Executive Summary

In high-volume electronics assembly, microscopic defects such as solder bridges or missing components can lead to costly rework and field failures. The customer faced rising defect escape rates and production slowdowns due to manual visual inspection bottlenecks. By deploying the Acuemax PEX-200 Edge AI Controller, the manufacturer transitioned to real-time, AI-driven inspection at the factory edge—improving detection accuracy to 99.9% and increasing line speed by 30%.

The Challenge

• Human error & fatigue: Manual inspection accuracy dropped to ~85–90% over long shifts, allowing escaped defects.
• High-speed image processing: Multiple 12MP camera streams needed to be analyzed in milliseconds to keep the line moving.
• Legacy integration: The system had to fit existing racks and communicate with factory protocols (e.g., Modbus / Profinet) while surviving dust and vibration.

The Solution

• Hybrid processing power: Intel® 13th Gen Core™ CPU + NVIDIA RTX™ MXM acceleration on the PEX-200 to run control logic and deep-learning inference on one device.
• Low-latency edge inference: Local GPU processing identified defects in <15ms, enabling instant reject decisions without stopping the conveyor.
• Industrial reliability: Rugged, fanless design supports 24/7 operation and prevents instability from thermal throttling seen in prior prototypes.

The Result

• Accuracy: Improved from ~88% manual detection to 99.9% AI detection.
• Speed: Inspection time reduced from 1.2s per unit to 0.05s per unit.
• Throughput: Production increased by 30% while maintaining quality targets.
• Business impact: Reduced waste and rework delivered a full ROI in ~7 months, with expansion planned across additional sites.

“The PEX-200 provided the exact balance of CPU power and GPU acceleration we needed to move our quality control into the AI era.” — Operations Manager, US Electronics OEM