A Tier 1 automotive parts manufacturer was having difficulty “seeing” critical surface defects during the molding process resulting in rejected parts from their customers.
Before – Operator Visual Inspection
- Operators inspecting parts after the molding process could not see quality issues such as short shots, splay and read-through defects.
- Additional time was required to move the parts to another area with better lighting to attempt to confirm the defects.
- These inspections were highly subjective, varying from one operator to another.
After – Eigen Visual Inspection
- FLIR thermal and optical cameras were installed at the molding station.
- A lighting display was installed to overcome the visibility issues making the surface defects “pop” in the captured images.
- Eigen edge devices collected image and process data.
- Using the high-resolution image and process data, Eigen’s machine-learning specialists designed and deployed models to provide superior inspection – detecting all three defects in real-time.
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