From Research to Application: Projects at Fraunhofer EMFT

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.

In the PCB direct contacting research project (T-1753), Fraunhofer EMFT investigated PCB direct contacting systems for highly reliable mechatronic and drive technology applications. The aim was to evaluate commercially available systems in terms of technical performance, reliability and economic suitability under realistic environmental and stress conditions.

In areas where personal or security-critical data is processed in particular – such as medical technology, autonomous driving and critical infrastructures – trustworthy electronic ICT compo-nents and systems are becoming increasingly important as digitalization gathers pace. esearchers at Fraunhofer EMFT primarily focus on the hardware level here.

Every year, over 3 million immobile people worldwide suffer from severe, mostly preventable pressure ulcers, with around 0.6 million in Germany. Pressure ulcers not only cause personal suffering but are also time-consuming and costly to treat. Current prophylaxis methods require significant commitment from nursing staff and do not provide continuous security. Therefore, there is an urgent need for individual and continuous monitoring for effective pressure ulcer prophylaxis. Sorala (formerly SoreAlert), a potential spin-off from Fraunhofer EMFT, addresses this need with a smart patch that allows for automated monitoring of at-risk body areas and provides early warnings for pressure ulcers.

Edge computing is considered a key for new IoT applications. In order to bring artificial intelligence into future edge products, Fraunhofer EMFT researchers are working together with Fraunhofer IIS and Fraunhofer IPMS as part of the EU ANDANTE project to develop innovative mixed-signal artificial neural network (ANN) accelerator with computation-in-memory (CIM) ability. These are intended to enable the construction of solid hardware and software platforms for AI application development.

Nature sets a high bar: Our brain is capable of processing and storing huge amounts of information without using more energy than a 20-watt light bulb. This is a good reason for researchers worldwide to take the human brain as a model for circuits in so-called neuromorphic chips. Within the EU project NeurONN, a Fraunhofer EMFT research team is working with six European partners on extremely energy-efficient elements and architectures for neuromorphic computing. Innovative 2D materials are also being used in the process.

An advanced abatement system and exhaust gas cleaning solutions capture and reduce PFAS, NF3, and SF6 emissions in semiconductor manufacturing.

Many plasma coating systems used in the semiconductor industry have to undergo thorough cleaning on a regular basis after each stage of production. Currently this is mainly carried out using perfluorinated compounds (PFCs) and nitrogen trifluoride (NF3) gases, which are up to 17,000 times as damaging to the environment and climate as the greenhouse gas CO2. Solvay, Texas Instruments, Muegge and Fraunhofer EMFT are working on the project ecoFluor to develop an environment-friendly alternative which only has the greenhouse potential of CO2: the gas mixture used by the cooperation partners – Solvaclean®, consisting of fluorine, nitrogen and argon – dispenses entirely with the highly environmentally harmful gases PFCs and NF3.

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 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.