How the Opsio Inspection System enables electronics teams to detect defects in seconds using real-time YOLO-powered inspections, automated annotation workflows, and complete traceability.
2 Specialists
Approx. 8 weeks
Development
Vue.js, TailwindCSS
Django, Python, YOLO Framework
Label Studio, YOLOv8 Training Engine
Industrial Camera, Fanless PC, Touchscreen Display
The development and implementation of the Opsio Inspection System focused on delivering an AI-powered, highly accurate, and scalable inspection workflow that can run in real-time manufacturing environments. The primary objective was to replace manual inspection dependency with an automated, reliable, and fully traceable solution.
Designed and developed an intelligent inspection pipeline capable of capturing high-resolution PCB images, detecting components, identifying defects, and generating instant pass/fail results without human interpretation.
Built a structured training lifecycle using labeled datasets and YOLO-powered learning models, ensuring precise defect detection even for fine-pitch and complex PCB layouts.
Configured industrial-grade imaging hardware and on-device inference to ensure stable, low-latency performance suitable for production lines, labs, and field environments.
Implemented automatic logging for each inspected board, including timestamps, defect types, component counts, and workflow outcomes, enabling analytics, compliance reporting, and progressive quality improvement.
Different lighting, angles, and surfaces across production lines caused uneven illumination and micro-shadows, reducing detection consistency.
Initial datasets had gaps and imbalances, leading to missed micro-components, false positives, and unstable accuracy.
Fanless industrial PCs struggled with real-time inference due to limited GPU power, thermal slowdowns, and frame delays.
Different PCB types with varying densities made it challenging to maintain uniform accuracy without retraining for every board.
Achieving stable, generalizable detection required significant dataset expansion, better annotations, and continuous refinement.
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