From Lab to Line: AI and Automation in Sustainable Plastics

Photo by Lalit Kumar on Unsplash  

New research shows that the global bioplastics sector is set to be worth US$15.6 billion by 2035. Sustainable plastics are emerging as critical materials in the transition to a circular economy. Yet the development and deployment of these materials face a unique set of challenges, from feedstock variability to scaling production and efficient distribution. Enter digital technologies. Artificial intelligence (AI), machine learning (ML), and automation can transform the sustainable plastics value chain, accelerate innovation and improve efficiency.

German manufacturer Reifenhaüser recently announced plans to incorporate AI and automation into production to boost factory output and address labour shortages. How would this work in practice? It begins at the early stages of research and development. Machine learning models can enable the rapid screening of bio-based monomers and additives, reducing reliance on trial-and-error lab work. AI tools can simulate environmental impacts across a plastic’s lifecycle (from raw material sourcing to end-of-life scenarios), helping researchers to prioritise low-impact alternatives. Digital twins and predictive modelling allow researchers to simulate production conditions (e.g., temperature, pressure, catalysts) to fine-tune polymerisation processes for better yield and lower energy use.

Automation is the next step, streamlining the production of sustainable plastics and making them more commercially viable. Internet of Things (IoT) sensors and AI algorithms can monitor real-time data from reactors and extruders, adjusting parameters to maintain quality and reduce waste. Automated systems can also manage raw material feeding, mixing, and packaging, minimising human error and reducing contamination risks. Lastly, AI-driven control systems optimise energy consumption during processing, aligning with sustainability. NatureWorks, a leading PLA biopolymer producer, uses automated systems to control fermentation and polymerisation in their production, improving consistency and reducing carbon emissions.

Distribution is key to scaling sustainable plastics, and digital technologies are enabling smarter, greener logistics. Blockchain and AI can track the origin, composition, and carbon footprint of plastic products, supporting traceability and compliance with ESG standards. Machine Learning models analyse market trends and customer behaviour to predict demand, reducing overproduction and inventory waste. AI-powered platforms facilitate the collection and sorting of plastics for recycling or composting. Circularise, a Danish blockchain-based platform, enables brands to trace recycled content in plastic products, enhancing trust and accountability in the supply chain. 

The integration of digital technologies into the sustainable plastics ecosystem is not just a technical upgrade. By merging data-driven intelligence with environmental stewardship, the sustainable plastics sector can unlock new pathways for innovation, scale, and circularity.