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Task / Problem
After production, tyre labelling at the site was done manually and took a lot of time.
Meanwhile, the line constantly handled different SKUs, and the tyres varied by diameter, profile, and size. Without automatic product recognition and code validation, the risk of mistakes, mix-ups, and additional labor costs increased.
Solution
We combined two complexes: a machine vision system and the ‘Chestny Znak’ labelling system.
First, machine vision recognizes the tyre model and size, and if necessary, identifies the presence of studs; then the system prints and applies the label, checks the code, and automatically rejects incorrect products.
Key features:
- Automatic SKU recognition of the tyre on the conveyor
- Machine learning for product identification
- Determining the presence of studs on winter tyres
- Validation of the applied code and error rejection
- Special label application and tyre removal mechanisms
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Results
- Automated SKU identification and production statistics collection
- Reduced labeling workload by minimizing manual labor
- Decreased labeling code application errors
- Integrated labelling data with the enterprise's accounting system
- Added ability to track weight characteristics for further raw material and material analysis
Technical details:
- The system recognizes the moving tyre, selects the correct labelling scenario, and starts label printing according to the actual SKU.
- After application, the system reads the code, validates it, and removes the tyre from the line if an error occurs.
- To improve application quality, a special rejection mechanism and an additional label pressing unit were developed.
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- Reduced defective production thanks to real-time monitoring
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- Automated control of critical parameter on the line
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- Automated marking across all production sites
- Solution deployed at 3 key enterprise sites
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Chestny ZNAK Labeling for 5 Rusagro Sites
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Result:
- Over 90 lines equipped at oil and fat production sites
- Labeling at speeds up to 18,000 units per hour with no loss of productivity
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Laser Thickness Control of Flexible Shingles for Shinglas Plant
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Result:
- Over 15% defect reduction thanks to instant thickness deviation detection
- Up to 7% raw material savings by maintaining thickness within tolerance
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