| dc.description.abstract | In the domestic PCB manufacturing industry, the detection and removal of photoresist (PR) residues generated during the PCB process currently are still carried out in a station-by-station approach, resulting in a longer processing time and higher costs. Moreover, the optical inspection machine and laser cleaning machine used are imported from foreign countries, which leads to higher costs and limited flexibility for specific requirements. This study continued to improve an automated optical inspection and repair (AOIR) machine developed by our research team. This machine integrated optical inspection, laser cleaning, and precision stage movement technologies. The automated process was divided into two main parts, namely coarse positioning and precise positioning. Coarse positioning involved capturing wide-range PCB images using a line scan camera and utilizing the EmguCv library for image processing to locate PR residues. Precise positioning involved sequentially transferring these labeled PR residues to a coaxial laser imaging system for high-precision contour identification and planning of laser scanning paths for effective removal via laser cleaning.
This study was focused on improving the effectiveness of laser removing and exploring the mechanism of laser cleaning, as well as optimizing the process efficiency of the machine. In the laser cleaning process, an infrared picosecond fiber laser was used as the laser source. To prevent laser scanning from damaging the copper surface, pulse laser parameters with lower peak energy were selected for testing. The test results demonstrated that using laser parameters with a fluence (energy density) of 1.048 J/cm2 and performing three repeated scans could completely remove intact PR residue with a height of 25 μm. Laser scanning confocal microscopy (LSCM) was utilized to measure the surface profile and roughness, confirming that the copper surface was not damaged after laser scanning. For the laser cleaning mechanism, the surface temperature rise of the material upon receiving pulsed laser energy was estimated using a one-dimensional heat diffusion equation. The surface temperature of the PR residue increased significantly beyond its boiling point after a single pulse irradiation, indicating the removal mechanism of the PR residue was vaporization ablation.
In terms of process efficiency, this study developed a more versatile and faster image processing procedure. It employed a circuit mask to specify the detection area, thus avoiding false detections, and enhancing the detection capability for PR residues at the edge of PCB circuit trace. The optimization of program computation significantly improved the image processing time, reducing the coarse positioning from 13.7 s to 4.8 s and the precise positioning from 1.2 s to 0.17 s. The successful rate of PR residue contour identification in precise positioning reached 92.7%. Furthermore, by adopting a strategy of performing three repeated scans directly on suspected PR residues without re-identification, the single residue cleaning time was reduced from 8 s to 3.3 s.
Finally, a test was conducted to assess the automated PCB inspection and cleaning procedure. LSCM and scanning electron microscopy (SEM) were employed before and after the test for surface observation and elemental composition analysis. The results confirmed that real PR residues could be completely removed without changing the copper surface structure. The goal of integrating optical inspection and laser cleaning into a single machine for automated operation was accomplished. A comparison was made with the current process time of a local PCB manufacturer, showing a nearly 10 times improvement in performance. Accordingly, such automated optical inspection and laser cleaning machine is readily available for commercialization. | en_US |