Projects

The integration of recycled materials continues to pose challenges for the manufacturing industry, as the quality of the products depends on the interaction between the materials used and the manufacturing processes. Variations in trace elements and chemical properties affect additive manufacturing processes such as 3D printing. The GEAR-UP project aims to develop digital tools to facilitate the use of recycled materials in metal and plastics processing. Simulation-based approaches and AI methods will be used to establish resource-efficient manufacturing processes. The digital product passport developed in the project ensures the traceability of materials.

The SYNTHIA project team develops new techniques for the responsible generation and use of synthetic patient data. These data, generated using generative methods of artificial intelligence, can help overcome data protection hurdles, improve prediction models for personalized medicine, and emulate control groups in clinical studies. The validated synthetic data will then be made available on a modern IT platform, together with their possible applications.

Today, most crash tests to evaluate vehicle safety are conducted virtually. Documenting the changes to the simulated vehicle models is particularly time-consuming and costly. The SAFECAR-ML project aims to simplify this process. By combining novel methods of artificial intelligence (AI) with technical knowledge from vehicle development, the project partners from research and automotive industry want to standardize the information processing for the documentation of virtual crash tests. New is the combination of semantically processed free text with multimodal engineering data for machine learning.

The main objective of the ETHCSTWIN initiative is to establish a collaborative network between the Institute of Ethnopharmacological Studies and Phytotherapy (IESP, Athens) and two renowned academic research teams from Italy (UNISG, Pollenzo) and Germany (Fraunhofer SCAI), as well as the biotech SME Pangea Botanica and the University of Prishtina. The goal is to integrate the knowledge of ethnopharmacology into novel computational and digital systems, focusing on the development of a rich portfolio of complex methods and tools, including the analysis of large data sets and the restoration of tangible and intangible heritage.

The BASE project aims to develop the digital battery passport, which every larger battery will be required to have in the future. The passport will contain continuously collected data on the "State of Health" as well as information on the supply chain, the manufacturing process and material data. It will apply the "mass balance" method, which offers a detailed accounting of the materials used in battery production, with special emphasis on the use of sustainable components. The data from the battery passport is stored in a decentralized and tamper-proof manner so that all parties involved have access to it. This enables the optimization of battery lifespan and enhances recycling.

The SmartEM project develops a standardized system that allows to combine different computational engineering models from different sources and to merge them into a complete system. This flexible reference architecture, inspired by open data space concepts such as Gaia-X, promotes collaboration between different actors and enables the reuse of engineering models. This makes development processes more efficient and replaces manual, time-consuming procedures for creating digital twins. The AI-based generation of "surrogate models" - simplified versions of complex models from heterogeneous data sources - facilitates model integration and thus improves interoperability. In this way, SmartEM accelerates digital transformation and innovation in engineering.