VISION: By 2030, Europe will lead the worldwide competition for an ethical and sustainable adoption of AI in Manufacturing, by integrating regional Digital Innovation Hubs and pan-EU open Digital Manufacturing Platforms via a cross-border network of SME-driven Industrial Experiments and Didactic Experimental Facilities. General Data Protection Regulations (GDPR) and Data Sovereignty will drive the European AI strategy for personal and non-personal Data Sharing Spaces.
The AI REGIO project aims at filling 3 major gaps currently preventing AI-driven DIHs from implementing fully effective digital transformation pathways for their Manufacturing SMEs: at policy level the Regional vs. EU gap; at technological level the Digital Manufacturing vs. Innovation Collaboration Platform gap; at business level the Innovative AI (Industry 5.0) vs Industry 4.0 gap.
POLICY. Regional smart specialization strategies for Efficient Sustainable Manufacturing and Digital Transformation (VANGUARD initiative for Industrial Modernisation) are so far insufficiently coordinated and integrated at crossregional and pan-EU level. SME-driven >AI innovations cannot scale up to become pan-EU accessible in global marketplaces as well as SME-driven experiments remain trapped into a too local dimension without achieving a large scale dimension. (Regional vs. EU Gap)
TECHNOLOGY. Digital Manufacturing Platforms DMP and Digital Innovation Hubs DIH play a fundamental role in the implementation of the Digital Single Market and Digitsing European Industry directives to SMEs, but so far such initiatives, communities, innovation actions are running in a quite independent if not siloed way, where very often Platform-related challenges are not of interest for DIHs and Socio-Business impact not of interest for DMP. (DMP vs. DIH Gap)
BUSINESS. Many Industrial Data Platforms based on IOT Data in Motion and Analytics Data at Rest have been recently developed to implement effective Industry 4.0 pilots (I4MS Phase III platforms). The AI revolution and the new relationship between autonomous systems and humans (Industry 5.0) has not been properly addressed in I4MS so far. (AI I5.0 vs. I4.0 Gap)
AI REGIO is following the 4 steps for VANGUARD innovation strategy (learn-connect-demonstrate-commercialize) by constantly aligning its methods with the AI DIH Network initiative and its assets with I4MS/DIH BEinCPPS Phase II and MIDIH / L4MS Phase III projects.
AI REGIO: Industry 5.0 for SMEs
Image recognition and localization of objects for the update of a manufacturing digital twin using RGB-D information processed in distinct computation layers (Cloud, Edge, Local).
Application of a Neural Network trained with Reinforcement Learning method aimed to assign production resources to tasks in a production schedule during its execution.
