A conveyor system operator · Manufacturing · logistics
AI vision added to an existing conveyor
Nara adds flexible AI vision to a traditional conveyor. The conveyor can now reject items by code, text, colour, or any feature an AI model can learn, and fewer inspection staff are needed.
- Customer
- A conveyor system operator
- Sector
- Manufacturing · logistics
- Deployment
- On-premise: camera on an existing conveyor, rejector via PLC
- Status
- Completed
Challenge
Traditional conveyors lack scalable AI capabilities. Every new inspection rule meant new hardware or manual inspectors.
Solution
Nara was integrated with the conveyor’s camera and PLC, so inspection rules can be changed in a visual flow rather than in hardware.
How it works
- 01inputCamera and item sensor on the conveyor
- 02processNara vision: codes, OCR, colour or a trained model
- 03actionThe PLC drives the rejector
Results
- Rejection based on 1D/2D codes, text (OCR), colours, or features trainable with AI
- Fewer inspection staff needed
Nabrio components
- Camera nodes
- Code reader
- OCR
- Colour detection
- Custom models (Reva)
- Modbus to PLC
Use cases
Build the same thing on your site.
cameranara seesDefect detection and rejection
Defects must be removed from the line automatically, at line speed, without stopping production.
cameranara seesBarcode and label inspection
Manual scanning is slow and misses items, and a wrong lot number, expiry date or allergen label means recalls and penalties.
cameranara seesSorting and grading
Sorting products by type, grade or destination by hand is slow and inconsistent.
See what Nara sees, on your own cameras.
Download Nara and build your first flow in minutes, or tell us what you need to see and do, and we’ll show you how it runs on your own hardware.