AI as a game changer for plastic packaging
In the KIOptiPack innovation lab, researchers at the Fraunhofer Institute for Process Engineering and Packaging IVV are working with 51 partners from industry and science to develop innovative AI-supported optimization tools and a data room that links all players in the packaging industry and their data. The aim is to use AI tools to manage plastic packaging in a closed loop in the future.
Plastics are lightweight, durable and easy to process - true all-rounders among materials. It is therefore not surprising that more than 60 percent of packaged goods in Germany are wrapped in plastic. The aim of the plastics industry is to use the ideal packaging design (design for recycling) to promote the circular economy, minimize the impact on the environment and at the same time provide optimum protection for the packaged goods. Ideally, packaging should contain as much recycled material as possible. A new EU regulation also requires that up to 35% of plastic packaging be made from recyclates by 2030.
This is where the research of KIOptiPack comes in - one of two innovation labs of the AI Application Hub Plastic Packaging (see below "The AI Application Hub Plastic Packaging"), which is funded by the Federal Ministry of Research, Technology and Space. Together with the project partners, researchers at the Fraunhofer IVV are using artificial intelligence as a game changer in recycling and for processing recyclate into packaging in order to meet the technical challenges and high demands of packaging production. The aim is to reduce plastic waste, create more sustainable packaging and meet the demand for raw materials by reusing them as recyclate in order to ensure greater security of supply in Europe in a cycle-oriented manner. To this end, the researchers at the Fraunhofer IVV have developed AI-based optimization tools and networked them with the help of a data room. In this way, the numerous requirements for plastic packaging can be efficiently taken into account. In particular, this also makes it possible to manage this packaging in the cycle and optimize it holistically. In addition to the question of environmental compatibility and eco-balance, the aspects of functionality, design, customer acceptance and manufacturability are also taken into account. Once all the data has been fully integrated, the AI tools suggest the best possible packaging designs for a specific product while minimizing the use of materials. The data room collects and links all the necessary digital data on material properties, origins and destinations. In this way, it provides a common infrastructure for data exchange across factory boundaries. The data model on which the complete package is based, which makes data exchange between the various players possible in the first place, was also developed at the Fraunhofer IVV.
Digitalization of material flows to protect the consumer
"A shared data space is essential in order to better incorporate recyclates into packaging solutions," says Prof. Dr. Andrea Büttner, Director of the Fraunhofer IVV. "Recyclate is a valuable material. But 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 impair their quality and even render them unusable. As soon as plastics are recycled, they can in principle contain impurities." This poses particular challenges for the industry. From recyclate manufacturers to companies that produce packaging films and the food industry, a systematic exchange of data and standardized terminology is therefore needed when dealing with plastics. This primarily concerns polyolefins - the largest group of plastics, which can change significantly during processing.
AIhelps to choose the right recycling method
"AI-supported tools are needed to ensure that recyclates can be processed to a high standard. Our modular software solutions developed at the Fraunhofer IVV support, among other things, the characterization and analysis of material properties and link information flows in such a way that a suitable field of application can be identified for recyclates with fluctuating properties," says Dr. Matthias Reinelt, Head of the Durability and Packaging Modeling Group at the Fraunhofer IVV. "Our AI tool for packaging production uses as much information as possible about the recyclate to determine the optimal processing method, so that at the end of the process chain, for example, a sustainably produced yoghurt pot with a homogeneous wall thickness distribution and the desired shape can end up on the shelf." The researchers also assess the quality of the recyclates using chromatographic analysis methods, which also use AI tools to improve substance identification. The aim is to prevent unsuitable or contaminated recyclates from entering the cycle despite good sorting.
The AI-based optimization tools and the networking data room of the Fraunhofer IVV and the project partners are sometimes integrated directly into the production process of the respective manufacturers. Real-time suggestions for further processing depending on the recyclate used on the machines used on site are therefore possible.
AI toolsaddress the recyclate gap
The use of recyclate in plastic products is continuously increasing, but despite this development, the amount of recycled plastics will not be sufficient to achieve the statutory recyclate use quotas. The gap between supply and demand for recycled plastics will grow in the coming years. By 2030, the demand for recyclates is expected to exceed supply by 30 percent. "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. We are networking the players from a wide range of industries and trying to respond better to resource shortages," summarizes Prof. Büttner.
Experts from science, industry, politics and associations from all over Germany will be discussing the entire range of topics relating to plastics, packaging and their recycling at the "Zukunftsforum Kunststoffkreislauf" in Berlin from 1 to 3 July. The aim is to discuss innovative ways of achieving a transition towards a resource-conserving circular economy - and to put specific solutions into practice.
The "AI application hub for plastic packaging"
51 partners from business, science and society are working together in two innovation labs to close the loop for plastic packaging as far as possible: KIOptiPack for design and production and K3I-Cycling for mechanical recycling and sorting. They were set up to enable the cross-laboratory exchange of data and ensure that all relevant findings are considered across the entire value chain.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
Other news from the department business & finance
More news from our other portals
See the theme worlds for related content
Artificial intelligence (AI) for food and beverages
Artificial intelligence (AI) is optimizing the food and beverage industry through automated quality control and more accurate demand forecasting. AI plays a particularly important role in product development by analyzing taste preferences and market trends. This allows new products to be developed that are better tailored to consumer needs, increasing efficiency and customer satisfaction.
Artificial intelligence (AI) for food and beverages
Artificial intelligence (AI) is optimizing the food and beverage industry through automated quality control and more accurate demand forecasting. AI plays a particularly important role in product development by analyzing taste preferences and market trends. This allows new products to be developed that are better tailored to consumer needs, increasing efficiency and customer satisfaction.