Periodic Reporting for period 2 - Circular TwAIn (AI Platform for Integrated Sustainable and Circular Manufacturing)
Reporting period: 2024-01-01 to 2025-06-30
The last years saw a surge of interest in cases for AI-based manufacturing such as predictive maintenance, quality and waste management and generative product design. Nevertheless, these cases are deployed independently from each other, do not make use of trusted AI and do not leverage data from circular value chains, in some cases barely digitized. This limits AI potential to enable a transition to holistic, end-to-end approach to sustainable manufacturing, to exploit the full potential of circular economy, while being acceptable and trusted by all stakeholders of the value chain.
Circular TwAIn is aimed to lower the barriers for all the stakeholders in manufacturing and process industry circular value chains to adopt and fully leverage trusted AI technologies, in ways that will enable end-to-end sustainability, i.e. from eco-friendly product and production processes design (i.e. ‘circularity by design’), to the maximum exploitation of production waste across the circular chain. To this end, the project is working to deliver a novel AI platform for circular manufacturing value chains, which will support the development of interoperable circular twins for end-to-end sustainability, fostering the transition to Industry 5.0.
To maximise its impact, Circular TwAIn has actively pursued collaboration and complementarity with other projects and initiatives. The digital and green transitions addressed by the project are deeply intertwined with the work of Made in Europe, supported by EFFRA and the AI4Manufacturing Project Cluster, as well as with ADRA and circular economy-related communities. Notably, recent projects such as DaCapo, AUTO-TWIN, and CIRC-UITS are working on Data Spaces for Circularity, creating valuable synergies.
Circular TwAIn has also initiated a strong collaboration with the Digital Factory Alliance (DFA)—of which ENG is a founding member—as a key vehicle to scale up project outcomes beyond the consortium and project timeframe. This collaboration led to the launch of the Sustainable Manufacturing Initiative, which aims to consolidate results under an impactful, long-lasting action. The initiative provides a platform where relevant projects and stakeholders contributing to the sustainability of European industries (and beyond) can promote their results and foster collective progress.
Moreover, the partnership with EFFRA has been further strengthened through the co-organization of the project’s final event, titled “Data, AI and Digital Twin Convergence for Efficient and Sustainable Manufacturing”, held at SPARKS in Brussels, back-to-back with the EFFRA General Assembly. This event provided a high-visibility platform to showcase project outcomes and engage with a broad community of stakeholders.
Circular TwAIn is aimed to lower the barriers for all the stakeholders in manufacturing and process industry circular value chains to adopt and fully leverage trusted AI technologies, in ways that will enable end-to-end sustainability, i.e. from eco-friendly product and production processes design (i.e. ‘circularity by design’), to the maximum exploitation of production waste across the circular chain. To this end, the project is working to deliver a novel AI platform for circular manufacturing value chains, which will support the development of interoperable circular twins for end-to-end sustainability, fostering the transition to Industry 5.0.
To maximise its impact, Circular TwAIn has actively pursued collaboration and complementarity with other projects and initiatives. The digital and green transitions addressed by the project are deeply intertwined with the work of Made in Europe, supported by EFFRA and the AI4Manufacturing Project Cluster, as well as with ADRA and circular economy-related communities. Notably, recent projects such as DaCapo, AUTO-TWIN, and CIRC-UITS are working on Data Spaces for Circularity, creating valuable synergies.
Circular TwAIn has also initiated a strong collaboration with the Digital Factory Alliance (DFA)—of which ENG is a founding member—as a key vehicle to scale up project outcomes beyond the consortium and project timeframe. This collaboration led to the launch of the Sustainable Manufacturing Initiative, which aims to consolidate results under an impactful, long-lasting action. The initiative provides a platform where relevant projects and stakeholders contributing to the sustainability of European industries (and beyond) can promote their results and foster collective progress.
Moreover, the partnership with EFFRA has been further strengthened through the co-organization of the project’s final event, titled “Data, AI and Digital Twin Convergence for Efficient and Sustainable Manufacturing”, held at SPARKS in Brussels, back-to-back with the EFFRA General Assembly. This event provided a high-visibility platform to showcase project outcomes and engage with a broad community of stakeholders.
Through the adoption and integration of advanced AI solutions with advanced circular manufacturing and re-manufacturing systems, the Project will enhance efficiency, productivity, and innovation while promoting sustainable practices and reducing environmental impact. By leveraging these AI capabilities, industry stakeholders can adapt more effectively to external and internal influences, such as market fluctuations, and regulatory changes, thereby increasing their capacity to thrive in dynamic and uncertain environments.
In the second reporting period, the consortium consolidated the outcomes of the Circular TwAIn project, marking a clear transition from strategy definition to execution.
The Exploitation Plan finalized during this phase confirms a comprehensive list of 37 Individual Exploitable Results (IERs), which have been strategically grouped into 12 Key Exploitable Results (KERs). These KERs span the full research-to-market continuum:
-Scientific KERs contribute to advancing knowledge and methodologies;
-Technological KERs provide enabling platforms and toolkits;
-Industrial KERs represent market-ready solutions tailored to specific industrial sectors.
The joint exploitation strategy has also been consolidated, focusing on bundling complementary results into coherent offerings aligned with use case specifications. This approach maximizes the innovation potential and market impact of Circular TwAIn, while ensuring alignment with partners’ strategic goals. These joint exploitation scenarios will serve as the foundation for future business development activities.
In the second reporting period, the consortium consolidated the outcomes of the Circular TwAIn project, marking a clear transition from strategy definition to execution.
The Exploitation Plan finalized during this phase confirms a comprehensive list of 37 Individual Exploitable Results (IERs), which have been strategically grouped into 12 Key Exploitable Results (KERs). These KERs span the full research-to-market continuum:
-Scientific KERs contribute to advancing knowledge and methodologies;
-Technological KERs provide enabling platforms and toolkits;
-Industrial KERs represent market-ready solutions tailored to specific industrial sectors.
The joint exploitation strategy has also been consolidated, focusing on bundling complementary results into coherent offerings aligned with use case specifications. This approach maximizes the innovation potential and market impact of Circular TwAIn, while ensuring alignment with partners’ strategic goals. These joint exploitation scenarios will serve as the foundation for future business development activities.
The ambition of Circular TwAIn is to apply a holistic approach of seamless modelling, enrichment and sharing of data across the entire circular value-chain. Technologies such as Artificial Intelligence and Digital Twins are already used in a variety of industrial use cases, but there is a limited integration in implementing circular manufacturing process chains and end-to-end waste optimization strategies at plant and value chain levels. This limitation should be overcome with the integration of the third technological pillar of the Project: the adoption of the emerging technologies to establish a Circular Material/Process/Product Data Space for AI-Based Sustainable Production. Circular TwAIn toolkit has been designed to unleash the sustainability potential of AI technologies in circular manufacturing chains through: (i) Introducing AI optimizations in stages where AI is still not used (e.g. AI-based product design, de-manufacturing); (ii) Using AI for multi-stage and multi-objective circular optimizations that could improve sustainability performance.