## 3 Results
Figure 8: Records of individual milling stages (I-II-III)—detailed view for following cutting conditions (rotation speed / feed rate): (**1**) 10,000 rpm/12 m.min\({}^{-1}\), (**2**) 10,000 rpm/6 m.min\({}^{-1}\). To determine the appropriate statistical methods, the normality of data within each cutting condition was first tested using the Shapiro-Wilk test. All four experimental conditions yielded \(p\)-values \(\leq\) 0.050, indicating a statistically significant deviation from normality. Therefore, the Kruskal-Wallis H test was used to determine significant differences among the experimental cutting conditions. Subsequent analysis was based solely on normalized data to maintain objectivity in result evaluation. The Kruskal-Wallis test produced an H statistic (4; 184,939) of 5671.651 and a \(p\)-value \(<\) 0.001, indicating that at least one experimental cutting condition differs significantly from the others in terms of the median AE signal value. Thus, a post hoc Dunn's test was conducted to identify specific group differences while controlling for multiple comparisons. The results are presented in Table 6.  
The data shown in Table 6 were corrected used a Bonferroni correction for multiple testing. The pairwise tests showed that cutting condition A differed significantly from both B (Bonferroni-adjusted \(p\)\(<\) 0.0001) and D (Bonferroni-adjusted \(p\)\(<\) 0.0001), but not from C (Bonferroni-adjusted \(p\)\(=\) 1.0000). Condition B likewise differed from C (Bonferroni-adjusted \(p\)\(<\) 0.0001) and from D (Bonferroni-adjusted \(p\)\(<\) 0.0001), and condition C differed from D (Bonferroni-adjusted \(p\)\(<\) 0.0001). Thus, five of the six possible comparisons reached statistical significance after adjustment: A vs. B, A vs. D, B vs. C, B vs. D, and C vs. D. Only A vs. C remained non-significant. These results demonstrate that condition B yields values significantly higher than A and D, and that condition C is statistically indistinguishable from A but significantly lower than B and D. Such a pattern suggests a graded effect across conditions, with C overlapping A, but B and D forming distinct extremes. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Cutting Conditions Comparison** & \multicolumn{1}{c}{**Z Statistic**} & \multicolumn{1}{c}{_p-Value_} \\ \hline
**Group 1** & **Group 2** & & \\ \hline A & B & 46.80 & \(<\)0.001 \\ A & C & 0.86 & 0.388 \\ A & D & 57.93 & \(<\)0.001 \\ B & C & 47.50 & \(<\)0.001 \\ B & D & 9.65 & \(<\)0.001 \\ C & D & 58,64 & \(<\)0.001 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Post hoc Dunn’s test analysis results. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Cutting Conditions** & \multicolumn{1}{c}{**Measurement**} & \multicolumn{4}{c}{**AE Signal**} & \multicolumn{4}{c}{**AE Signal**} \\  & & & **Original Data (dB)** & & & **Normalized Data (dB)** \\ \cline{3-8}  & & **Average** & **Sum** & **SD** & **Average** & **Sum** & **SD** \\ \hline \multirow{9}{*}{C} & 1 & 65.007 & 664,633.701 & 5.016 & 0.076 & 781.932 & 0.006 \\  & 2 & 65.077 & 665,473.423 & 4.989 & 0.077 & 782.930 & 0.006 \\  & 3 & 65.210 & 666,571.525 & 4.885 & 0.077 & 784.169 & 0.006 \\  & 4 & 66.778 & 683,936.462 & 4.866 & 0.079 & 804.685 & 0.006 \\  & 5 & 65.342 & 667,274.433 & 4.859 & 0.077 & 785.019 & 0.006 \\  & 6 & 65.481 & 667,910.095 & 4.730 & 0.077 & 785.764 & 0.006 \\ \hline \multirow{9}{*}{D} & 1 & 69.661 & 361,540.940 & 3.916 & 0.080 & 417.013 & 0.005 \\  & 2 & 68.258 & 354,669.920 & 4.413 & 0.079 & 409.070 & 0.005 \\  & 3 & 68.214 & 354,710.700 & 4.584 & 0.079 & 409.116 & 0.005 \\  & 4 & 69.675 & 362,586.659 & 4.352 & 0.080 & 418.184 & 0.005 \\  & 5 & 68.404 & 354,607.667 & 4.225 & 0.079 & 409.056 & 0.005 \\  & 6 & 68.390 & 354,399.495 & 4.093 & 0.079 & 408.767 & 0.005 \\ \hline \hline \end{tabular} Note: The AE signal data are represented using RMS values.  
\end{table} 
Table 5: _Cont._In addition, normalized AE signal data as calculated averages and sums of each cutting condition and measurement were analyzed (see Table 5).