Automated Visual Inspection System
Deployed AI-powered visual inspection system for automotive component manufacturing, detecting surface defects with 99.7% accuracy and reducing inspection time by 85%.
The Challenge
A leading automotive component manufacturer relied on manual visual inspection of machined parts. With over 500,000 parts produced monthly, inspectors were unable to consistently identify subtle surface defects, scratches, and dimensional inconsistencies within the required timeframe.
Human fatigue led to detection rate variations between 78-88%, resulting in defective parts reaching customers and costly warranty claims. The company needed an automated, reliable solution that could match human capability while operating 24/7.
Key Pain Points
- Inconsistent defect detection due to human fatigue (78-88% accuracy)
- Manual inspection unable to keep pace with production volume
- High customer warranty claims for missed defects
- Significant labor costs for dedicated inspection team
Our Solution
Multi-Angle Camera System
Integrated high-resolution cameras with controlled lighting to capture parts from multiple angles, enabling comprehensive defect detection.
CNN-Based Defect Recognition
Trained convolutional neural networks to recognize 15+ types of surface defects including scratches, cracks, dimensional errors, and finish issues.
Real-Time Pass/Reject Decision
Automated rejection and sorting system with confidence scoring, enabling operator review of borderline cases.
Results & Impact
Detection Accuracy
Inspection Time Reduction
Warranty Claims Reduction
Additional Benefits
Ready to Improve Your Quality Control?
Let's explore how automated visual inspection can boost accuracy and efficiency in your manufacturing process.
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