In nearly every sector of industrial manufacturing surface processing techniques are used, e.g. for structuring or polishing of aesthetical or functional surfaces. In many applications laser based surface processing techniques already achieve highest precision and quality. But often the throughput is limited. State of the art for many applications in laser surface processing is the utilization of one round laser beam. The idea of ultraSURFACE is to increase the throughput for laser surface processing by at least a factor of 10 without any drawbacks in the quality of the processing results. Therefore, two different optics concepts will be realised and combined with a fast and synchronized machine, scanner and optics control. Optics Concept 1 refers to a dynamic and flexible beam-shaping approach with piezo-deformable mirrors which enables the realisation and the fast adaption of application specific intensity distributions. This will allow significant increase in feed speed and track offset and therefore of throughput. Optics Concept 2 is a beam splitting approach which allows simultaneous processing with multiple laser beams and thus a significant increase of throughput. For both concepts the implementation of prototypes is planned as well as their industrial validation in different fields of application (laser structuring, laser polishing, laser thin-film processing). The main ultraSURFACE Objectives are uSO1 Dynamic and flexible beam-shaping optics for laser surface processing uSO2 Multi-beam optics for parallel laser surface processing uSO3 Ultrafast synchronisation of optics and machine for 3D processing uSO4 Validation in industrial scenarios

HERAQCLES stands for New Manufacturing Approaches for Hydrogen Electrolysers To Provide Reliable AEM Technology Based Solutions While Achieving Quality, Circularity, Low LCOH, High Efficiency And Scalability. Project HERAQCLES delivers an operational 25kW electrolyser stack including balance-of-plant based on AEM technology to validate both our novel design-for-manufacturing architecture and innovative components developed for automated production processes. AEM electrolysis offers a more attractive cost/performance ratio compared to state-of-art PEM electrolysis because these is no need to utilise precious group metals in stack components like catalysts, porous transport layers and bipolar plates for generating hydrogen at reasonably high current density. Current stack manufacturing processes face bottlenecks limited by many separate components, manual assembly and lack of tooling due to low production numbers. The project focusses on increasing Manufacturing Readiness Level from 4 to 5 by collectively advancing all components to comply with automated manufacturing processes at industrial scale: forming of metal plates, 3D-screen printing porous layers, pilot-scale synthesis of membrane polymers and catalyst. Validation occurs in three yearly loops using single cell, short stack and full 25kW stack configurations, where test results are benchmarked against commercially available options to highlight critical improvements of composition, functionality and recyclability. The experienced consortium brings together a unique combination of know-hows acquired in previous projects (e.g. Anione) and manufacturing capabilities provided by strong representation from industrial partners (6 out of 8). If successful, the final qualified stack prototype can be scaled-up quickly. Finally, a business plan is established comprising of a technology roadmap, an analysis of premium applications, an overview of product-market combinations and feasible market development plans.

The success of the European rail system to foster the modal shift towards rail requires cost-efficient and reliable long-lasting trains. GEARBODIES contributes to this effort by improving the efficiency of rolling stock maintenance in close collaboration with the ongoing CFM-IP1-01-2019 (PIVOT2). To achieve the above, GEARBODIES follows a twofold approach: extending overhaul periods and improving maintenance processes. The extension of overhaul periods will be facilitated by developing high-performance and long-lifetime components for running gear. The improvement of maintenance processes will be boosted by developing innovative NDT technologies to optimise inspection processes for lightweight carbody shells. GEARBODIES will design and prototype several elastomer-metal running gear components, suitable for serial production, based on high-performance new elastomer formulations and existing elastomers not yet applied in rolling stock elements. In addition, the project will also explore innovative technologies for the development of low LCC bearings. New lubrication solutions, new materials for races and rollers, novel polymers for cages and the effects of new bearing geometries will be researched, among which the most feasible ones will be integrated in a new bearing design and prototyped. GEARBODIES will develop an innovative modular platform to reduce the inspection time of lightweight carbody shells. The platform will incorporate tailored thermography and ultrasonic inspection systems and will facilitate the automated detection and assessment of defects throughout the thickness of the shell by using a customed software module. GEARBODIES will benefit form a strong multidisciplinary consortium, made of 13 partners from 8 countries, committed to the mentioned actions towards maximisation of the project's impact.

It is the high ambition of the project to create “FACTorieS for WORKERS” (FACTS4WORKERS), therefore a serious effort will be put into integrating already available IT enablers into a seamless & flexible Smart Factory infrastructure based on worker-centric and data-driven technology building blocks. As FACTS4WORKERS is underpinned by a clear human-centric approach: usability, user experience and technology acceptance are of the utmost project interest. FACTS4WORKERS will develop and demonstrate workplace solutions that support the inclusion of increasing elements of knowledge work on the factory floor. These solutions will empower workers on the shop floor with smart factory ICT infrastructure. Advancement will be gained through integrating several building blocks from a flexible smart factory infrastructure, focusing on workers’ needs, expectations and requirements, and being supported by organisational measures and change management. In line with our assumptions on impacts on productivity we therefore estimate that that we can increase job satisfaction for 800,000 European workers by the year 2025. These solutions will be developed according to the following four industrial challenges which are generalise-able to manufacturing in general: personalised augmented operator (IC1), worked-centric rich-media knowledge sharing/management (IC2), self-learning manufacturing workplaces (IC3) and in-situ mobile learning in the production (IC4). Moreover, FACT4WORKER‘s objectives in terms of measureable indicators are: • To increase problem-solving and innovation skills of workers; • To increase cognitive job satisfaction of workers; • To increase average worker productivity by 10%; • To achieve TRL 5-7 on a number of worker-centric solutions through which workers become the smart element in smart factories The smart factory demonstrator will be run within the automotive supply chain. The consortium is composed by 15 partners from 7 different EU member states.

Bearing condition monitoring is an important task in any rotary machine application, given that a bearing is a Single Point of Failure that can lead to catastrophic failure of an entire system. A variety of scenarios can arise from a bearing failure, ranging from only a little monetary loss to hard human fatalities. Accordingly to the risk presented by each system, a wide set of monitoring techniques may be considered, from a simple periodic monitoring routine, usually performed locally by an operator, to a permanently online system that triggers warnings or alarms when a fault is detected on a bearing. The ultimate aim of iBearing is to monitor the bearing in real-time, and directly in the structure of the bearing, being subjected to the same surrounding harsh environment defined by oil lubricant and high temperatures. Moreover, the proposed system will apply an advanced data fusion algorithm capable of integrating sensorial data from several sources simultaneously, namely temperature, low frequency accelerations, acoustic emission waves, and quality of the lubricant, in order to calculate the most reliable prediction of the time to failure, without intervention of any testing operator. The consortium composed by Active Space Technologies, Cranfield University, and Schaeffler intend study the best solutions to achieve the iBearing goal. The selected solutions will be designed, implemented and tested on the Schaeffler test rigs, in the framework of the present activity. The final iBearing product will be a miniaturized and integrated piece of equipment to install in any bearing, just requiring minimal adaptations to the shape of new bearings.