Ongoing Projects
Tec4MaaSEs
This project aims to deploy a network of Digital Twins (DT), equipped with trustworthiness and cognition, to co-operate in a distributed manner within a value network as core enablers of Manufacturing-as-a-Service (MaaS) practices.
Lab Contribution: Our lab leads the development of the semantic framework, applying IMF to enable structured, machine-readable data exchange across manufacturing ecosystems. We also support integration with the Asset Administration Shell (AAS) and contribute to standardization for interoperable industrial data exchange.
SM4RTENANCE
This project aims to leverage AI-driven predictive maintenance (PdM) and dynamic asset management to scale collaborative solutions across Europe, and harmonise data spaces into a data space federation.
Lab Contribution: The IM Lab contribution to this project is focusing on the application of the IMF methodology in selected project pilots, including key elements of the design of Data Products for manufacturing assets and associated Data Spaces.
CRCMAN 5.0
This project aims to develop a human-centred, AI-aided digital framework designed to optimise the entire lifecycle of PV products—from design and production to end-of-life recovery.
Lab Contribution: Our lab has focused on industrial case analysis, system design, and semantic modeling and is developing system models and ontologies ensuring consistency, interoperability, and a solid foundation for digital integration.
Upcoming Projects
EuroFMX
This project builds a European ecosystem of generative AI and frontier models for manufacturing. It aims to enable trustworthy, sovereign, and human-centric AI to strengthen industrial competitiveness and resilience.
Lab Contribution: Our lab develops the semantic data foundation using an MBSE approach based on IMF and ISO/IEC 81346. We design behavior-aware, multi-layered knowledge graphs aligned with Industrial Ontologies Foundry (IOF) standards.
CIRCULARIS
This project develops a harmonised indicator framework to assess circular economy performance in the food service sector. It integrates systems science, data ethics, and digital innovation to support better decision-making and governance.
Lab Contribution: Our lab contributes system analysis, design, and semantic modelling, developing system models and ontologies for interoperable data integration. We also support compliance with standards and regulations, enabling AI-driven recommendations for automated decision support.
Achieved Projects
EU3KA
This project developed a unified framework for coordinating COVID-19 response across digital, manufacturing, health, and certification domains. It integrated technologies and standardized processes into a scalable Plug&Respond platform to enable rapid, reliable, resilient, and robust crisis response.
Lab Contribution: System design and semantic modelling, developing system models and ontologies to ensure interoperability and consistency. These supported the integration of diverse technologies and processes within the platform.
PLOOTO
This project aims to deliver a Circular and Resilient Information System (CRIS) to support manufacturers in their green, digital and circular transition, and enable waste reduction and end-to-end traceability of Secondary Raw Materials.
Lab Contribution: System design and semantic modelling, developing system models and ontologies to ensure interoperability and consistent data integration. Supporting the standardization of the Digital Product Passport (DPP) in alignment with European initiatives.
ONTO COMMONS
This project focused on standardizing data documentation across materials and manufacturing domains. It developed interoperable ontologies to enable data sharing, support digital innovation, and advance a unified European data ecosystem.
Lab Contribution: Expertise in ontology engineering and data interoperability. We also co-led demonstrator development and community activities to support adoption and standardization.
RE4DY
This project aims to build a framework for smart products and connected Factory 4.0 ecosystems, enhancing data pipelines, digital threads, and digital twin interoperability to accelerate adoption and lower implementation costs for Zero-X smart manufacturing.
Lab Contribution:Our lab developed semantic technologies and knowledge models to support resilient manufacturing. Using IMF and linked data, we enabled machine-readable representations of industrial systems, supporting data integration, anomaly detection, and optimization in industrial pilots.