## 5 Conclusions  
In this study, the cutting path effect on the acoustic emission (AE) and vibration signals during micro milling processes was investigated by implementing three types of cutting paths in a micro milling experiment. The results show that the time domain signal generated from the cutting of a straight line, the corner of the square path, and the circle path are different from each other. Based on the correlation analysis of the frequency features with tool wear, the optimum frequency features which are closely related to the tool wear condition differ along with the change in cutting paths for the vibration signal. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} Bandwidth Size \\ 6000 Hz \\ \end{tabular} } & \multicolumn{3}{c}{**Straight Line**} & \multicolumn{3}{c}{**Square**} & \multicolumn{3}{c}{**Circle**} \\ \cline{2-10}  & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** \\ \hline
**0.015 s** & 59 & 59 & 59 & 94 & 50 & **72** & 75 & 31 & **53** \\ \hline
**0.22 s** & 68 & 77 & **73** & 94 & 44 & **69** & 75 & 38 & **56** \\ \hline
**1 s** & 55 & 100 & **78** & 88 & 75 & **81** & 75 & 81 & **78** \\ \hline
**1.75 s** & 50 & 100 & **75** & 75 & 75 & **75** & 75 & 81 & **78** \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Tool wear classification rate with AE signals and various signal lengths (model trained by straight line data). \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} Bandwidth Size \\ 150 Hz \\ \end{tabular} } & \multicolumn{3}{c}{**Straight Line**} & \multicolumn{3}{c}{**Square**} & \multicolumn{3}{c}{**Circle**} \\ \cline{2-10}  & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** \\ \hline
**Signal Length** & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** \\ \hline
**0.017 s** & 32 & 86 & **59** & 69 & 75 & **72** & 75 & 56 & **66** \\ \hline
**0.27 s** & 27 & 100 & **64** & 50 & 100 & **75** & 44 & 100 & **72** \\ \hline
**0.82 s** & 50 & 100 & **75** & 69 & 100 & **84** & 88 & 100 & **94** \\ \hline
**2.18 s** & 100 & 100 & **100** & 100 & 94 & **97** & 100 & 100 & **100** \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Tool wear classification rate with the X-axis vibration signal and a 150 Hz bandwidth size (model trained by straight line data). \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} Bandwidth Size \\ 150 Hz \\ \end{tabular} } & \multicolumn{3}{c}{**Straight Line**} & \multicolumn{3}{c}{**Square**} & \multicolumn{3}{c}{**Circle**} \\ \cline{2-10}  & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** & **Sharp** & **Worn** & **Average** \\ \hline
**0.017 s** & 95 & 36 & **66** & 100 & 31 & **66** & 100 & 38 & **69** \\ \hline
**0.27 s** & 100 & 100 & **100** & 94 & 100 & **97** & 88 & 100 & 94 \\ \hline
**0.82 s** & 100 & 100 & 100 & 100 & 100 & **100** & 100 & 100 & **100** \\ \hline
**2.18 s** & 100 & 100 & **100** & 100 & 100 & **100** & 100 & 100 & **100** \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Tool wear classification rate with the Z-axis vibration signal and a 150 Hz bandwidth size (model trained by straight line data). However, the cutting path effect on the AE signal is lower than that of the vibration signal. In the study of the effect on the monitoring performance caused by the sampled length and bandwidth size of the features, the increase in the sampled signal length to generate the signal features will reduce the path change effect, based on the scatter index analysis. Moreover, unlike that of the sampled signal length, the cutting path effect was not observed to change with the increase in the bandwidth size of the features.