Case 04 | Electronic Modules

AI Visual Quality Inspection

Edge computing AI vision system identifies surface defects on electronic modules with millisecond precision. Transition from manual inspection to vision-based quality control — making quality inspection smarter and more consistent.

Challenges

Two Site Challenges

Inconsistent Quality Inspection

Traditional manual inspection lacked consistency with high miss rates. Fatigue-induced errors made it difficult to meet the quality stability demands of large-scale production.

Inspection Bottleneck

Manual visual inspection was slow and became a production bottleneck, unable to keep pace with high-volume manufacturing delivery requirements.

Solution

Edge AI Vision × Deep Learning

Edge computing AI vision system covers十余 types of defect detection including missing components, damage, and scratches. Real-time capture on the production line with automatic judgment and classification. Breaks through the manual inspection bottleneck by fusing machine vision with deep learning algorithms.

Multi-type Defect Detection

Covers十余 defect types — missing components, damage, scratches, foreign objects — with a single system. Real-time line-side capture with millisecond automatic classification.

Quality Traceability

Inspection results are accumulated as data, ensuring per-product quality traceability. Standardized inspection eliminates human variability and guarantees yield at the source.

Results

Intelligent Quality Inspection

≥95%Defect Recognition Accuracy

Machine vision and deep learning significantly outperform traditional visual inspection.

70%+Miss Rate Reduction

Eliminates fatigue and oversight from manual work, dramatically reducing missed defects.

2-3×Inspection Efficiency

Automation achieves 2-3× inspection throughput compared to manual methods.

PoC

Start with a small-scale proof of concept.

We'll assess your existing cameras, target areas, and improvement metrics to propose the optimal approach.