The main objectives of this project are to develop a model-based prognostics method integrating the FMECA and PRM approaches for the smart prediction of equipment condition, a novel MDSS tool for smart industries maintenance strategy determination and resource management integrating ERP support, and the introduction of an MSP tool to share information between involved personnel. The proposers' approach is able to improve overall business effectiveness with respect to the following perspectives: • Increasing Availability and then Overall Equipment Effectiveness through increasing of MTBF, and reduction of MTTR and MDT. • Continuously monitoring the criticality of system components by performing/updating the FMECA analysis at first implementation or whenever a variation in the system design or composition occurs. • Building physical-based models of the components which have a higher criticality level or which status is difficult to monitor. • Determining an optimal strategy for the maintenance activities. • Creating a new schedule for the production activities that will optimize the overall system performance through a Smart Scheduling tool ensuring collaboration among the MDSS, the ERP and the RUL Estimation tool. • Providing, in addition to traditional data acquisition and management functions in a machine condition monitoring system, robust and customizable data analysis services by a cloud-based platform. • An Intra Factory Information Service will be developed to allow the company staff to be quickly informed of changes in the machine tool performances and to easily react to eventual production and maintenance activities rescheduling. The production and maintenance schedule of complete production lines and entire plants will run with real-time flexibility in order to perform at the required level of efficiency, optimize resources and plan repair interventions.

Cheaper and more powerful sensors, together with big data analytics, offer an unprecedented opportunity to track machine-tool performance and health condition. However, manufacturers only spend 15% of their total maintenance costs on predictive (vs reactive or preventative) maintenance. The project will deploy and test a predictive cognitive maintenance decision-support system able to identify and localize damage, assess damage severity, predict damage evolution, assess remaining asset life, reduce the probability of false alarms, provide more accurate failure detection, issue notices to conduct preventive maintenance actions and ultimately increase in-service efficiency of machines by at least 10%. The platform includes 4 modules: 1) a data acquisition module leveraging external sensors as well as sensors directly embedded in the machine tool components, 2) an artificial intelligence module combining physical models, statistical models and machine-learning algorithms able to track individual health condition and supporting a large range of assets and dynamic operating conditions, 3) a secure integration module connecting the platform to production planning and maintenance systems via a private cloud and providing additional safety, self-healing and self-learning capabilities and 4) a human interface module including production dashboards and augmented reality interfaces for facilitating maintenance tasks. The consortium includes 3 end-user factories, 3 machine-tool suppliers, 1 leading component supplier, 4 innovative SMEs, 3 research organizations and 3 academic institutions. Together, we will validate the platform in a broad spectrum of real-life industrial scenarios (low volume, high volume and continuous manufacturing). We will also demonstrate the direct impact of the platform on maintainability, availability, work safety and costs in order to document the results in detailed business cases for widespread industry dissemination and exploitation.

AIMS5.0, a collaborative Innovation Action aims at strengthening European digital sovereignty in comprehensively sustainable production, by adopting, extending and implementing AI-enabled hardware and software components and systems across the whole industrial value chain to further increase the overall efficiency. Vulnerability of existing supply chains in crisis shows the need for shorter supply chains and for keeping production in Europe. AI enabled fabs will be given more output and higher sustainability, which makes them more competitive on a global scale. New technologies from IoT and based on semantic web ontologies, ML and AI will help to enable the transformation from Industry4.0 to Industry5.0, to create human-centric workplace conditions and to enable the transformation of European industry to climate-friendly production. Above all, sustainability and resilience will be improved. In essence, AIMS5.0 will deliver: - AI-enabled electronic hardware components & systems for sustainable production - AI tools, methods & algorithms for sustainable industrial processes - SoS-based architectures & micro-services for AI-supported sustainable production - Semantic modelling & data integration for an open access productive sustainability platform - Acceptance, trust & ethics for explainable industrial AI leading to human-centered sustainable manufacturing 20 use cases in 9 industrial domains resulting in high TRLs will validate the project’s findings in an interdisciplinary manner. A professional dissemination, communication, exploitation and standardisation will ensure the highest impact possible. For the first time a joint approach for implementing AI and AI-enabled hardware will be developed that overarches different industrial domains. AIMS5.0 will result in lower manufacturing costs, increased product quality through AI-enabled innovation, decreased time-to-market and increased user acceptance of versatile technology offerings. They will foster a sustainable development, in an economical, ecological and societal sense and act as enablers for the Green Deal and push the industry towards Industry5.0. The innovations will leverage the experience of the 53 partners, such as renowned OEMs, Tier-1 and Tier-2 suppliers, technology and application large enterprises and SMEs, supported by academic research specialists in fields like AI, industrial hard-ware and software, decision making and management algorithms. Specific outcomes of the project are - 20% faster time to market, - Participation of disabled people in the factory environment > 5% (in relation to the total number of employees employed in production), - AI based MES capability > 10 %, - Increased user awareness and trust by 10%, - Subsequent reduction of environmental footprint for wafer transport, handling and storage > 20 %, - 50% reduction of time for monitoring industrial equipment. AIMS5.0 is a pan-European initiative to boost industrial competitiveness through interdisciplinary innovations, establishing sustainable ECS value chains and therefore contribute to European Digital Sovereignty addressing urgent issues like Security of Supply, Monitoring and Crisis Response, and Chip Shortage.

PRODUCTIVE4.0 - AMBITIOUS PROJECT WITH A UNIQUE MAIN OBJECTIVE The main objective of Productive4.0 is to achieve improvement of digitising the European industry by electronics and ICT. Ultimately, the project aims at suitability for everyday application across all industrial sectors – up to TRL8. It addresses various industrial domains with one single approach of digitalisation. What makes the project unique is the holistic system approach of consistently focusing on the three main pillars: digital automation, supply chain networks and product lifecycle management, all of which interact and influence each other. This is part of the new concept of introducing seamless automation and network solutions as well as enhancing the transparency of data, their consistence and overall efficiency. Currently, such a complex project can only be realised in ECSEL. The consortium consists of 45% AENEAS, 30% ARTEMIS-IA, 25% EPOSS partners, thus bringing together all ECSEL communities. Representing over 100 partners from 19 EU and other associated countries, it is a European project, indeed. HANDS-ON SOLUTIONS FOR THE EUROPEAN DIGITAL INDUSTRY • Productive4.0 tackles technological and conceptual approaches in the field of Industry 4.0. The term comprises IIoT (Industrial Internet of Things), CPS (Cyber Physical Systems) and Automation. • The innovation project takes a step further towards hands-on solutions. In the process, practical reference implementations such as 3D printerfarms, customised production or self-learning robot systems will benefit in fields like service-oriented architecture (SOA), IOT components & infrastructures, process virtualisation or standardisation. These fields are addressed in the work packages WP1 through WP6. • In addition to furnishing the industry with tailor-made digital solutions, the Productive4.0 Framework will be provided. • Productive4.0 is a brain pool initiated to strengthen the international leadership of the European industry.

Manufacturing industries continuously face the challenge of delivering high-quality products under high production rates while minimizing non value-adding activities. The recent COVID-19 pandemic is causing manufacturers to rethink and reassess their global supply chains and the flexibility of their production sites. Resilience means the ability to withstand difficult situations, while flexibility can be considered as the ability to accommodate changes without incurring significant extra costs. Production processes demanding high human skill such as forming processes, requires readjustment of the process parameters of all production steps as a new product evolves. The deficiencies can be attributed largely to the lack of efficient ways for trusted data sharing among the stakeholders without interoperability barriers. There is a need to be able to determine when such changes lead to deterministic-chaotic behavior with far reaching consequences. FLEX4RES provides an open platform to support production networks' reconfiguration for resilient manufacturing value chains. FLEX4RES will utilize platform-based manufacturing that builds on the state-of-the-art Gaia-X and IDS technologies for data-sharing in the horizontal supply chain and the Asset Administration Shell (AAS) that is to implement intra-factory reconfiguration practices. FLEX4RES considers the Digital Twin of the value-adding network a key enabling technology to achieve reconfiguration processes in highly flexible production systems and networks. The key element of technology linkage is represented by the Self-Descriptions with linked, standardized information models, especially in terms of resilience. The developed platform and specialized hardware aim to improve the existing industry-established lean management approaches related to Reconfiguration Management through the digitalization of the production, characterized as Industry4.0, by allowing for the information sharing between value chain stakeholders.