Industry Background and Pain Points
3C electronics assembly lines typically feature dense workstations, fast inspection takt, and diverse defect types. Take a smartphone middle-frame assembly line as an example: a single line usually includes multiple quality inspection stations—appearance defect inspection, critical dimension measurement, DPM laser code recognition, and assembly part presence/absence inspection—with inspection takt requirements exceeding 60 pieces per minute. Under traditional manual visual inspection, each station requires 2–3 inspectors on rotation. Long-term high-intensity work easily causes visual fatigue, and the defect escape rate is as high as 15% or more. Moreover, manual inspection data cannot be structurally entered into the MES system, making quality traceability difficult. With conventional industrial PC + vision card solutions, a single device usually supports only 1–2 camera inference streams. Multi-station deployment requires multiple independent systems, resulting in high hardware costs, complex wiring, and fragmented data across stations—making it difficult to achieve overall production line quality data analysis.
EA Series Product Functions and Application Solution
This solution adopts Beilai Technology’s EA230 Pro enhanced industrial edge AI computer as the core processing unit. It is equipped with the NVIDIA Jetson Orin Nano 8GB core module, providing 67 TOPS INT8 peak AI compute—sufficient to support parallel inference for multiple industrial cameras. The device natively provides 4 independent Gigabit Ethernet ports, each supporting independent subnet configuration and hardware isolation. They connect to GigE Vision industrial cameras at four workstations on the production line, corresponding to four inspection tasks: appearance defect inspection, precision dimension measurement, DPM code recognition, and assembly presence/absence inspection—truly enabling a single device to cover multi-station quality inspection across the entire production line.
At the hardware synchronization level, the EA230 Pro has a built-in isolated PWM hardware trigger circuit and Strobe flash synchronization output, supporting encoder cascaded triggering. It can precisely control camera exposure timing and light source on/off according to conveyor speed, ensuring clear image acquisition without motion blur at high speed. The four camera trigger signals are synchronized by the same clock source, with time synchronization precision reaching the microsecond level—completely solving the trigger desynchronization problem in multi-device stitching solutions. At the network level, camera data streams, PLC real-time control signals, and MES data upload belong to three independent subnets, physically preventing high-volume image data from preempting control link bandwidth and ensuring real-time reliability of production line control commands.
At the algorithm level, the EA230 Pro fully supports CUDA and TensorRT inference acceleration engines. For common 3C industry defects such as scratches, dents, discoloration, and burrs, a trained YOLOv8-s model, after INT8 quantization optimization, achieves single-frame inference latency below 15 ms and single-channel inspection frame rates above 60 FPS—fully matching the high-speed production line takt. The device comes pre-installed with Beilai Technology’s EdgeAI Studio development environment, supporting one-click model deployment, version management, and online iteration. The customer’s algorithm team can continuously optimize models based on their own data without changing the hardware architecture.
Customer Benefits and Deployment Results
After a leading consumer electronics contract manufacturer introduced this solution, a single EA230 Pro on one assembly line replaced the original four independent inspection systems. Hardware deployment cost was reduced by 60%, equipment volume inside the control cabinet was reduced by 70%, and wiring workload dropped significantly. The comprehensive defect detection rate increased from 85% under manual mode to 99.6%, with micro-scratch detection reaching 98.5%—far exceeding the industry average. All inspection data is structured and uploaded directly to the MES system, enabling full lifecycle quality traceability for individual products and helping the process department precisely identify high-defect workstations to continuously optimize production processes. Since going live six months ago, the device has achieved continuous failure-free operation exceeding 4,000 hours, stably adapting to the constant-temperature clean environment of the SMT workshop.
