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AI REDGIO 5.0
Project reference: 101092069
Start/end: January 2023 – December 2025
Total Cost: 7 462 614.00
Call: HORIZON-CL4-2022-TWIN-TRANSITION-01
Topic: HORIZON-CL4-2022-TWIN-TRANSITION-01-06
The I4MS program in H2020 has been and is a great success for the Digital Transformation of European Manufacturing SMEs. Phase IV of the program was focussing on DIHs and on highly innovative technologies like Digital Twins and AI. In particular, the AI REGIO Innovation Action developed a virtuous alliance between Regions, DIHs, AI solution providers and Manufacturing SMEs, which is materialized by a new methodology for DIHs service portfolio and customer journey analysis, an AI4EU-oriented toolkit of Data and AI resources, a network of Didactic Factories and their TEchnology and REgulatory SAndboxes (TERESA) and an ecosystem of SMEdriven experiments and their Digital Transformation pathways. It is time now to align such important outcomes to the evolution of Manufacturing towards Industry 5.0, the evolution of cloud AI Technologies to AI-at-the-Edge, the evolution of H2020 to Horizon and Digital Europe programs e.g. to EDIH, Data Spaces, and AI TEFs (Testing and Experimentation Facilities) for Manufacturing. Some of the AI REGIO I4MS Phase IV motivations have now evolved: it is time for AI REDGIO 5.0 to keep the momentum of AI technologies adoption in Manufacturing SMEs. AI REDGIO 5.0 aims at renovating and extending the H2020 I4MS AI REGIO alliance between Vanguard EU regions and DIHs for a competitive AI-at-the-edge digital Transformation of Industry 5.0 Manufacturing SMEs. AI REGIO outcomes (methods and tools for DIHs governance and cross-DIH collaboration; Data Space and AI for Manufacturing toolkit; Didactic Factories network and TERESA facilities; SME-driven experimentations in 14 Vanguard regions) will be i) extended to the I5.0 principles; ii) enabled by the newest trusted technologies along the edge-to-cloud continuum; iii) supported by European open source hw/sw reference implementations, preserving EU values and ethical principles; iv) interconnected with the EDIH network in DEP as well as with the AI TEF nodes and the Data Spaces deployment program.
Polycom is responsible for performing the Use-Case is a small-scale demo/experiment (for one production cell/process) of predictive maintenance scenario in POLYCOM. The scenario will consist of data infrastructure, edge devices and algorithms that will detect and measure the condition of the molding tools. The demonstrated system will enable operators to continuously monitor the condition of machines and tools and general process operations (changes/events on a daily base). Predictive maintenance will be based on active monitoring of the production process, where several data sources will be gathered from the production set-up (material, production parameters and signals, end-quality measurements). Deviations in the performance of specific assets (tool and machine) will be monitored using AI technologies deployed on the local edge device.
