Plastic AI Tools Will Circulate Plastic Packaging in the Future

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Fraunhofer-Institut für Verfahrenstechnik und Verpackung IVV

Taiwan Machine Tool & Accessory Builders' Association (TMBA)

Wuxi InfiMotion Technology Co., Ltd.

Researchers at Fraunhofer IVV, in collaboration with 51 partners from industry and academia in the Innovation Lab KIOptiPack, are developing AI-supported optimization tools to circulate plastic packaging in the future.

In Germany, more than 60 percent of packaged goods are wrapped in plastic. Therefore, the plastics industry aims to promote the circular economy with the ideal packaging design (Design for Recycling). Ideally, packaging should have the highest possible recycled content. A new EU regulation also mandates that by 2030, packaging made of plastic must be produced with a minimum content of up to 35 percent recycled materials.

This is where the research of KIOptiPack comes in—together with project partners, researchers from the Fraunhofer Institute for Process Engineering and Packaging IVV are using artificial intelligence as a game-changer in recycling and for processing recyclate into packaging to meet the technical challenges and high demands of packaging production. The aim is to reduce plastic waste, create more sustainable packaging, and address the raw material demand through reuse as recyclate.

For this purpose, the researchers at Fraunhofer IVV have developed AI-based optimization tools and networked them using a data space. This makes it possible to circulate these packages and optimize them holistically. Besides the question of environmental compatibility and life cycle assessment, aspects of functionality, design, customer acceptance, and manufacturability are taken into account. Once all data is fully integrated, the AI tools propose the best possible packaging designs for a specific product while minimizing material usage. The data space captures all the necessary digital data on material properties, origins, and destinations and links them.

If recyclates are contaminated by undesirable substances such as foreign plastics, printing inks, or degradation products, this can significantly impair their quality and even render them unusable. Once plastics are circulated, they can essentially contain impurities.

Prof. Dr. Andrea Büttner

Uniform Terminology Needed for Dealing With Plastics

"To better incorporate recyclates into packaging solutions, a shared data space is essential," says Prof. Dr. Andrea Büttner, Director of the Fraunhofer IVV. "Recyclate is a valuable material. However, the quality of the recyclable plastic must be right. If recyclates are contaminated by undesirable substances such as foreign plastics, printing inks, or degradation products, this can significantly affect their quality and even render them unusable. Once plastics are kept in circulation, they can potentially contain impurities." This presents particular challenges for the industry. From recyclate manufacturers to companies producing packaging films, to the food industry, systematic data exchange and a uniform terminology for handling plastics are needed. This especially concerns polyolefins—the largest group of plastics, which can change significantly during their processing.

AI helps in choosing the right recycling method

"In order for recyclates to be processed to a high quality, AI-supported tools are needed. Our modular software solutions developed at Fraunhofer IVV support, among other things, the characterization and analysis of material properties and link information flows so that suitable application fields can be identified for recyclates with varying properties," says Dr. Matthias Reinelt, Head of the Shelf Life and Packaging Modeling Group at Fraunhofer IVV. "Our AI tool for packaging production uses as much information as possible about the recyclate to determine the optimal processing process, so that at the end of the process chain, for example, a sustainably manufactured yogurt cup with homogeneous wall thickness distribution and the desired shape can end up on the store shelf." The researchers also assess the quality of the recyclates using chromatographic analysis methods, which also utilize AI tools for improved substance identification. This is intended to prevent unsuitable or contaminated recyclates from entering the cycle despite good sorting.

The AI-based optimization tools and the interconnected data room of Fraunhofer IVV and the project partners are partially integrated directly into the production process of the respective manufacturers. Real-time suggestions for further processing depending on the recyclate used on the machines on-site are thus possible.

We cannot fill the recycling gap in the plastics sector in the long term with isolated solutions. Our AI-supported optimization tools, which interlink material and information flows, address the problem.

Prof. Dr. Andrea Büttner

AI Tools Address the Recyclate Gap

The use of recyclates in plastic products is steadily increasing, but despite this development, the amount of recycled plastics will not be sufficient to meet the mandated legal recyclate usage quotas. The gap between supply and demand for plastic recyclates will grow in the coming years. By 2030, the demand for recyclates is expected to exceed the supply by 30 percent. "With isolated solutions, we cannot fill the recycling gap in the plastics sector in the long term. Our AI-supported optimization tools, which integrate material and information flows, address the problem. We network actors from various industries and try to respond better to resource shortages," summarizes Prof. Büttner.

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