The use of fossil fuels and emission of greenhouse gases (GHG) from waterborne must be minimised as fast as possible to reach a climate-neutral society by 2050. A vital prerequisite of the decarbonisation is the rapid growth of low-carbon power sources and energy storage. To achieve this, the efficient integration in the shipboard power system requires the development of high-power components and protections, and more specifically DC-DC power converters and DC switchgear. Albeit DC primary grids have been deployed for several vessels, the secondary grid has remained substantially identical to traditional solution based on AC. There is an opportunity to unlock the capabilities and functionalities of novel components for secondary grids that can improve the safety and the operations on the vessel. These components, integrated with the power converters and the protections of the primary grids, will reduce the risks of blackouts connected to faults and improve the reliability of the power supply. ALL-DC-SHIPS has devised a comprehensive strategy to address the challenges faced by shipowners, systems integrators and ship operators that includes: 1) development of new modular power converters with wide bandgap devices for primary DC grids 2) high-density power converters for secondary DC grids 3) innovative DC protection systems for primary and secondary DC grids 4) implementation of advanced algorithms for real-time ship energy management 5) rigorous testing and validation methodologies for the vessel demonstrator 6) providing recommendations for relevant use cases above 5,000 GT. ALL-DC-SHIPS will contribute to enable low-emission waterborne transport and technology transition for a resilient and sustainable future of the maritime sector.

The main objective of the iDev40 project proposal is to achieve a disruptive or “breakthrough change” step toward speedup in time to market by digitalising the European industry, closely interlinking development processes, logistics and manufacturing. Ultimately, the project aims at suitable digital technology advancements to strengthen the electronic components and systems industry in Europe. It addresses various industrial domains with one and the same approach of digitalisation towards competitive and innovative solutions. The new concept of introducing seamlessly integrated development together with automation and network solutions as well as enhancing the transparency of data, their consistence, flexibility and overall efficiency will lead to a significant speedup in the time to market (T2M) race. iDev40’s unique approach addresses: • AI learning, Data Life Cycle Management and IP Protection • Embedding Digital Development in Digital Production (the digital twin) • Close the Knowledge loop in product life cycle management along the supply chain • Collaboration 4.0 and Development of highly skilled R&D and Manufacturing Teams • Prove the innovated technologies on selected use cases in real productive environment Progress in mastering these challenges will significantly impact the productivity of future design processes embedded in an Industrial Internet environment. The global state-of-art technologies already offer tremendous diagnostics algorithms, machine controls, simulators, optimizers, etc., but only an extensive framework like iDev40 can combine them into effective integration into the development process enabling such powerful simulations like “digital twins” that ever more govern the hardware, manufacturing service and business functions. To cope with the exceptional complexity it becomes even more crucial to be competitive leaders in developing virtual representations of real physical implementation.

ALL2GaN will be the backbone for the European Power Electronics Industry by offering an EU-born smart GaN Integration Toolbox. The project will provide the base for applications with significantly increased material- and energy efficiency, thus meeting the global energy needs while keeping the CO2 footprint to the minimum. 46 partners from 12 European countries will collaborate on 8 major objectives along the entire vertical value chain of power and RF electronics. O1: Push the limits of industrial GaN devices and system-on-chip approaches for ≤ 100V O2: Leverage the full potential of innovative substrates for GaN O3: Achieve novel benchmark solutions for lateral GaN devices and integrated circuits ≥ 650V O4: Reach best technical and cost performance of RF GaN on Si with novel integration concepts O5: Break the packaging limits by application driven integrated solutions of high performance GaN products O6: Advance the methods to evaluate and optimize reliability and robustness of GaN components, modules, and systems for shortest time-to-market and maximum product availability at the end user O7: Demonstrate highest affordable performance for greener power electronics and RF applications O8: Road-mapping for the future GaN technology development and applications to support long-term exploitation/business cases and European leadership beyond ALL2GaN. The collaboration in ALL2GaN is based on a work package structure covering activities on novel power- and RF-GaN technologies for various voltage classes, latest packaging technologies, research on reliability and demonstration in 11 Use Cases. With ambitious goals and a clear vision, ALL2GaN will unleash the energy saving and material efficiency potential of GaN semiconductors for a broad field of applications, thus being in line with the major challenges outlined in the ECS-SRIA. ALL2GaN technology will directly contribute to energy saving and cutting-edge green technology innovation as…Every Watt counts!

Intelligent Reliability 4.0 (iRel40) has the ultimate goal of improving reliability for electronic components and systems by reducing failure rates along the entire value chain. Trend for system integration, especially for heterogeneous integration, is miniaturization. Thus, reliability becomes an increasing challenge on device and system level and faces exceptional requirements for future complex applications. Applications require customer acceptance and satisfaction at acceptable cost. Reliability must be guaranteed when using systems in new and critical environments. In iRel40, 79 partners from 14 countries collaborate in 6 technical work packages along the value chain. WP1 focuses on specifications and requirements. WP2 and WP3 focus on modelling, simulation, materials and interfaces based on test vehicles. WP4 applies the test vehicle knowledge to industrial pilots related to production. WP5 applies the knowledge to testing. WP6 focuses on application use cases applying the industrial pilots. We assess and validate the iRel40 results. Reliable electronic components and systems are developed faster and new processes are transferred to production with higher speed. Crucial insight gained by Physics of Failure and AI methods will push overall quality levels and reliability. iRel40 results will strengthen production along the value chain and support sustainable success of Electronic Components and Systems investment in Europe. By collaboration between academy, industry and knowledge institutes on this challenging topic of reliability, the project secures more than 25.000 jobs in the 25 participating production and testing sites in Europe. The project supports new applications and reliable chips push applications in energy efficiency, e-mobility, autonomous driving and IoT. This unique project brings, for the first time ever, world-leading reliability experts and European manufacturing expertise together to generate a sustainable pan-European reliability community.

Modern data-driven applications leverage large, heterogeneous data collections to find interesting patterns, and build robust machine learning (ML) models for accurate predictions. Large data sizes and advanced analytics spurred the development and adoption of data-parallel computation frameworks like Apache Spark or Flink as well as distributed ML systems like MLlib, TensorFlow, or PyTorch. A key observation is that these new systems share many techniques with traditional high-performance computing (HPC), and the architecture of underlying HW clusters converges. Yet, the programming paradigms, cluster resource management, as well as data formats and representations differ substantially across data management, HPC, and ML software stacks. There is a trend though, toward complex data analysis pipelines that combine these different systems. Examples are workflows of distributed data pre-processing, tuned HPC libraries, and dedicated ML systems, but also HPC applications that leverage ML models for more cost-eff