A multi-camera industrial Visual Inspection system that uses pretrained YOLO models for real-time product defect detection, digitizing the complete workflow from image acquisition to exception alerts.
Supports synchronized input from multiple industrial cameras with millisecond-level inspection response.
Uses YOLO models to accurately classify defects such as scratches, contamination, and deformation.
Inspection results are stored automatically for yield analysis and Traceability queries.
This intelligent inspection system uses a two-stage “coarse localization + precise recognition” vision model to replace manual inspection, accurately identifying cavity plugs in connector positions while creating a traceable digital quality inspection loop.
Because cavity-plug positions can vary across connector models, the system provides a template option. A correctly plugged connector is recorded once and used as the inspection template. The operator places a completed connector under the camera; the system identifies plug positions and announces “Correct” or “Incorrect.”
Connectors often contain many cavities requiring plugs, and operators, especially new employees, can insert plugs into the wrong positions or repeat the mistake across a batch. VisDetect uses AI vision to prevent this issue at the source.