenic cutting at this parameter, but in smaller amount (Figure 8 b). Adhesion wear mechanism was promoted at 0.05 mm/rev feed rate under cryogenic and flooded conditions which resulted in larger BUE formations (Figure 8 a-d).
Flank wear value did not change significantly compared to that of at 0.05 mm/rev (Figure 6b). However, under cryogenic condition, tool wear mechanism changed - chipping was not happened on the major and minor cutting edges under cryogenic cutting (Figure 9 a, b), however, another wear mechanism, namely depth of cut (DOC) notch was seen in the minor and major cutting edges. Abrasion and adhesion were other wear mechanisms observed during the cutting of Inconel 718 at different feed rates (Figure 7 - Figure 9). Adhesion of workpiece material on the cutting edge was high under cryogenic cutting which resulted in formation of BUE at all the feed rates. Zhuang et al.  reported similar results in which high adhesion and built-up edge (BUE) were observed in cryogenic cutting of Inconel 718 when comparing the results with plasma-enhanced machining (PEM). Flank wear values were almost the same for cryogenic and flooded conditions at all cutting parameters while dry cutting resulted in higher flank wear at all the cutting parameters.
1.1.3 Effect of cutting parameters on Ra surface roughness under different cutting conditions
Figure 10a, b shows variations of Ra surface roughness with cutting speed and feed rate under different cutting conditions. Effect of cutting speed on surface roughness depends on the variation of the cutting force with speed - as cutting speed increased from 20 m/min to 70 m/min, cutting force first decreased to a minimum value (0.5 – 0.6 μm) and increased again at the speed of 120 m/min by increasing in the cutting force (Figure 4a).
Figure 10b shows that high values of Ra (1.65 µm) were observed at low feed rate (0.01 mm/rev) when cutting was carried out using LN2 due to tool failure at this parameter (Figure 7b). Flooded cutting resulted in lower Ra (0.32 µm) at this parameter because cutting force was low (Figure 4b) and the cutting edge was retained its original shape (Figure 7c, d).
Generally, surface roughness was lower under flooded than cryogenic cutting condition. This can be attributed to brittleness of the workpiece material under cryogenic condition which created more vibration during the cutting process (Figure 5a-c). Similar results were reported by Tebaldo et al. . They compared MQC with dry and flooded cutting and reported that the lowest magnitude of surface roughness when flood turning was obtained compared to cryogenic cutting.
Produced workpiece surface quality under cryogenic and flooded cutting conditions were closely investigated by SEM (Figure 11a, b). Figure 11a shows surface quality produced while LN2 was applied during the cutting process at different feed rates. At low feed rate (0.01 mm/rev), at which the tool failed, formation of cavities and high built-up layers (BUL) resulted in high roughness value (1.7 µm) and poor surface quality. Side flow and BUL were observed at high feed rate (0.09 mm/rev) in lesser extent than 0.01 mm/rev, but the roughness value was still high (1.4 µm). Side flow is the result of high pressure on the workpiece material left behind on the on the secondary cutting edge of the tool . It has been shown that side flow can be zero for brittle materials . At the medium feed rate (0.05 mm/rev), however, the surface defects such as groove and BUL were less prominent and the roughness value dropped to 0.6 µm, resulting in good surface quality, which was comparable to the one produced under flooded cutting as shown in Figure 11b. Under flooded cutting surface quality was consistent whereby there were no dramatic change in formation of surface defects at different cutting parameters like the one happened in cryogenic cutting. However, the surface roughness increased with feed rate (Figure 11b) because of formation of larger feed marks. Therefore, surface quality and formation of surface defects when LN2 was sprayed to the cutting area was highly dependent on the feed rate at which the machining process was carried out. On the opposite, there was a consistency in formation of surface defects under flooded cutting at various cutting speed and feed rates.
1.2 Statistical analysis and optimization of cutting parameters in cutting Inconel 718 using LN2 by RSM
Experimental results in section 3.1 indicated that there can be a set of parameters in which machinability of Inconel 718 in terms of tool wear, cutting force and surface quality can be improved without using flooded machining. In order to find the optimum cutting parameters under cryogenic cutting condition response surface methodology (RSM) was utilized. Cutting speed, feed rate and depth of cut were selected as the process parameters (Table 1) and flank wear, cutting force, Ra surface roughness and material removal rate (MRR) were considered as the response parameters for multi-objective optimization process using desirability function. Material removal rate (MRR) is defined as Cc x f x αp.
Experimental results of machining of Inconel 718 using LN2 according to RSM experimental design arrangement are summarized in Table 2. The effect of cutting parameters on the response parameters were investigated by 3D surface graphs and statistical analyses such as ANOVA so as to determine the most significant parameters on each response factor.
Table 1 Cutting parameters and their levels
|Cutting speed, Vc (m/min)
|Feed rate, f (mm/rev)
|Depth of cut, ap (mm)
Table 2 Experimental results after machining of Inconel 718 using LN2.
* C: Central point, A: Axial point, F: Factorial point
1.2.1 Effect of cutting parameters on cutting force
Quadratic regression model developed for the cutting force is presented in Eq. 1 R2 and R2 -adjusted values of the model were calculated as 88.17% and 82.69%.
Normal probability plot of the residuals (Figure 12a) and histogram of standardized residuals (Figure 12b) for cutting force show that residuals are distributed normally around zero which shows the adequacy of the developed model.
Analysis of variance (ANOVA) for cutting force is presented in Table 3. In this table, DF is degree of freedom which is one for each parameter, SS is sum of squares which is a statistical technique to determine the variation of data point compared to the line of best fit, MS is mean square which is defined as SS/DF, MSE is mean square of error. F-value is calculated as MS/MSE which is used to determine whether the test is statistically significant, meaning the results are meaningful and not gained by random . For this purpose, probability value (P-value) is calculated. P-value is defined as the smallest level of significance (α=0.05) that would lead to rejection of the null hypothesis which is that the average value of the dependent variable is the same for all groups . In other words, when the P-value of a variable is less than 0.05, it can be stated with the 95% of confidence that the variable is statistically significant and when the P-value of a variable is between 0.5 and 0.1, the variable is considered marginally significant . P-value analysis for the cutting parameters in Table 3 showed that cutting speed (P-value= 0.011) was the only statistically significant parameter for cutting force. Feed rate (P-value=0.122) had a marginally significant effect on cutting force.
Table 3 Results of ANOVA for cutting force
* Significant variables
3D surface graph for interaction effect of the cutting parameters is shown in Figure 13a, b. Increase in cutting speed first reduced the cutting force and then increased it. Cutting force constantly increased with increase in feed rate and depth of cut (Figure 13b).
1.2.2 Effect of cutting parameters on flank wear
The experimental data were used for developing a quadratic regression model in terms of flank wear using Box-Cox transformation (λ = 0) which is presented in Eq. 2.
Coefficient of determination, R2 and R2 -adjusted of the model was calculated as 92.17% and 85.13% which confirmed the effectiveness of the model. Figure 14a, b shows the normal probability plot of the residuals for flank wear in which the data closely fall on the straight line indicating that the errors are distributed normally . This also can be seen in Figure 14b in which histogram of residuals for flank wear shows distribution around the zero value.
ANOVA for flank wear in Table 4 shows that all the parameters had statistically significant effect on flank wear as the P-values are less than 0.05. Cutting speed with the P-value of 0.001 for Vc and 0.000 for V2c was a highly significant variable. In addition, F-values of cutting speed showed that it was the most influential parameter on flank wear.
Table 4 Results of ANOVA for flank wear
Effect of cutting speed on flank wear also can be observed in Figure 15. Flank wear increased significantly with the cutting speed especially at the lower feed rates and high depth of cuts. At high cutting speed of 120 m/min, flank wear first decreased to a minimum value of 180 µm at the feed rate of 0.06 mm/rev and then increased exponentially to 410 µm.
1.2.3 Effect of cutting parameters on Ra surface roughness
Regression model for predicting Ra surface roughness was developed using Box-Cox transformation (λ=2) (Eq. 3). Coefficient of determination, R2 and R2- adjusted of the developed model were calculated as 82.52% and 66.72%.
Normal probability plot (Figure 16a) and histogram of standardized residual (Figure 16b) showed that the residuals were distributed around zero which confirmed that the developed model was adequate. F-values and P-values of feed rate and depth of cut presented in Table 5 showed that these parameters were statistically significant for Ra surface roughness.
Table 5 Results of ANOVA for Ra surface roughness
* Significant variables
Figure 17a shows the variation of Ra surface roughness with cutting speed and feed rate. At low feed rates, Ra values were high (1.4 µm) which was because of high tool wear as a result of chipping (Figure 7). However, by increasing the feed rate, Ra decreased to a minimum value and then increased again with higher feed rates. Higher feed rates result in higher feed marks on the machined surface (Figure 11). Ra surface roughness increased with increasing depth of cut due to generation of deeper feed marks especially at high feed rate of 0.09 mm/rev (Figure 17b). Minimum amount of Ra roughness was achieved at cutting speed of 90 m/min, feed rate of 0.04 mm/rev and 0.4 mm depth of cut.
1.2.4 Multi-objective optimization
Desirability function of RSM was used to perform the multi-objective optimization in order to find the optimal cutting parameters that would result in the maximum possible material removal rate, while maintaining the lowest possible flank wear, cutting force and Ra surface roughness values. Each response parameter was converted to a desirability function varying from 0 to 1 in which zero means the response is outside the acceptable region and the value of one indicates that the response has reached the goal. Individual desirability was combined to provide a measure of composite desirability of the multi response system . Constraints for optimizing flank wear, surface roughness, cutting force and material removal rate are summarized in Table 6. It was determined that cutting speed of 87 m/min, feed rate of 0.06 m/rev and depth of cut of 0.37 mm were the optimum cutting parameters for achieving flank wear of 58 µm, cutting force of 78 N and Ra surface roughness of 0.49 µm with the MRR value of 1.97 cm3/min (Table 7).
The proposed ranges for the cutting parameters which was provided by the manufacturer were cutting speed of 40 m/min (0.08-3), feed rate of 0.04 mm/rev (0.02-0.1) and depth of cut of 0.2 (0.08-3). The optimum feed rate and depth of cut found in this research are in the range of the manufacturer’s catalogue, but the cutting speed is twice as high as the one that manufacturer was proposed which means higher production rate can be possible.
Table 6 Constraints for optimization of flank wear, surface roughness, cutting force and material removal rate
Table 7 Multi-objective optimization results for response parameters