Food and beverage
Packing, palletizing and quality control, with specific hygiene and cleaning requirements.
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Link to the SDGs SDG 8 SDG 12
- SDG 8 Decent work and economic growth Cobots can take over repetitive lifting of cases and tasks in cold rooms, reducing workers' strain and exposure.
- SDG 12 Responsible consumption and production Sensors and simulation help reduce product losses, off-spec packaging and stoppages during format changes.
Written with AI assistance. Still under review by the team.
In food and beverage, much of the manual work happens after the product is packaged: erecting cases, placing packs inside them, stacking pallets and checking labels. That is where most collaborative cells tend to be installed.
Why cobots here
- End of line: case packing and palletizing are repetitive and physically heavy.
- Format changes: the same line packs different products and sizes during the week; a cobot can switch palletizing patterns by program.
- Harsh environments: cold rooms and wet areas are uncomfortable for long shifts.
Where IoT and the digital twin come in
- Temperature and humidity: sensors track the cold chain and storage conditions.
- Quality: cameras and sensors check label, expiry date, seal and fill level.
- Packaging-line simulation: the digital twin helps predict bottlenecks and the effect of each format change.
Watch out for
- Hygiene: where there is direct contact with food, the robot, gripper and lubricants must be food-grade and the equipment must withstand the area’s cleaning process (including washdown, where applicable). Many applications avoid direct contact and handle only packaged product.
- Weight and pace: full pallets and heavy cases can exceed a cobot’s payload, and collaborative speeds may not keep up with very fast lines.
- Risk assessment: collaborative palletizers share space with operators and forklifts; the whole area must be assessed.