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The BMW Group uses a powerful Digital Twin Registry (DTR) based on Eclipse BaSyx. It helps users to quickly find digital twins in the Catena-X data space and unambiguously map them to the corresponding data sets. Fraunhofer IESE implemented the solution and optimized it, particularly in terms of performance, scalability, and future-proofing.

In this workshop, Fraunhofer IESE collaborated with Daimler Truck and its customers to explore how software-defined systems are fundamentally transforming the development, functionality, and business models of commercial vehicles. The focus was on technological fundamentals, specific areas of application, and the opportunities presented by a more flexible, connected, and updatable vehicle architecture.

Reference Project: Gideon: The “Gideon” project (Public-Good-Oriented Innovations Through the Use of Data in Organizations and Networks) is developing an AI-supported data ecosystem that helps organizations securely and automatically exchange data.

As part of the VIMOPROP project, the Fraunhofer Institute for Experimental Software Engineering IESE developed a modular software platform designed to support pharmaceutical manufacturers in the virtual planning, simulation, and commissioning of production processes. The goal was to make the manufacture of complex and highly customized Advanced Therapy Medicinal Products (ATMPs), such as gene and cell therapies, more flexible, efficient, and compliant with regulatory requirements. In doing so, the strict requirements of pharmaceutical production are taken into account from the very beginning.

As part of the "Mittelstand-Digital" funding priority of the Federal Ministry for Economic Affairs and Energy, Fraunhofer IESE, together with Ansbach University of Applied Sciences, Nuremberg Tech, and the Academy for Artificial Intelligence (AKI), supports companies in classifying and introducing AI and sustainability in their own operations.

UncertAInty (Uncertainty Quantification in AI Systems for International Compliance) is a WIPANO project funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK) that advances the systematic handling of uncertainty in AI systems. Over a 30-month period, partners from industry, research, and standardization are working together to clearly describe uncertainties in AI, make them measurable, and standardize them internationally as part of the development of ISO/IEC TS 25223.

Fraunhofer IESE has collaborated with the DIHK to design a digital ecosystem for register modernization in order to realize opportunities through platform business models for commercial registers. To this end, IESE has tailored and applied its proven and flexible methods for modeling ecosystems to the context of register modernization in a specific application.

Project for the automated creation of training content from existing data using generative AI.

The aim of the “OneViewMed” (OVM) project was to significantly improve the information situation for medical staff. Work processes were to be simplified and patient safety further increased. To achieve this, Fraunhofer IESE developed a graphical dashboard together with medical staff and the IT departments of Frankfurt University Hospital in order to facilitate the work of medical staff and ensure interoperability between the IT systems used on different wards.

How Fraunhofer IESE and Robert Bosch GmbH make complex safety-critical applications automatically testable using Linux as the operating system platform.