Projects

At its core, the project investigates the synergies between AI, the Digital Product Passports (DPP) and circular engineering to make value chains more resource-efficient and transparent. By combining AI methods, knowledge graphs, and data space technologies, lifecycle data is semantically linked to identify circular innovation potential early in the engineering phase. This approach ensures regulatory compliance and increases global competitiveness through improved data integration and automation.

The Wuppertal Institute leads the work package, which focuses on the development of a circular engineering process based on a 150 per cent reference model as a guiding framework for iPP-enabled engineering. This includes an analysis of the practical organisational impacts, the derivation of specific implementation implications, and the development of compact guidelines. Based on a cross-case analysis of the pilot projects, design principles and best practices will be developed to serve as a foundation for action and transformation for companies.

In the project „Enabling Circular Value Chains via Production Digitization and Human Empowerment“ (ENCIRCLE), the Wuppertal Institute is collaborating with 14 international partner organisations to develop the industrial basis for a digitally-enabled Circular Economy. The EU-funded project aims to fundamentally transform the prevailing linear production methods.

Innovative technologies such as artificial intelligence, digital twins and digital product passports are at the heart of ENCIRCLE. Using these tools, the researchers put conventional production methods to the test – and develop sustainable, circular alternatives. In this way, they create the conditions for keeping products and materials in circulation in industrial ecosystems. The focus lies on combining technological innovation, upskilling of the workforce and improved information flow as well as enabling end consumers to make more sustainable decisions.

ENCIRCLE pursues a holistic approach with three main objectives:

In addition to technological innovations, the project partners also incorporate legal and ethical issues into their research. The project is being funded as part of the EU’s Research Framework Programme Horizon Europe and will run for three years.

The „Green AI Hub for SMEs“ is part of the five-point programme „Artificial Intelligence for the Environment and Climate“ launched by the German Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety’s (BMUKN). It aims to bring the benefits of Artificial Intelligence (AI) for resource efficiency closer to small and medium-sized enterprises (SMEs). To this end, the project team drives forward the research, development, testing and practical implementation of resource-saving AI technologies. Together with selected SMEs, practicable AI pilot applications are developed for operational challenges, such as the optimisation of logistics or digitally integrated solutions for the maintenance of machinery or the closure of material flows in the industry. 

The aim of the project is to develop a development methodology for Sustainable Lifecycle Engineering (SLE) with a focus on Circular Economy. It will enable product and process developers to integrate sustainability aspects into their decision making already in the early phases of engineering.
The methodology is based on existing Model-based Systems Engineering (MBSE) approaches, which are extended to include sustainability aspects and requirements along the entire product life cycle. The model-based representation of individual sustainability aspects is intended to enable developers to weigh up the effects of individual solution options on sustainability at an early stage and in a transparent manner.

The scientists of the Wuppertal Institute are investigating which aspects of sustainability in engineering need to be taken into account along the entire product life cycle. To this end, the individual dimensions of sustainability in relation to engineering must be recorded and processed in a transparent manner.