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 materialised 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 SME-driven 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 programmes e.g. to EDIH, Data Spaces and AI TEFs (Testing and Experimentation Facilities) for Manufacturing. Some of the AI REGIO I4MS Phase IV motivations are now evolved: it is time for AI REDGIO 5.0 for keeping 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.

ARISE will make industrial HRI deployments simpler, cheaper, and more widespread in Europe by developing and demonstrating the concept of AgileHRI. The ARISE project envisions a near future which aligns with the principles of Industry 5.0, prioritising resilient, sustainable, and human-centric work environments. In such a future, companies recognise that investing in industrial human-robot interaction (HRI) is essential for achieving better short- and long-term goals, rather than a cost. Human-centric approaches surpass traditional technology-driven approaches, with technology serving people rather than the other way around. Industrial HRI establishes its position as a game-changing asset that enables seamless collaboration between humans and robots on complex tasks, allowing them to work together in shifts of any length. On its way to materialise such a vision, the ARISE project will i) address major application challenges from today’s industry, ii) develop human-centric solutions, tools, and software modules which expand the state-of-the-art in industrial HRI, and iii) deploy industrial HRI at scale in four testing and experimentation facilities and more than 25 workplaces across Europe (FSTP Projects). The ARISE project will address these challenges using cutting-edge open-source technologies from the European innovation ecosystem and will make a significant adavance on their state-of-the-art to position Europe globally at the forefront of industrial HRI. To that aim, the project will put the focus on the achievement of four major goals: (1) to increase the efficiency and cost-effectiveness of developing, deploying, and maintaining HRI solutions; (2) To develop open-source based reusabmodules which push industrial HRI beyond the SotA; (3) to demonstrate openness and agility as crucial enablers of truly valuable and sustainable HRI solutions; (4) to ensure impact a and sustainability through a critical mass of stakeholders & strong liaisons with ADRA ecosystem.

Manufacturing industry faces the challenges of driving competitiveness, resilience, sustainability and circularity in the context of a Volatile, Uncertain, Complex and Ambiguous environment. A VUCA world calls for new capabilities on the manufacturing systems demanding HUMANufacturing systems to evolve from industrial automation towards industrial autonomy. MaaS technologies still lack a solid foundation for more active resilience mechanisms that can respond with increased agility to more volatile and uncertainty scenarios. M4ESTRO envisions to create an end-to-end trustworthy and transparent platform for Manufacturing as a Service offering active and predictive resilience and timely preparedness to disruptive events. M4ESTRO will foster an interactive, collaborative, and dynamic ecosystem where these stakeholders will operate in a hyper-distributed way to manufacture products by providing and receiving services in a secure and trusted manner. It will offer response actions to foreseen risk based on the intrinsic network’s flexibility while offer preparedness to unforeseen risks based on the documented resilience to switch action plans To do so, M4ESTRO will focus on four (4) pillars, offering HW and SW components: Pillar 1: Resilient, transparent and flexible manufacturing processes in value chains. Pillar 2: Resilient equipment, AI and trusted data for adaptive manufacturing. Pillar 3: Resilient Simulations to the Industrial Metaverse for responsive manufacturing. Pillar 4: Human centred Manufacturing Resilience and Sustainability. The impact of M4ESTRO for the European Manufacturing industry, but also the society itself, can be summarised in the following (with a horizon of 4 years after project ends): (i) Process ramp-up time (>26%); (ii) OEE (>14%); (iii) Yield & CpK (>11% & >24%); (iv) Product cost reduction (>9%); (v) Cost per piece (>38%); (vi) Energy consumption (>26%); (vii) about 305 new jobs created and (viii) over 42.89 MEUR ROI for the consortium.

AI-DAPT brings forward a data-centric mentality in AI, that is effectively fused with a model-centric, science-guided approach, across the complete lifecycle of AI-Ops, by introducing end-to-end automation and AI-based systematic methods to support the design, the execution, the observability and the lifecycle management of robust, intelligent and scalable data-AI pipelines that continuously learn and adapt based on their context. AI-DAPT will design a novel AI-Ops / intelligent pipeline lifecycle framework cross-cutting the different business, legal/ethics, data, AI logic/models, and system requirements while always ensuring a human-in-the-loop (HITL) approach across five axis: “Data Design for AI”, “Data Nurturning for AI”, “Data Generation for AI”, “Model Delivery for AI”, “Data-Model Optimization for AI”. AI-DAPT will contribute to the current research and advance the state-of-the-art techniques and technologies across a number of research paths, including sophisticated Explainable AI (XAI)-driven data operations from purposing, harvesting/mining, exploration, documentation and valuation to interoperability, annotation, cleaning, augmentation and bias detection; collaborative feature engineering minimizing the data where appropriate; adaptive AI for model retraining purposes. Overall, AI-DAPT aims at reinstating the pure data-related work in its rightful place in AI and at reinforcing the generalizability, reliability, trustworthiness and fairness of Al solutions. In order to demonstrate the actual innovation and added value that can be derived through the AI-DAPT scientific advancements, the AI-DAPT results will be validated in two, interlinked axes: I. Through their actual application to address real-life problems in four (4) representative industries: Health, Robotics, Energy, and Manufacturing; II. Through their integration in different AI solutions, either open source or commercial, that are currently available in the market.

QU4LITY will demonstrate, in a realistic, measurable, and replicable way an open, certifiable and highly standardised, SME-friendly and transformative shared data-driven ZDM product and service model for Factory 4.0 through 5 strategic ZDM plug & control lighthouse equipment pilots and 9 production lighthouse facility pilots. QU4LITY will also demonstrate how European industry can build unique and highly tailored ZDM strategies and competitive advantages (significantly increase operational efficiency, scrap reduction, prescriptive quality management, energy efficiency, defect propagation avoidance and improved smart product customer experience, and foster new digital business models; e.g. outcome-based and product servitisation) through an orchestrated open platforms ecosystem, ZDM atomized components and digital enablers (Industry 4.0 digital connectivity & edge computing package, plug & control autonomous manufacturing equipment, real-time data spaces for process monitoring & adaptation, simulation data spaces for digital process twin continuity, AI-powered analytic data spaces for cognitive digital control twin composable services, augmented worker interventions, European quality data marketplace) across all phases of product and process lifecycle (engineering, planning, operation and production) building upon the QU4LITY autonomous quality model to meet the Industry 4.0 ZDM challenges (cost and time effective brownfield ZDM deployment, flexible ZDM strategy design & adaptation, agile operation of zero defect processes & products, zero break down sustainable manufacturing process operation and human centred manufacturing).