From Research to Application: Projects at Fraunhofer EMFT

In the European project SpikeHERO, Fraunhofer EMFT develops input neurons that turn photocurrents into spikes, plus a SENNA redesign targeting spike rates up to 500 MHz.

Cynergy4MIE is an EU-funded research project aimed at developing a platform for sensor technology, electronics and AI in mobility, infrastructure and energy systems. The goal is to accelerate innovation and strengthen Europe's competitiveness.

How can supply chains for the chip industry become more independent and better protected? The coronavirus pandemic in particular has highlighted the problems for Germany and Europe. In the "Semiconductor-X" research project on the digitalization of supply chains in the semiconductor industry, Fraunhofer EMFT is working with over 20 partners to make supply chains more sustainable and resilient and to promote decentralized, sovereign data exchange.

The technology is already state of the art in modern cars: radar sensors that alert the driver when the vehicle is approaching an obstacle. Collision protection of this kind is also crucial in the future of production - smart factories in which intelligent industrial robots are expected to act completely autonomously in an increasing number of work steps - in order to ensure safe cooperation between man and machine. In the RoboMove project, Fraunhofer EMFT is working with robotics manufacturer KUKA and InnoSenT GmbH to develop an intelligent 3D distance measurement and obstacle detection system for robot arms in motion.

The DigiSeal research project is setting new standards in the predictive maintenance of mechanical seals, which are essential for many branches of industry. By using informed AI and the expertise of Fraunhofer EMFT, precise models are being developed that not only predict maintenance requirements, but also provide specific recommendations for action. Together with partners such as EagleBurgmann Germany GmbH & Co. KG, Molkerei Alois Müller GmbH & Co. KG and Munich University of Applied Sciences, digitalization in the industry is being driven forward and a significant contribution is being made to Industry 4.0.

Gear oils make a significant contribution to minimising friction and thus ensure the safe operation of production facilities. In the Smart Gear project, researchers at Fraunhofer EMFT are developing solutions to detect a drop in the performance of gear oils with the help of sensor technology and machine learning methods and to predict when the oil needs to be changed.

The aim of predictive maintenance is to maintain operating resources proactively and with foresight. This should reduce downtime and maintenance costs to a minimum. Researchers at Fraunhofer EMFT are testing new concepts that use machine learning methods to efficiently process even extremely heterogeneous data and make accurate maintenance predictions for production facilities.

Safety First! - Is the motto of the "StressScent III" project, in which researchers from Fraunhofer EMFT, in collaboration with the University of the Bundeswehr Munich, have developed a Virtual Reality System (VR System) which uses realistic and immersive training to better prepare rescue and emergency personnel for sometimes dangerous missions and stressful situations and thus contribute to a safer working life. Through realistic training engaging all senses, real-world situations can be simulated more accurately, thus contributing to a safer work life. The goal of the project is to develop a scent dosing system adapted to an existing VR headset for practical application.

Within the SOIL project, Fraunhofer EMFT develops FDSOI IP blocks to boost Europe's next-generation chipindustry.

SENNA Connect develops a developer kit for the SENNA neuromorphic processor, so you can run spiking neural networks on real hardware instead of in simulation.