Briefing on EU Projects

Aug 15, 2019 | News

IDS leaves a footprint in European research – these projects are important pillars in order to bring IDS to life, to develop fundamental concepts, to test first proofs of concepts and to stimulate adoption and proliferation of IDS concepts.

AMable (Additive ManufacturABLE) 

Enabling adoption of additive manufacturing (AM) technologies by SMEs in order to facilitate the development of innovative business and service models, and new value chain models, in a fully digital environment.

Overall Goal: Bringing innovative ideas and business cases to life and making innovations additively manufacturable (AMable).

BOOST 4.0 – Big Data for Factories

Boost 4.0 is the biggest European initiative in big data for Industry 4.0. With a budget of 20 million euros, and leveraging 100 million euros of private investments, Boost 4.0 will lead the proliferation of the European Industrial Data Space to improve Europe’s competitiveness regarding Industry 4.0. Furthermore, the project will guide the European manufacturing industry in leveraging big data for factory processes.

Overall Goal: Providing the manufacturing industry with the necessary tools to exploit the full benefit of big data.

AI4EU (Artificial Intelligence for the EU)

AI4EU is the European Union’s landmark artificial intelligence project, which seeks to develop a European AI ecosystem bringing together the necessary knowledge, algorithms, tools, and resources, making it a compelling solution for users

Overall Goal: Mobilizing the entire European AI community to make AI’s promises real for European societies and economies and creating a leading collaborative European AI platform to nurture economic growth.

QU4LITY (Digital Manufacturing Platforms for Connected Smart Factories)

QU4LITY demonstrates – in a realistic, measurable, and replicable way – an open, certifiable, highly standardized, SME-friendly, transformative, shared, data-driven product and service model for zero-defect manufacturing (ZDM) for Factory 4.0 scenarios, and it does so by means of five strategic ZDM plug&control lighthouse equipment pilots and nine production lighthouse facility pilots.

Overall Goal: Demonstrating how the European manufacturing industry can build unique and tailor-made ZDM strategies and competitive advantages through an orchestrated open-platform ecosystem, ZDM-atomized components, and digital enablers across all phases of product and process lifecycles, building upon the QU4LITY autonomous quality model to meet Industry 4.0 ZDM challenges.

DIH² (Digital Innovation Hubs)

DIH² is a network of twenty-six DIHs aiming at supporting SMEs in agile production (i.e. 50 % increase in productivity) and unleashing their digitalization potential by enabling robot solutions that are more cost-effective at smaller lot sizes. DIH² will transform this network into a self-sustainable non-profit association with members all over Europe (the goal is to include over 170 DIHs). DIH² will demonstrate that publicly funded research can help SMEs and mid-caps achieve digital excellence and global competitiveness by adopting advanced robotics solutions in agile production.

Overall Goal: Sparking incremental (cut 50 % of cost of advanced robotics solutions, double the growth of robotics market) and disruptive (maximum productivity and optimum agility) innovations in over 300,000 manufacturing SMEs and midcaps.


Musketeer – Machine Learning to Augment Shared Knowledge in Federated Privacy Preserving Scenarios

The massive increase in data collected and stored worldwide calls for new ways to preserve data privacy while still allowing data sharing among multiple data owners. Data can continue to be stored in different locations with different privacy constraints, but data sharing needs to be secure. The MUSKETEER crossdomain platform will validate progress in the industrial scenarios of smart manufacturing and healthcare. MUSKETEER strives to create machine learning models over a variety of privacy-preserving scenarios, ensure security and robustness against external and internal threats, provide a standardized and extendable architecture, demonstrate and validate the solutions in two different industrial scenarios, and enhance the data economy by boosting data sharing across domains.

Overall Goal: Creating a validated, federated, privacy-preserving machine learning platform to be tested on industrial data that is interoperable, scalable and efficient enough to be deployed in real use cases. Alleviating data-sharing barriers by providing secure, scalable and privacy-preserving analytics over decentralized datasets using machine learning.

MARKET 4.0 – A Multi-Sided Business Platform for Plug and Produce Industrial Product Service Systems

MARKET4.0 will offer advanced web presence of production equipment SMEs extended with additional functionalities, such as simulations or VR/AR capabilities. It will also be a P2P Industrial Data Space that offers smart user services, a secure API to try and test the digital twin of the production equipment, on top supplier and customer data that enable direct transaction between market peers (supplier-to-supplier, supplier-to-customer, customer-to-supplier and more) during the whole B2B process from equipment search to procurement and commissioning. MARKET4.0 will create trust in the busiCONNECT & PRODUCE ness transaction between the SME production equipment manufacturer and the customer, as indicated in in the IDS reference architecture.

Overall Goal: Defining, developing, and validating an open, multi-sided marketplace, based on a trusted P2P data sharing infrastructure for Industry 4.0, which brings together Industrial Product Service Systems (IPSS) providers (supply side) and customers (demand side), and which allows direct interaction among the different sides in order to improve the sales power of production equipment SMEs.

MIDIH (Manufacturing Industry Digital Innovation Hubs)

MIDIH is a one-stop shop of services granting manufacturing SMEs access to the most advanced digital solutions, the most advanced industrial experiments, pools of human and industrial competencies, the “ICT for Manufacturing” market, and financial opportunities.

Overall Goal: Leveraging networks of local Competence Centers specialized in peculiar aspects of the CPPS/IIOT (Cyber Physical Production System / Industrial Internet of Things) technologies and able to attract, mentor and nurture local manufacturing SMEs towards Industry 4.0 projects, experiments, and business. Establishing a common platform of knowledge, methods, and collaboration tools to be shared among the members of the MIDIH network, allowing cross-fertilization, continuous improvement, and open innovation.

OPEN DEI – Aligning Reference Architectures, Open Platforms and Large Scale Pilots in Digitizing European Industry

In the Horizon 2020 funding programme, the European Commission’s “Platforms and Pilots” section aims to implement digital platforms in the four basic areas of manufacturing, agriculture, energy and healthcare. OPEN DEI is located in this context: OPEN DEI aims to leverage synergies, identify gaps, share best practices, reinforce regional and national relationships and take joint actions to disseminate, communicate, train and exploit the digtial innovations, thus implementing the EU Digital Transformation Strategy.

Overall Goal: 

  1. Platform Building: a reference architecture, a set of open source reference implementations and an Industrial Data Platform
  2. Large Scale Piloting: a digital maturity model, a set of assessment methods and a migration journey benchmarking tool
  3. Ecosystem Building: an Innovation and Collaboration Platform, a pan-EU network of Industrial DIHs, an Industrial Skills catalogue and observatory;
  4. Standardization: a cross-domain survey, a promotion and implementation plan and a strategic alliance with existing EU and International SDOs.

LEVEL UP – Protocols and strategies for extending the useful life of major capital investments and large industrial equipment

Europe is still lacking an efficient systemic multi-level approach that enables a recursive, cost-effective, holistic and integrated application of circular principles to the digital uplifting of factory 4.0 capital investments; addressing issues at product, process, system as well as the entire value-chain levels, integrating best practices from emerging enabling digital technologies and avoid a two speed digital transformation across industries in different sectors. LEVEL-UP will offer a scalable platform covering the overall lifecycle, ranging from the digital twins setup, modernisation actions to diagnose and predict the operation of physical assets, to the refurbishment and remanufacturing activities towards end of life. In-situ repair technologies and the redesign for new upgraded components will be facilitated through virtual simulations for increased performance and lifetime. LEVEL-UP will therefore comprise new hardware and software components interfaced with the current facilities through IoT and data-management platforms, while being orchestrated through eight (8) scalable strategies at component, work-station and shopfloor level. The actions for modernising, upgrading, refurbishing, remanufacturing, and recycling will be structured and formalised into ten (10) special Protocols, linked with an Industrial Digital Thread weaving a seamless digital integration with all actors in the value chain for improved future iterations. LEVEL-UP will be demonstrated in 7 demo sites from different sectors. The impact of LEVEL-UP to the European manufacturing industry, but also the society itself, can be sum-marised in the following (with a horizon of 4 years after project ends): (i) increase of the material and resource efficiency by 11.5%, (ii) increased reliability by 16% of the equipment in an extended lifetime by 20%, (iii) over 50% increase of the Return on Investment (ROI), (iv) about 810 new jobs created and (v) over 80M EUR ROI for the consortium.

These projects have received funding from the European Union‘s Horizon 2020 research and innovation program under grant agreements Nº825619, Nº768775, Nº780732, Nº824964, Nº825030, Nº822064, Nº767498 and Nº824988.

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