Intelligent Solutions for Food Processing

Food Processing & Forming

Problem

Manual shaping is slow (20-30 pieces/min) with >±5% weight variance, causing inconsistent baked goods.
Dough stickiness leads to residue buildup on grippers, requiring 30% downtime for cleaning.

Solution

Food-grade silicone gripper + dynamic pressure control enables 60 pieces/min shaping with <±1% weight error.
Self-cleaning design (FDA 21 CFR compliant) cuts cleaning to 5 minutes/shift.

Meat Cutting

Problem

Manual cutting produces 15% meat scraps, with blades requiring replacement every 2 hours.
Frozen meat hardness variations cause inconsistent cuts, yielding >8% defects.

Solution

Vbot Series with 3D vision systems + force-adaptive cutter adjusts parameters in real-time, reducing scraps to <5%.
Blade wear monitoring extends service life to 8 hours/use.

Sorting & Packaging

Problem

Sorting delicate items like pastries and fresh fruit poses challenges. Manual sorting often results in over 5% errors, especially during busy seasons when temporary labor is hired, increasing training costs by 20%. Traditional vibrating screen sorters, though fast, are harsh on fragile products like strawberries, with damage rates up to 12%.

Solution

Integrating the Vbot Series with advanced AI vision and precision-engineered soft suction cups significantly improves sorting speed and accuracy. The system performs up to 300 picks per minute while detecting defects with an accuracy of ±0.3mm, achieving error rates below 0.5%. Air-cushion conveying protects sensitive products by minimizing impact, reducing breakage to under 2%.

  • Vbot Series + AI vision + soft suction cups achieve 300 picks/min with ±0.3mm defect detection, error rate <0.5%.

  • Air-cushion conveying reduces impact, keeping breakage <2%.

Inspection & Quality Control

Problem

Manual sampling is slow (5-10 pieces/min) with high missed detection rates for micro contaminants (e.g., metal/glass fragments), posing food safety risks.
Traditional optical sorters only detect surface flaws, failing to identify internal moisture variations (e.g., underbaked cookie centers).

Solution

Revopoint robot + Hyperspectral Imaging System for dual functions:
Contaminant detection: Identifies ≥0.3mm metal/plastic/hair with >99.5% accuracy.
Moisture mapping: NIR spectroscopy monitors moisture gradients in real-time (<±0.8% error).
AI-powered sorting: Auto-classifies defects and triggers rejection at 60 pieces/min.

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Technical Support

  • Compatible Devices

    Revopoint 3D camera vision system

  • SDK Support

    SDK interface supports the rapid
    development of more applications

  • Download Center

    Get the latest software and
    hardware manual to help you start

Why Choose Us

  • Streamlining

    Workflow

  • Improved

    Production Efficiency

  • Safety

    and Stability

  • Superior

    Performance