SWIR Technology for Plastic Sorting and Material Identification
1. Introduction
As global attention to environmental protection and resource reuse intensifies, the efficiency and accuracy of plastic recycling and material sorting have become critical. Traditional sorting methods are slow and error-prone, unable to meet modern production demands. Short-wave infrared (SWIR) technology, with its unique optical properties and high sensitivity, is emerging as a key solution for plastic classification and material sorting. This paper discusses the application of SWIR in plastic identification and material sorting, and analyzes its advantages in improving automated sorting efficiency and promoting resource reuse. Zhuhai Tianhui is a SWIR solution designer and light-source supplier.
2. SWIR Technical Principle
SWIR uses the 1000–1700 nm band, offering:
- Molecular vibrational spectral response: Different polymers show characteristic absorption peaks that act as material “fingerprints”
- High penetration: Light penetrates the surface, detecting internal structure independent of surface contamination or coatings
- Thermal radiation characteristics: Sensitive to micro-structural changes within materials
3. SWIR in Plastic Classification
3.1 Technical Implementation
- Spectral measurement & analysis: SWIR cameras (InGaAs) collect reflected spectra; real-time machine-learning algorithms perform identification
- Multispectral SWIR imaging + high-speed robot arms: On-the-fly spectral analysis and sorting
3.2 Case Studies
- Plastic recycling: Differentiates near-transparent PET vs PVC (absorption peaks at 1.4 µm & 1.7 µm); purity >99 %
- Industrial waste sorting: Identifies materials despite dust/film (≤2 mm); unaffected by surface soiling
- High-precision plant: SWIR line sorts PP/PE mix (with dust, films) at 1000 kg/h, 99.5 % accuracy, <0.5 % false-sort; saves ≈600 k¥ labor/year, boosts recycled-plastic purity to 99 %
4. SWIR in General Material Sorting
4.1 Technical Implementation
Same spectral/imaging approach, extended to metals, glass, paper.
4.2 Case Studies
- Metal recovery: Separates Al, Cu, Fe (purity >98 %)
- Industrial waste: Penetrates dust/film; immunity to surface contamination
- High-precision metal line: SWIR sorts Al/Cu mix at 1200 kg/h, 99 % accuracy, <0.5 % error; saves ≈700 k¥ labor/year, purity up to 98 %
5. Boosting Automated Sorting Efficiency & Resource Reuse
- All-weather operation: Stable performance in haze, smoke, day or night
- High-accuracy recognition: Low scattering & polymer-specific peaks deliver >99 % purity
- Data-driven intelligence: Real-time analytics predict mis-sort trends, allowing proactive adjustments
6. Future Trends & Challenges
- Sensor fusion: SWIR + mm-wave radar/LiDAR for even higher precision and robustness
- AI-driven management: Big-data & deep-learning algorithms will forecast sorting issues and auto-tune parameters
- Challenges: Further improve accuracy/reliability; secure sorting data against leakage; reduce system cost for mass deployment
7. Conclusion
SWIR technology offers broad prospects for plastic and mixed-material sorting. By lifting automated recognition speed and accuracy, it increases recycling rates and supports environmental protection. Future advances will expand SWIR into more waste streams and circular-economy applications.
Leveraging deep penetration and low scattering of SWIR LEDs, Zhuhai Tianhui has deployed SWIR solutions for internal-defect inspection and sorting of resins, plastics and silicon. The non-contact, non-destructive, on-line systems raise first-pass yield and cut rework/recall costs. Tianhui’s LED modules—using DOWA dies—have proven their precision, ease of integration and long-term stability in electronics, automotive, food packaging, plastic recycling and semiconductor fabs, becoming a key optical engine for quality upgrades. Going forward, Zhuhai Tianhui will continue to integrate SWIR sources with multi-sensor fusion and smart algorithms, helping manufacturers move toward higher accuracy, lower cost and smarter quality management.