An automatic sorting system for electronic components detached from waste printed circuit boards.

Recycling e-waste makes for eliminating the pollution to environment and recovering critical materials as one of resource. Printed circuit boards (PCBs) serve as the important part in all e-waste, containing valuable but hazardous elements to be recycled when they reach the end of life. For the recycling of waste PCB, the electronic components (ECs) are liberated from base board and to be treated separately for element recovery. Due to the diverse element composition, ECs deserve to be further classified and sorted to improve the efficiency of recycling, achieving the concept of accurate recovery. Currently, the recycling industry only roughly screen the ECs manually by labors, which increases the risk of health for exposure to the hazardous environment. Automatic solutions are necessary for replacing labors to classify and sort the waste ECs, thus safeguarding them against the hazards of factory environment. In this work, the YOLO-V3, an emerging image detection algorithm, is utilized to train the self-made dataset and classify the ECs into specific categories. To avoid surface damage that weakens the accuracy of object detection, the technology process of detaching the ECs is improved by building a nitrogen atmosphere during the desoldering process, which delivers great protection effects on ECs. Results of YOLO-V3 detection model present satisfactory classification capability for all the classes of ECs and a smart on-line sorting system is proposed to automatically separate the ECs detached from WPCB.