Grün HDF-R Series AI-Driven Sorting System

E-scrap shred recycling presents a core challenge defined by extreme material complexity: e-scrap streams are mixed with high-value engineering plastics, copper, and aluminum, commingled in unpredictable combinations, with varying particle sizes, shapes, and surface features.

The Grün HDF-R Series is an intelligent machine-vision-based sorting system tailored 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 on e-scrap shreds. Coupled with high-performance air ejectors, it efficiently identifies and recovers high-value fractions such as plastics, copper, and aluminum from material streams within milliseconds, based on surface feature differences.

Empowered by AI-driven surface feature recognition algorithms, the system can conduct deep learning training based on real production data, continuously optimizing the machine vision detection accuracy. This means the equipment’s performance is not fixed at the time of factory shipment; instead, it continuously adjusts and improves with the accumulation of production data, delivering stable and reliable sorting performance to help e-scrap recyclers significantly boost recycling efficiency and commercial value.

Technical Features

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

Material surface features are clearly captured, providing reliable image input for AI algorithms and ensuring the accuracy and stability of surface defect recognition.

● Innovative Dual-Belt Sorting Structure

High-sensitivity sorting is performed on the upper level to establish extremely high purity of the main material stream; secondary re-inspection of upper-level rejects is conducted on the lower level, ensuring effective recovery of high-value fractions mixed within.

● Proprietary AI Deep Learning Algorithms

Trained against comprehensive identification and sorting standards, the system uses deep learning to replicate the surface-feature judgment logic of manual picking. The AI model can be continuously optimized with new production data, driving ongoing improvements in sorting accuracy.

● High-Intensity LED Illumination

A constant imaging environment is maintained with clear and stable images, unaffected by external light changes, guaranteeing consistent detection results across different time periods and batches.

● High-Performance Air Ejector

Equipped with in-house, high-power, high-speed air ejectors, the system delivers high-precision material rejection and ensures long-term stable operation even under high-throughput sorting conditions.

● Multi-Specification Model Portfolio

Available in two models with belt widths of 600 mm and 1200 mm, to meet varying throughput requirements.

Typical Applications

● Plastic Sorting

✦ Separates engineering plastics such as ABS, PC, and PP by color and surface feature variations (burnt/oxidized material).

✦ Distinguishes matte black ABS from glossy black PC by detecting surface gloss variation and subtle color differences (a separation that is visually indistinguishable under standard lighting).

* For polymer-type identification and material-grade separation, Lauffer offers the VPMC series, equipped with SWIR imaging technology for precise classification of ABS, PC, PP, and other engineering plastics by chemical composition.

● Appliance Sorting

✦ Separates copper tubes (reddish-brown) from aluminum heat sinks (silver-white) in refrigerator and air conditioner shredder output.

✦ Separates copper windings (high reflectivity) from silicon steel sheets (low reflectivity) in washing machine motor shredder mixes.

● Battery Sorting

✦ Recovers high-value electrode materials from shredded lithium-ion battery cell fractions by distinguishing copper foils (reddish-purple) from aluminum foils (silver-white), enabling clean separation of anode and cathode current collectors for downstream hydrometallurgical processing.

Specifications