AI Defect Detection for Printed Packaging

In printed packaging and textile production lines, color deviation, print misregistration, uneven ink, contamination, broken threads, and holes are the defects most likely to affect shipment quality and brand image.

Traditional manual inspection relies on visual judgment and experience — prone to missed defects from fatigue, and hard to keep consistent on high-speed lines. Drawing on years of image-recognition and production-line integration experience, Cheng Chi Tech built an automated AI quality inspection system for cartons, printed packaging, labels, and textile fabric, helping factories monitor the quality of every section of fabric and every printed surface in real time within a high-speed production environment.

The system combines high-speed image capture, preprocessing algorithms, and deep-learning models to continuously photograph material while machinery is running, with AI automatically detecting color deviation, missing print, pattern misalignment, uneven ink, discontinuous texture, broken threads, holes, or foreign contamination.

Detected defects are automatically classified and located, with the type and position shown on a monitoring dashboard so on-site staff can respond immediately.