KIOptiPack

AI-based Optimization of Plastic Packaging

Comprehensive AI-based optimization of plastic packaging with recycled content.

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Funded R&D | Funder: BMBF | Budget: €20M | Year: 2025 | Role: AI Partner

KIOptiPack (08/2022 – 07/2025)

AI-based Optimization of Plastic Packaging with Recycled Content

KIOptiPack

KIOptiPack aims to drastically reduce emissions and petroleum consumption by optimizing plastic packaging with AI and recycled materials.

Problem Statement

Plastic is known for its versatility and functionality, especially in packaging. The low reuse rate of recycled materials in packaging, currently at about 11%, presents a challenge to sustainability goals. Factors such as fluctuating properties and limited availability of high-purity batches hinder recycled materials usage.

Project Goal

The project seeks to develop AI-based tools for successful design and production of plastic packaging with high recycled content. These tools will be validated and implemented in a data-driven application space, encompassing processes like design under recyclability and functionality, extrusion production, and forming.

IKV-Lab — Institute for Polymer Processing, RWTH Aachen.

IKV-Lab — Institute for Polymer Processing at RWTH Aachen.

Project Approach

The project involves establishing a data infrastructure, developing new analysis and process optimization tools, and ensuring continuous sustainability evaluation. A central networking platform facilitates collaboration with partner projects like K3I-Cycling, enhancing insights for lifecycle assessments and optimizing the overall system.

Innovations and Perspectives

Fraunhofer UMSICHT leads sustainability assessments, validating processes against ecological criteria to minimize climate impact. Investigations include material stability and perception by consumers to prevent “Greenwashing.” Tools developed within the project guide packaging manufacturers in sustainable decision-making.

Project Details

Project Partners

Funding Information