From Research to Application: Projects at Fraunhofer EMFT

Aquaplaning and black ice turn streets into dangerous slides, which often leads to serious accidents. Within the framework of the high-performance center »secure intelligent systems« (LZSiS), Fraunhofer EMFT and Uedelhoven Studios are working together on a solution to the problem. A real-time warning system shall identify the potential danger due to water or ice on the road surface, thus enabling a predictive detection of the road conditions. Such an early warning system would increase the road safety for all traffic participants.

The SUE project (Self-driving Urban E-Shuttle) developed an autonomous people mover designed to serve as a highly automated feeder vehicle for regional public transport. The aim was to enable reliable and safe autonomous driving under real infrastructure conditions - at speeds of up to 50 km/h. A key component in achieving this is a robust, redundant localization technology developed at Fraunhofer EMFT.

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.

With the Soldering Mobile, the Center for Interconnection Technology in Electronics ZVE at Fraunhofer EMFT is now offering its customers an attractive alternative to onsite training courses at the Oberpfaffenhofen training center. The soldering station on wheels can be put into operation directly at the customer's premises using plug & play.

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 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.

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.

Microrelative movements can lead to crack formation and crack growth in press-fit connections. Together with the Institute of Materials Engineering and the Institute of Drive and Vehicle Technology, both at the University of Kassel, Fraunhofer EMFT researchers are working on a suitable accelerating model to better understand how these undesirable effects occur.

Press-fit technology provides an innovative connection method which, due to its high reliability and robustness, is particularly suitable for safety-relevant connection points. Another advantage is that the method is much more eco-friendly than the soldering technique most commonly used to date. A Fraunhofer EMFT research team is working on a predictive model that relates easily accessible material/process data to the reliability of press-fit contacts.

Whether in automobiles – especially in the context of autonomous driving – or future industrial manufacturing: plugs and electrical connection technologies have a key role to play in digital networking. They are the main interface between machines, control units and data processing systems and so they provide the basis for the functionality, simple handling and reliability of automation technology.