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Automating Quality Control for Automotive Parts Manufacturing
94%
Defect Accuracy
-65%
Manual Labor
24/7
Inspection
3.2x
ROI Year 1
The Challenge
A leading automotive component manufacturer in Pune was struggling with inconsistent manual inspections. Human fatigue on the night shifts led to a 12% escape rate of micro-cracks in cylinder heads, resulting in expensive recalls and strained client relationships.
The Solution
Foxkrit engineered a custom computer vision pipeline using edge-AI cameras positioned directly on the assembly line. We trained a Deep Convolutional Neural Network on over 50,000 labeled images of defect-free and flawed components.
Real-time edge processing (120ms per part)
Automated rejection mechanism integration
Cloud-based analytics dashboard
Historical defect trend reporting
The Result
Within 3 months of deployment, the escape rate dropped to near zero. The system identifies defects that are invisible to the naked eye under factory lighting conditions.
- Total Recall Savings$420,000+ Annual
- Employee Reallocation12 Skilled Techs