Connectivity Cable Classification Using AR + AI
Case Overview
Connectivity cable classification using AR + AI is a visual inspection process for identifying, classifying, and counting connectivity cables in electronics manufacturing.
The Case
Cable Inspection and Classification in Electronics Manufacturing
SP Vision Technology Co., Ltd. is a Thailand-based system integrator providing machine vision and automation solutions to electronics manufacturers producing connectivity cables.
End-user production lines require inspection of connectivity cables, including USB, HDMI, Lightning, and RJ45 types, with requirements covering type identification and cable counting.
The Challenge
Limitations of Manual Inspection and Rule-Based AOI
Manual inspection in high-mix production is inconsistent due to variability in visual judgment.
Rule-based AOI improves defect detection but requires frequent parameter tuning and is sensitive to lighting and appearance changes, resulting in false rejects.
AOI systems also rely on predefined defect rules and limited datasets, which reduce flexibility for new cable types and increase the risk of missed defects and inaccurate counts.
The Solution
META-aivi AR + AI Visual Inspection
META-aivi enables real-time cable recognition, classification, and counting using smart devices with AI vision.
The vision system AI model is trained using 5–10 images per cable type to identify and classify each cable variant and perform cable counting. META-aivi also supports connector defect detection.
Deployed on smartphones and tablets, the AR + AI vision system performs inline inspection and verification at the point of production.
Connectivity Cable Classification
The Results
Application Summary
META-aivi enables AR-assisted AI inspection for connectivity cable classification, defect detection, and counting in electronics manufacturing environments, supporting consistent visual inspection across mixed-model production lines.