In an interview with K-MAG, Dr Sophie Pachner talks about why so little is recycled and what potential AI holds in plastics recycling.
Dr Pachner, of 6,300 million tonnes of plastic waste generated from 1950 to 2015, only 570 million tonnes were recycled. Why is the recycling rate so low? And how can we change that?
Dr Sophie Pachner: The challenge with plastics recycling is that the incoming material stream is very heterogeneous in its composition – shape, degree of contamination, etc. – but in the end the recyclates have to be of a consistently high quality so that they can be reused at all. In order to be able to produce a high-quality recyclate, not only precise waste sorting is required, but also flexible adaptation of the recycling processes to changing material flows.
However, these recycling processes are very complex: the feedstock is sorted, crushed, washed, prepared, extruded, degassed, filtered and processed into regranulate. Artificial intelligence can help us optimise these processes.
To what extent can AI optimise plastics recycling?
Pachner: Various companies work together along the value chain: Recycling collection points, companies that buy the waste, do the sorting and then the companies that produce the recyclates. A particular challenge in data management is the traceability of material flows along the value chain. However, the problem with cross-company data analysis is often that the companies do not want to disclose the data.
Here, universities and competence centres are developing privacy-preserving methods for data collection in order to obtain a holistic view of value chains in the future without having to exchange data across company boundaries. With the help of AI, waste will be networked and thus become "smart waste".
Artificial intelligence recognises patterns in production data, can warn in the event of anomalies, develop forecasting models, thus providing decision support for the customer and ultimately ensuring consistent product quality.