Projects

Remanufacturing boosts circular economies and job creation. RESTORE enhances this with sustainable processes and materials. It merges advanced technologies for better remanufacturing applications. The RESTORE platform will digitize and streamline the remanufacturing process. Fraunhofer SCAI standardizes data for remanufacturing efficiency.

The DeployAI project aims to build and operate a European AI on Demand Platform (AIoDP). To this end, DeployAI brings together industry representatives and research institutions. The aim is to provide trustworthy, ethical, and transparent European AI solutions for use in industry – especially small and medium enterprises – and the public sector.

The ALABAMA project is developing adaptive laser techniques for improved additive manufacturing. The goal is to decrease material porosity and adjust microstructures. The innovation includes the development of models for process optimization. Process parameters are optimized using multi-beam control and laser shaping. Advanced monitoring uses multispectral imaging for quality control. Material tests ensure compliance with requirements. The technology is being tested in aerospace, maritime, and automotive industries. These sectors face challenges regarding material quality. The project promises significant productivity increases and cost reductions. It also promotes the autonomy of the European industry.

This project aims to create a multi-scale patient-specific human virtual twin for patients eligible for CAR T cell therapy, which can be extended to cellular immunotherapies in general.

Over the next four years, PREDICTOM will develop a platform for assessing dementia risks. The platform will enable early detection, allowing timely intervention and preventive treatment.

The overall aim of COMMITMENT is to develop a computational systems medicine framework that allows clinically meaningful stratification of psychotic disorders and the identification of biological processes shared with somatic and neurodegenerative comorbidities.

Recent years have seen an explosion in health data generation from diverse sources. This data has the potential to help advance both research and patient care. However, accessing, integrating, and analyzing it is exceptionally challenging. IDERHA aims to set up an open platform that will facilitate the integration and analysis of diverse types of health data. The platform will link up multiple public and private data sources and implement interoperable tools and services to enable key groups, such as doctors, patients, and researchers, to use the data. To focus their efforts, the IDERHA team will use lung cancer as a use case to design the platform.

A further increase in the performance of supercomputers is expected over the next few years. So-called exascale computers will then be able to deliver more accurate simulation results. Fraunhofer SCAI is developing efficient data analysis methods for the much larger amounts of data generated in this way, which will also provide the engineer with detailed insights into the complex technical interrelationships.

The Real4Reg project, coordinated by the German Federal Institute for Drugs and Medical Devices (BfArM), aims to analyze billing data with the help of AI to generate better insights into drug side effects and interactions.

PIONEER aims to develop and implement an interoperable material modeling and manufacturing ecosystem that enables multi-directional data flow along the material value chain by linking product design and distributed modeling data with information from material characterization, manufacturing processes, and product quality criteria. PIONEER combines a design-by-simulation approach with manufacturing and quality data to optimize product development strategies in high-mix/low-volume production systems.