## 3 Verifying the Automatic Deburring System  
To verify the feasibility of the method proposed in this study, the Industrial Technology Research Institute's 12A62 robotic arm (which has a movement range of 1406 mm, a repeatability accuracy of 0.06 mm, and an absolute positioning precision of approximately 5 mm, according to the ISO9283 standard for laser trackers) was used to test the automatic deburring system. The method was applied to a bicycle fork processed through die casting. The dimensions of the robotic arm are presented in Figure 8. The system consisted of a Taiwan-made robotic arm controller, a Keyence LJ-X8080 online contour sensor (which had a measurement depth of 41 \(\pm\) 20.5 mm, a width of 30-39 mm [depending on the depth], a repeatability accuracy of 0.5 \(\upmu\)m, and a sampling frequency of 16 kHz), and a motorized spindle with \(\varnothing\)6 four-edge standard milling cutters (Figure 9). Figure 6: Automatic burr detection. (**a**) contour fitting of processed edge. (**b**) contour fitting of parting lines/risers. Figure 7: Deburring trajectory generation. (**a**) workpiece edges. (**b**) parting lines/risers. To enable immediate deburring after scanning, the regions scanned by the contour scanning sensors were placed as close to the processing locations of the spindle milling cutters as possible. When the milling cutters moved to the burr locations after scanning, the laser contour scanning sensors were required to obtain the next cross-sectional contour information to determine the next processing trajectory point (Figure 10). Figure 8: Industrial Technology Research Institute 12A62 robotic arm dimensions. Figure 9: Verifying the automatic deburring system. After the system was set up, the robotic arm controller and contour output controller were connected using network cables and the digital communication method. The robotic arm controller obtained contour information by using the API provided by the contour output controller. Once the contour information was obtained, adjustments were made using the hand-eye calibration method [23] and the spindle coordinate system correction method to determine the relative relationships among the contour sensors, spindle locations, and robotic arm coordinate system. The deburring process started at the location where the contour scanning sensors could capture contour information. Once the contour information was obtained, the proposed method was used to analyze the burring region and generate processing trajectories. The burr locations were aligned with the spindle for deburring and to obtain the next cross-sectional contour for additional analyses. The proposed procedure enables continuous processing trajectory generation and complete deburring (Figures 11 and 12). Figure 11: Cross–sectional contour information of bicycle fork (red box is the schematic of deburring tool): (**a**) contour information and (**b**) cutter trajectory. Figure 10: Relative relationship between contour scanning and spindle location. Figure 12a shows the bicycle fork used for system verification. Figure 11 illustrates the cross-sectional data from Figure 12a that were obtained using laser contour scanning sensors. By applying the proposed method, the deburring trajectory could be generated for the subsequent deburring process. The result of the processing along the cross-sectional contour is displayed in Figure 12b. The proposed method can be applied to deburr workpieces after molding as well as to deburr workpiece edges after cutting. Because the processed edges comprise two discontinuous line segments, the two segments must be fitted separately during curve fitting (Figure 13). All the contour information was first input into the linear equation to obtain the first line segment, and the interior point \(m_{i}\) was removed from the contour points obtained by the sensors to generate a new contour point set. The second fitting was performed thereafter to obtain the mathematical equation for the second line segment.