Visual defect inspection — Automotive
Deep-learning vision that flags surface and assembly defects at line speed. Delivered for a automotive client in Mundra.
- Location
- Mundra
- Year
- 2020
- Duration
- 28 weeks
- Team
- 6 engineers
- 98%
- defect recall
- 27
- ms per part
- 84%
- fewer escapes
The challenge
Existing vendors had delivered pieces of a visual defect inspection system, but nobody owned the integration and the pilot had stalled.
What we built
A phased rollout: a measured pilot first, then scale-out. The core runs on PyTorch with TensorRT, integrated into existing systems through OPC UA.
Delivery timeline
Phase 1
Discovery sprint and site survey
Phase 2
Prototype built and tested in the Motera lab
Phase 3
Pilot on site with before/after measurement
Phase 4
Scale-out, training and handover
Highlights
- Runs on-premises; no data leaves the site unless agreed
- Remote monitoring and over-the-air updates included
- Integrated with existing PLC, ERP or GIS systems — no rip-and-replace
- Operator training delivered in Gujarati, Hindi and English
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