AI-PRISM is an industrial-end-user driven project that will provide a human-centred AI-based solutions ecosystem targeted to manufacturing scenarios with tasks difficult to automate and where speed and versatility are essential. The result will be an integrated and scalable ecosystem with installation-specific solutions for semi-automated and collaborative manufacturing in flexible production processes and for which specific robotic programming skills will not be required, thanks to its programming-by-demonstration modules. The ecosystem will be composed by four main pillars including 1) Human Centred Collaborative Robotic Platform, 2) Human Robot Cooperation Ambient, 3) Social Human-Agent-Robots Teams Collaboration and 4) Open Access Network Portal. In order to facilitate the assessment of the performance, transferability, scalability and large-scale deployment of these solutions, the demonstrations will be conducted under real operational environments in four pilot involving key manufacturing sectors - Furniture (ES), Food/Beverage (GR), Built-in Appliances (TR) and Electronics (PL) -, plus one generic demonstration facility (AT). The project is not just aiming at quantitative improvements in a specific sector, but to use technology innovation to support a change of paradigm where AI, robotics and Social Sciences and Humanities (SSH) integrated in the manufacturing domain for the improvement of flexible production processes, become a feasible and widespread alternative for European factories, especially SMEs. To achieve this, the project relies on a strong consortium of 25 partners from 12 countries including international cooperation with Korea. The consortium brings together all the actors of the Human Robot Collaboration (HRC) value chain including relevant competence centres, technology providers, equipment providers, integrators, and manufacturers/end users; and involves key expert partners in SSH, standardisation, exploitation, and dissemination.

SEISMEC will demonstrate an empowered, human-centred and ethical development of digital and industrial technologies in 17 pilots in 19 companies from 14 countries across 14 industrial ecosystems. It will do so through a two-way engagement in the development of technologies, empowering end-users and workers, and supporting social innovation, in a process labelled the SEISMEC shift. It will contribute to increased inclusiveness, by supporting a human-centred approach to technology development that is aligned with European social and ethical values (including gender and intersectional aspects). The benefits of human centrism will be measured in Creativity, Collaboration, Autonomy, Automation, Productivity, Privacy, Safety and job Satisfaction, the CAPS empowerment factors for human-centrism. SEIMSECs two-way engagement introduces technical innovations such as explainability, co-development, feedback methods and interfaces to enhance human centrism, but also incorporates plans, needs and innovations from companies and their workers steering them towards an empowered human-centric Industry 5.0 path. The consortium brings together institutions at the forefront of engineering, computer science, networking and exploitation, coordinated by a world-leading social sciences and humanities university, and building up on groundbreaking European projects on industrial innovation. SEISMEC pilots are representative of all sectors and company sizes, and most European countries and worker roles. Every industrial enterprise in Europe will be able to see some aspect of their activity reflected in SEISMECs pilots and will be able to learn from the project’s outputs through an active campaign of cross-sector empowerment practices exchange. With a strong engagement of European, national and local stakeholders, SEISMEC is landmark effort in European industry’s shift to empowerment and human-centrism, one that puts the worker and European Values at the core of its global competitiveness

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.

Procedural Knowledge (PK) is knowing-how to perform some tasks. For industry workers, PK is the knowledge required to carry out a specific job, like correctly executing the safety procedure during maintenance interventions, or configuring an industrial system by following the necessary steps in the right order, or adopting practices and behaviours to optimise energy consumption in a plant. The challenge in PK management is that this kind of knowledge may be hard to explain and describe, oftentimes it is poorly digitalised, and, even when documented, it may be still difficult to access and retrieve by industry operators. The PERKS project supports the holistic governance of industrial PK in its entire life cycle, from elicitation to management and from access to exploitation. PERKS bases its solutions on AI (both symbolic and subsymbolic) and data technologies, by advancing and integrating existing methodologies and tools in terms of readiness, flexibility and user acceptance. The results are applied and tested in three industrial scenarios (white goods production plant, computer numerical control machines, microgrid testbed) providing different use cases in terms of PK complexity and industrial requirements. Besides AI and data, the third pillar of PERKS is people: the goal is to satisfy the concrete needs of industry workers, providing them with digital support to better and easier perform their tasks following a human-in-the-loop paradigm, and putting them at the centre according to Industry 5.0 approaches. The outcomes of PERKS are: a reference architecture for PK management; a set of modular, interoperable and complementary digital tools to be composed and customised to industrial requirements; specific integrated solutions to solve the challenges of the project use cases; a set of methodologies and best practices for broader application in other industrial settings, paving the way for a wider transferability across contexts and sectors.

Growing challenges are identified during the last years in both passenger and freight mobility, such as urbanization trends, the increasing complexity of stakeholder scene, e-commerce, rising fragmentation of freight transport. Despite the various technical challenges and shortcomings, current governance and regulatory systems have proven so far inadequate, dealing with the passengers and freight transport systems as independent -and thus disconnected- sectors while integration between passenger and freight transport has been a subject of debate in the transport community over the last years with a peak coming after the recent Covid19 crisis. DELPHI focuses on the strategic dimension of integrating passenger and freight transport in a single system aiming to deliver the enablers -both on technical and governance/regulatory level, towards a federated network of platforms for multimodal passenger and freight transport, capable of sharing in a seamless and secure manner, cross-sectoral, multi-modal passenger and freight transport data, as well as traffic management systems information. Moreover, DELPHI will utilise novel and ultra-efficient methodologies for traffic monitoring such as UAS-powered monitoring, multi-/inter-modal optimisation, AI/ML-powered algorithms and frameworks, and will exploit diverse modes for hybrid passenger and freight transport in different ecosystem types. To achieve its maximum potential, utmost interoperability and best optimisation results, DELPHI’s digital framework and transversal tools will be validated in the context of 4 pilots with complementary requirements and features.