BACKGROUNDRapid technological change means we face a very real digital competence gap in the coming years—a period in which technological capabilities accelerate so swiftly that talent and knowledge can’t keep up. The competence gap will create friction, slowing realization of the benefits of digital transformation. Almost all EU countries are introducing schemes, offers, services aimed at reducing the competence gap but despite the EU goal of creating a common Digital Single Market, most of them are not connected, don’t know each other or have never thought about establishing any kind of cooperation scheme.OBJECTIVEThe DITA project wants to strengthen transnational cooperation among synergic training organizations and increase the mobility opportunities of trainees in the European digital industry scene by a) providing a transparent and useful overview of available training opportunities in the field of Digital Transformation, b) supporting trainees in identifying which available training opportunities may best fit to their needs and expectations, c) establishing permanent cooperation schemes among the identified training, programs and facilities, d) delivering and permanently maintaining an open but supervised tool (The Digital Industry Training Atlas) that will collect, connect and display synergic available training opportunities in Europe on digital transformation.TARGET GROUPSThe project has 2 main target groups: 1) it responds to the needs of todays and tomorrows professionals or graduates working for (or being potential candidates to work for) European small and medium sized enterprises, specifically the project addresses the needs of current or future managers and staff of almost all operational departments of a typical European SME; 2) vocational training organizations that would highly benefit from connecting to complementary organizations in their country as well as in other countries.The project will involve at least 100 end users (learners) during the teat phase and 160 during multiplier events plus 110 training organizations.NEEDS ADDRESSEDUnder this perspective the project allows a) learners to 1) have full and transparent access to available training paths in the field of digital transformation; 2) be facilitated and supported in identifying and choosing the most appropriate training path that would increase their competences and skills in the field of digital transformation;b) training organizations to increase the quality of their training offer by establishing international formal connections with complementary training organizations.EXPECTED RESULTSThe project’s expected results are to increase: 1) the general awareness level of the current and future European workforce about available training opportunities in the field of Digital Transformation; 2) the understanding of potential synergies among the identified training opportunities in the field of Digital Transformation; 3) learners’ mobility throughout Europe to benefit from the different and complementary offer of training programs in the field of Digital Transformation; 4) the internationalization strategies of life-long learning training organizations in the field of Digital Transformation.INTELLECTUAL OUTPUTS7 synergic and complementary project partners from 6 EU countries (IT, AT, DE, BE, PT and ES) representing the most relevant running European Industry 4.0 initiatives will cooperate to achieve these results by delivering 4 synergic IOs, namely 1) Digital Transformation & Competences in Europe: Available Training Facilities & Approaches; 2) Digital Transformation & Competences in Europe: Industry Relevant Training Case Studies and ideal synergies; 3) The Interactive EU Map of Digital Transformation Training Providers; 4) Cooperation Framework for a common Digital Transformation Training Arena.LONG TERM BENEFITAt the end of the project an interactive EU Map of available training options and their potential interconnections will be available for European exploitation via the Training Atlas. A long-term action plan, describing strategy and concrete action lines until the end of 2024, and concrete synergies with EU digitalization-oriented initiatives will guarantee its availability after the end of the project. European Learners and Training Organizations will benefit from it as well as all those programs and action lines foreseen and anchored to the Digital Single Market initiative..

Operation & Maintenance (O&M) costs are the main cost driver in offshore energy due to the difficult accessibility to the WTs, but also due to the environmental conditions. O&M costs can account for up to 30% of the levelised cost of energy (LCOE) and sensing & monitoring systems could help attain the expected fall to 70 EUR/MWh by 2030. The highest criticality (in €/kWh) in offshore wind is caused by structural failure, that mainly occurs due to corrosion processes non-adequately neither predicted nor monitored. For that reason, it is crucial to implement new monitoring, diagnosis, prognosis and control tools into the offshore wind farms (WFs) to enable Wind Farm Operators (WFOs) to take predictive smart O&M decisions fully considering structural components real and future status. WATEREYE aims to develop an integral solution that will allow to WFOs a 4% reduction of OPEX, accurately predicting the need for future maintenance strategy and increasing the offshore wind annual energy production. To this end, WATEREYE will: 1/ develop a monitoring system capable of remotely estimating the corrosion level in exact WT locations (tower, splash-zone, tower-platform junction) as a supporting tool for predictive maintenance to considerably reduce the O&M costs and reduce the risk for operation failures; New Ultrasound corrosion sensors (ad-hoc, low-cost, high accuracy, fast-response, non-invasive) will be developed, as well as high efficient and robust wireless communications specifically conceived for offshore WTs hard communicating environment. Besides, a novel drone-based mobile platform to move one mobile sensor inside the WT tower will be developed. 2/ develop enhanced prediction models by analysing the acquired data in novel ways (semantic models); 3/ develop WT & WF control algorithms with accurate consideration of the structural health, giving operators freedom to choose the best balance between energy production, protective control, and predictive maintenance.

The past years have shown the vulnerability of rigid international supply chains. The ability to adapt to changes and create resilient supply chains will be a key competitive advantage for manufacturers in the future. RAASCEMAN tackles three different possibilities to react to unforeseen events: adapting the production plan based on supply chain data adapting the supply chain by switching the supplier using a MaaS network integrating remanufacturing as procurement alternative leveraging circularity. The project aims to enable companies to mitigate short- and medium-term unforeseen events and to enable companies to participate in a dynamic MaaS-network lowering the market barriers for companies specialized in remanufacturing or alternative technologies such as 3D printing. RAASCEMAN designs and demonstrates a series of software tools digitizing supply chains by using digital twins and an infrastructure for data-exchange based on European values. RAASCEMAN will develop its overall ambition by the means of five scientific objectives namely: Actionable propositions for adapting supply chains or internal production and logistics based on reliable quantification and impact prediction of unforeseen events Dynamic supply chain generation enabling resilience and self-adaptation of MaaS networks, Building Trust in MaaS networks auditing suppliers’ reliability and testing plausibility of offers Dynamic planning and scheduling of production processes enabling companies to swiftly adapt logistics and production to varying external conditions and Dynamic assembly and disassembly to enable machines in the field level We demonstrate our solutions in two industrial use-cases of the automotive and bike industry and create a MaaS network connecting five pilot lines distributed over Europe. The majority of project results will be made available under appropriate open-source licensing schemes to allow further maturation in integration after the RAASCEMAN project concludes.

The main target of the ITEAM project is to establish and sustainably maintain the European training network with high grade of interdisciplinarity, which will train strong specialists skilled in research and development of novel technologies in the field of multi-actuated ground vehicles (MAGV). The global goals are: (i) Advance of European postgraduate education in the area of environment- and user-friendly vehicle technologies that highly demanded by the European industry and society; (ii) Reinforcement of cooperation between academia and industry to improve career perspectives of talented graduates in both public and private sectors; (iii) Creation of strong European research and innovation group making determinant contributions to next generations of multi-actuated ground vehicles. To achieve the project objectives, the consortium unites 11 beneficiaries and 5 partner organizations from 9 European countries including 7 universities, 2 research centres, and 7 non-academic organizations. Distinctive feature of the ITEAM network is the concept of interaction of three research clusters: "MAGV integration", "Green MAGV", "MAGV Driving Environment". Within these clusters, the training concept will be based on intersectoral cooperation and will cover domains of (i) basic research, (ii) applied research, and (iii) experimentations. The ITEAM project will provide the first-of-its kind European training network in Ground Vehicles at doctorate level to fill up the niche in private sector and industry with researcher-practitioners. The proposed network will be developed as innovative, multidisciplinary, engineering product-oriented and project-based program to train the scientists by integrating cutting-edge research methods of ground vehicles, electric/mechatronic systems, environmental engineering and applied intelligent control. The ITEAM network measures will guarantee excellent career prospects for participating researchers both in industrial and academic sectors.

During the last years, EU manufacturing has faced production flexibility challenges by deploying, among others, novel hybrid manufacturing systems, involving collaborative robots and mobile manipulators combined with flexible grippers, vision systems, sophisticated tasks/actions planning solutions and flexible integration platforms. Despite the importance of AI enabled flexible robotic systems, several aspects settle back their wider adoption, and impact on the objectives of the green deal: •Limited cognition/ intelligence: existing solutions support non-trivial tasks but cannot act autonomously. •Insufficient perception and diagnostics: In a circular economy, there is an increased need for understanding the state of products or parts that are being handled, after they have been used. •Decision making is restricted: Current decision-making focuses on process or line level, not taking into account optimization at value chain level or per individual product. •Small scale adaptation of AI due to small number of available data and training needed, to support tailored solutions in high variability context. •Lack of use of explicitized knowledge in AI and robotics. Lifecycle data and knowledge is not used across the value chain to improve decision making after a product’s first life. •Complexity in robot programming and interaction which requires the involvement of skilled engineers, does not provide flexibility in execution, Thus, ROB4GREEN aims to develop easy to use and deploy AI driven collaborative robotic systems, that can reason and adapt to a variety of strategies for processing products after their first life, both hardware and behavior wise, improving existing skills and generating new ones, working autonomously combining data and knowledge. Such systems will be validated at scale and in major industries, showcasing optimization ranging from cell to the whole value chain, towards achieving significant impact on the objectives of the green deal.