EMPYREAN envisages a hyper-distributed computing paradigm, based on federations of collaborative and heterogeneous IoT devices and resources (e.g., on RISC-V) across different providers and networks. These federations, namely Associations, operate autonomously and interconnect seamlessly utilizing distributed, cognitive and dynamic AI-enabled decision-making, to balance computing tasks and data inside an Association as well as between Associations in a multi-agent manner and across central computing environments, optimizing resources and providing scalability, resiliency, energy efficiency and quality of service. An Association will constitute a trusted execution environment, while identity and data access management schemes will assure controlled access and confidentiality of data, utilizing Cluster 3 related outcomes from participating partners. EMPYREAN will also be empowered with automated tools and mechanisms for efficient data processing of AI-workloads and secure distributed edge storage. Developed technologies will also enable Associations-native application development and deployment, contributing to the entire application lifecycle and interoperability. EMPYREAN will provide open and standardized APIs, while utilizing and extending open-source platforms maintained by European companies from the consortium. EMPYREAN will demonstrate its advanced and innovative capabilities through three well-defined use cases that involve device- and data-rich applications in advanced manufacturing, smart agriculture and warehouse automation, involving AI-driven value extraction from high volume and dynamic IoT data generated by multiple sources (e.g., robots) at the edge of the network. Also, a South Korea based use case in smart factories will further showcase the benefits of the EMPYREAN’s technologies. EMPYREAN will develop its Association-based continuum through synergies with emerging IPCEI initiatives and EU bodies (e.g., GAIA-X, IDSA) by involved partners.

In the current complex socio-economic situation, European producers face challenges posed by a growing scarcity of raw materials and goods, fluctuating costs and unpredictable delivery times. According to the EU agenda, they must contribute to reducing the environmental impact of manufacturing processes to prevent climate change and to achieve zero carbon emissions. Thus, the only sustainable option is to rethink the Life Cycle of goods and search for new approaches to give new life to End of Life (EoL) products. Grounding on this vision, the RemaNet project aims to enable a widespread diffusion of the concepts of remanufacturing, recycling, material saving and functional upgrading by implementing a factory-integrated digital platform able to extend the remanufacturing value chain. The main project goal is to establish a new remanufacturing business model by creating a community where different actors can make available their specific know-how and contribute to any step of the remanufacturing process. To achieve this goal, multiple digital tools will be developed on the RemaNet digital platform. Horizontal tools will help matching supply and demand, also providing secure data sharing to spread the needed competences in terms of human resources or digitized formalized knowledge. Vertical tools will enable the integration of shopfloor and process data with advanced tools for monitoring, prognostics and full traceability of material and information flows as well as cutting edge remanufacturing technologies. The digital platform will provide a standard for manufacturing and re-manufacturing with an integrated and easy-to-use infrastructure fostering a reliable and secure data flow, access, and use at all levels, from shopfloor and further along the value chain. The proposed business model and digital solutions will be validated in five use cases ranging from automotive to mold and dies, and to the energy sector and its decarbonization.

COGNIPLANT project will develop and demonstrate an innovative approach for the advanced digitization and intelligent management of the process industries. This approach will be based on a novel vision to data monitoring and analysis, that will make the most of the latest developments on advanced analytics and cognitive reasoning, coupled with a disruptive use of the Digital Twin concept to improve Production plants’ operation performance by up to 68% in real time control of the productive environment, 65% in quality control of the final products and 70 % in response time to uncontrolled incidents. The concept will be implemented by four end-users from four different SPIRE industries, one chemical industry in Austria, one aluminum refinery in Ireland, one concrete manufacturing industry in Italy and one metal industry in Spain. The COGNIPLANT solution will provide a hierarchical monitoring and supervisory control that will give a comprehensive vision of the plants’ production performance as well as the energy and resource consumption. Advanced data analytics will be applied to extract valuable information from the data collected about the processes and their effect on the production plant’s overall performance enabling to design and simulate operation plans in digital twin models based on the conclusions. As a result, optimal operation plans will be obtained that will improve the performance of those cognitive production plants. In addition, the project will demonstrate the positive impact derived from the implementation of COGNIPLANT solution that will allow industries reducing their CO2 emissions up to 20%. A training strategy will be designed to provide a comprehensive framework for the dissemination of the project outcomes and a clear understanding of the new solution for the employees of the SPIRE sectors.