Surface-mount technology (SMT) production lines involve a broad range of mounted components and exhibit inconsistent charging tray specifications. To address issues such as error-prone chip positioning and orientation, as well as difficulty in recognizing chip characters during production, this study designs and implements a component detection system for SMT production lines based on improved YOLOv5s. A high-precision line-scan camera is used to rapidly capture images of the charging trays on the production line, and improving the YOLOv5s object detection algorithm through enhancements such as adding an attention mechanism and a P2 small object detection layer, the system achieves improved position and orientation detection, as well as improved information recognition, for all chips in the images of the charging trays with varying specifications. Practical testing verifies that the system enables accurate component detection under various working conditions, significantly enhancing the quality and efficiency of component inspection in SMT production lines.