[Project Background] This client is a large 3C electronic components contract manufacturer in South China. To improve production line yield, the client decided to implement a smart upgrade to its existing SMT (Surface Mount Technology) production lines by introducing a deep learning-based AOI (Automated Optical Inspection) multi-camera vision system to detect minor defects such as misplaced components, missing components, and cold solder joints on circuit boards in real time.
B [Real-World Engineering Challenges] During the initial testing phase of the project, the client’s integrator encountered a difficult low-level networking issue:
Packet loss caused by instantaneous concurrency (high bandwidth concurrency): Each quality inspection device is equipped with six 5-megapixel industrial cameras. When products pass by on the conveyor belt, all six cameras trigger simultaneously to capture images, generating a massive concurrent data stream. The standard commercial-grade switches previously used lacked sufficient buffering capacity, resulting in frequent frame drops. Consequently, the AI algorithms frequently encountered errors and shut down due to missing images.
Cable Clutter and Limited Space (Cabling Challenges): The interior space of the quality inspection station is extremely confined. If separate power and network cables were run to each of the six cameras, not only would the cabling become excessively bulky, but the frequent movement of the cameras on the robotic arm would also cause the complex cable harnesses to wear out and break easily, making troubleshooting extremely difficult later on.
Electromagnetic interference (EMC issues) in the workshop: The quality inspection equipment is located right next to a large SMT machine and a reflow oven, and the surrounding area is filled with servo motors. The environment is subject to significant electromagnetic interference, which occasionally causes snow-like noise in the image transmission.
[Rayin Solutions] Following an on-site survey, Rayin provided all-Gigabit industrial-grade PoE+ switches for this project to serve as the core data hub of the vision system:
Large-Cache Non-Blocking Design: Featuring redundant backplane bandwidth and a large-capacity cache, this design effortlessly handles the "sudden surge in traffic" caused by six HD cameras triggering simultaneously, completely eliminating packet loss and image corruption.
Single-cable PoE+ High-Power Supply: Using the standard IEEE 802.3at (PoE+) protocol, a single Category 5e Ethernet cable simultaneously supports 100Mbps/1Gbps data transmission and 30W high-power supply. The internal wiring harness is reduced by half, resulting in a clean cable layout and significantly lowering the likelihood of cable interference during robotic arm movement.
E High-Level Electromagnetic Interference Protection: Featuring a corrugated aluminum alloy housing and a rigorous conductive oxidation process, the entire unit achieves power-grade electromagnetic interference immunity (Level 4). It operates stably next to the placement machine, ensuring that every frame of the transmitted image is clear and free of noise.
[Actual Client Returns]
Efficiency Improvements: Following the upgrade, the network-level frame drop rate was reduced to 0%, allowing the AI quality inspection system to operate at full capacity. As a result, the inspection cycle time for the entire production line was reduced from 5 seconds per item to 3 seconds per item.
B Cost Reduction in Operations and Maintenance: PoE power delivery has significantly reduced cabling, shortening the construction timeline by 30%. During the past six months of continuous full-load operation, there has not been a single outage caused by network communication issues, greatly alleviating the operational burden on on-site IT/OT engineers.
