Grün VFG Series AI-Driven Sorting System

Dry glass cullet recycling faces a sorting challenge: mixed container glass, MRF glass, or flat glass cullet is mixed with glass of various hues, opaque impurities, ceramics, stones, and heat-resistant glass. These materials differ in color, brightness, and transparency, and accurate identification of colors and impurities often determines the final commercial value. For glass recyclers, the ability to efficiently classify glass by color and type, while detecting and removing non-glass impurities, is the key to producing high-purity, furnace-ready cullet.

The Grün VFG Series is an intelligent vision-based sorting system tailored for this exact scenario. It employs high-resolution RGB (HR-RGB) VIS imaging and proprietary AI deep learning algorithms to perform real-time scanning and surface feature analysis of dry container glass, MRF glass, or flat glass cullet with a particle size of 4–70 mm. Combined with high-performance air ejectors, the system efficiently sorts high-value glass fractions from waste streams within milliseconds.

Empowered by AI-driven surface feature recognition, the system continuously learns from real production data, steadily improving its detection accuracy. This means the equipment's performance is not static after deployment; instead, it continuously adapts and improves as production data accumulates, delivering stable and reliable sorting performance. This enables recyclers significantly improve cullet purity, remove impurities, consistently deliver recycled glass that meets the strict quality specifications of glass manufacturers, and command a premium in the market.

Technical Features

● High-Resolution RGB (HR-RGB) VIS Imaging

Clearly presents surface features of the material, providing reliable image input for AI algorithms. Efficiently identifies glass colors (clear, amber, green, etc.) and a wide range of contaminants (ceramics, stones, porcelain, metals, and plastics).

● Proprietary AI Deep Learning Algorithms

Enhances surface feature recognition and supports model retraining with real-world production data, continuously improving the detection accuracy through deep learning.

● Wear-Resistant Design

Utilizes special alloy chutes optimized for the high hardness and abrasiveness of glass, effectively resisting wear to reduce maintenance costs and ensure long-term stable operation under high-throughput conditions.

● High-Intensity LED Illumination

Maintains a constant imaging environment with clear, stable images unaffected by ambient light variations, ensuring consistent detection results across different periods and batches.

● In-House High-Performance Air Ejector

Delivers high-precision material rejection and ensures long-term stable operation even under high-throughput sorting conditions.

● Multi-Specification Model Portfolio

Offers configurations with 4 and 6 chutes, meeting diverse throughput requirements.

Typical Application Scenarios

✦ Glass Recycling Plants

✦ Bottle-to-Bottle Recyclers

✦ Solar Glass Producers

Specifications