Enabling Plastics Recycling With Digital Tools

Di-Plast Pilots

There is still a huge gap between the goals of the European Union for plastic recycling in 2030 and the status quo today. One key chance for closing this gap is the application of digital technologies like data science to improve processes and information flows throughout the entire recyclate supply chain.

Di-Plast develops and applies digital tools to enable high value plastics recycling, i.e. bring recycled plastics to its highest application possible. Supported by Interreg North-West Europe, we aim to close the knowledge and information gaps which inhibits plastics recycling. We enable companies to achieve access to highly relevant yet mostly hidden data, parameters and analytics from and for their own production processes. To realise this, our toolkit combines a distinct set of tools:

  1. VSM Tool: Value stream mapping to visualise and improve process-flows.
  2. Sensoring Tool: a process problem / solution case library to support with the selection of suitable sensor-based quality control mechanisms.
  3. Data Science Tools: This is a sub-toolkit of data science applications that creates, validates and extrapolates data:
    1. Data Validation Tool: Assesses data, gives insights in the variables and their data quality to increase the overall quality. Allows to prove stable processes and thus high quality recyclates to your customers.
    2. Exploratory Pattern Analytics Tool: Works on prepared/preprocessed tabular data. It provides explanatory patterns, i.e., simple rules between parameters (e.g., temperature, pressure) that are predictive for a certain target parameter (e.g., scrap rate). This helps to identify optimisation possibilities in your process through unveiling unrecognised correlations.
    3. Process Analytics Tool: Provides insights consisting of reports, visualisations and other analytical methods that describe the state of your processes and/or machinery. .Using this information, production processes with recyclates can be streamlined and output quality and quantity can potentially be increased.
    4. Machine Data Acquisition Tool: A wiki for selection of a data acquisition infrastructure based on your budget and technical expertise.
    5. Forecasting Tool: A system where information is combined to predict future quantities. This tool helps to create information of future supply of plastic recyclates and therefore enhance procurement and production planning.
  4. Matrix Tool: The Matrix tool helps to find matches for recycled plastic suppliers and converters based on multiple given constraints

Currently, we are testing our toolkit with several companies and to validate their fit to industry’s needs. However, we are still looking for partners to test and apply these tools and for companies interested to learn about them in our uptake acceleration management.

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