Data-driven AI-assisted digital framework for enhancing circularity in manufacturing

The DATA4CIRC project aims to enhance circularity within the manufacturing sector to facilitate decarbonisation whilst improving competitiveness and boosting the adoption of R-strategies.

These objectives will be achieved by providing the sector with the proposed DATA4CIRC solution, a human-centred collaborative digital framework that leverages the power of data and cutting-edge digital technologies for assets digitalisation.

This framework will comprise (A) Federated Data Spaces, (B) Digital Models of the circular value chains and products; (C) Digital Product Passport (DPP); and (D) an AI-assisted end-to-end LCA tool.

The integration of these tools into a single framework will improve data interoperability and accessibility, therefore boosting the collaboration and the establishment of circular value chains. To do so, (E) ontologies and semantic models will be leveraged and proper user-friendly interfaces will be developed.

Furthermore, the DATA4CIRC solutions will be based on existing standards and architectures to maximise their adoption and impact.Special focus will be placed on social aspects for the transition to circular business models which prioritise the needs, expectations and experiences of end-users.

By embracing the social innovation paradigm, human involvement throughout the project is boosted through co-creation and co-validation activities.

Moreover, an upskilling and reskilling training programme will be designed and conducted to facilitate the uptake of digital tools in the manufacturing workforce during the project and beyond its completion.

Validation and demonstration of the DATA4CIRC solution will be achieved via three use cases, thereby consolidating successful progress from TRL4 to TRL6.

The selected use cases are circular value chains in manufacturing sectors with high impact potential and significant room for improvement regarding the field of circular economy: the electronics, plastics, and automotive sectors.