## 3 Results
Implementation of the ANOVA method was used to determine the extent to which the controllable factors influence the performance of the cutting process. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Controllable Factor** & **Level 1** & **Level 2** & **Level 3** & **Rank** \\ \hline Cutting speed, \(v_{c}\) [m/min] & **0.6437** & 0.6013 & 0.5716 & 3 (0.0721) \\ \hline Feed rate, \(f_{n}\) [mm/rev] & **0.7122** & 0.5550 & 0.5495 & 1 (0.1627) \\ \hline Cutting environment, \(ce\) [/] & 0.5239 & **0.6576** & 0.6351 & 2 (0.1337) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Means of grey relation grade and optimal ranking. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Test No. **} & \multicolumn{4}{c}{**Grey Relation Coefficients**} & \multicolumn{2}{c}{**Grey**} \\ \cline{2-7}  & **F\({}_{\text{t}}\)** & **\(\alpha\)** & **L\({}_{\text{bue}}\)** & **H\({}_{\text{bue}}\)** & **Relation** & **Grade** & **Order** \\ \hline
1 & 1.000 & 0.523 & 0.548 & 0.846 & 0.729 & 2 \\ \hline
2 & 0.490 & 0.400 & 0.575 & 0.595 & 0.515 & 7 \\ \hline
3 & 0.472 & 0.438 & 0.958 & 0.880 & 0.687 & 3 \\ \hline
4 & 0.801 & 1.000 & 0.852 & 0.667 & 0.830 & 1 \\ \hline
5 Table 7 shows the contribution of each controllable factor on the output variables, with feed rate having the highest contribution (31%), followed by cutting environment (18%) and cutting speed (5%). To verify the degree of improvement that the optimal controllable factor set provides, a new experiment was carried out. Using the grey relation analysis, the optimal grey relation grade can be estimated using the formula:  
\[\mathrm{y}=\mathrm{y}_{\mathrm{t}}+\sum_{\mathrm{i=1}}^{\mathrm{p}}(\mathrm{y }_{\mathrm{i}}-\mathrm{y}_{\mathrm{t}}) \tag{8}\]  
where \(\mathrm{y}_{\mathrm{t}}\) is the total mean of the grey relation grade for the complete experiment set, \(\mathrm{p}\) is the number of controllable parameters in the experiment set and \(\mathrm{y}_{\mathrm{i}}\) is the mean of the grey relation grade for the optimal set of controllable parameters. The experiment implementing the optimal parameter set is presented in Table 8. Implementing the optimal parameters, thrust force was reduced from 3.3 N to 2.7 N, hole deviation decreased from 2.46\({}^{\circ}\) to 1.88\({}^{\circ}\) and BUE length was greatly reduced from 0.38 mm to 0.15 mm. Built-up edge height increased slightly from 0.22 mm to 0.29 mm. Figure 7 shows a comparison of BUE dimensions using various cutting parameters and an MQL cutting environment. Using the optimal cutting parameters caused the least amount of built-up length across the width of the cutting edge. The predicted grey relation grade for optimal parameters was calculated using Equation (8). Comparing the initial controllable parameter grade and experimental optimal parameter grade, an improvement of 0.1035 was noted. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Controllable Factor** & **SS** & **Contribution [\%]** \\ \hline Cutting speed, \(v_{c}\) [m/min] & 0.0079 & 5 \\ \hline Feed rate, \(f_{n}\) [mm/rev] & 0.0512 & 31 \\ \hline Cutting environment, \(ce\) [/] & 0.0307 & 18 \\ \hline \(\mathrm{SS}_{\mathrm{T}}\) & 0.1663 & \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Contribution of controllable parameters on output variables. Figure 7: Built-up edge dimensions for MQL tests conducted at: (**a**) 40 m/min and 0.125 mm/rev, (**b**) 70 m/min and 0.05 mm/rev, (**c**) 100 m/min and 0.2 mm/rev, (**d**) 40 m/min and 0.05 mm/rev (optimal conditions).