| Title |
Near-infrared-based quality control of plastic pre-concentrates in lightweight-packaging waste sorting plants |
| ID_Doc |
23222 |
| Authors |
Kroell, N; Chen, XZ; Küppers, B; Schlögl, S; Feil, A; Greiff, K |
| Title |
Near-infrared-based quality control of plastic pre-concentrates in lightweight-packaging waste sorting plants |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.resconrec.2023.107256 |
| Abstract |
Today's post-consumer plastic recycling is limited by labor-intensive manual quality control (MQC) procedures, resulting in largely unknown pre-concentrate purities. Sensor-based quality control (SBQC) could enable an automated inline quality monitoring and thus contribute to a more transparent and enhanced plastic recycling. Therefore, we investigated the technical feasibility of near-infrared-based SBQC for plastic pre-concentrates in a lightweight packaging waste sorting plant. The developed SBQC method outperformed MQC methods by reducing measurement uncertainties from between +/- 0.8 wt% and +/- 6.7 wt% (MQC) to +/- 0.31 wt% (SBQC) for bale-specific purities at monolayered material flow presentations. In addition, we show that SBQC may even be possible at multilayered material flow presentations, although further research is needed to address identified segregation effects. The demonstrated technical feasibility of SBQC at plant scale represents a major break-through as it opens new opportunities in plastic recycling, such as adaptive pricing models and intelligent process control in sorting plants. |
| Author Keywords |
Sensor-based material flow characterization; Automated quality control; Inline quality monitoring; Circular economy; Mechanical post-consumer plastic recycling; Machine learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001128077500001 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.resconrec.2023.107256
|