Projects

The battery although is at its central role for green transitioning of the road transport, the current battery supply chain is lacking in traceability and sustainability, resiliency, and circularity aspects. Critical Raw Materials (CRM) are essential ingredients for battery manufacturing. The exploding growth of Electric vehicles driven by the climate neutrality policy objectives will create pressure on CRM supply chain and will increase the EU dependency for CRM on 3rd countries, resulting in decrease of competitiveness of the EU automotive and battery manufacturers. Implementation of the digital battery passport (DBP) concept in the battery value chain might resolve these issues.

SmartEM aims to address the limitations of current engineering models by developing a reference architecture for engineering model spaces. The architecture will enable the reuse, exchange and integration of computational engineering models, reducing the need for costly design corrections and promoting early data and model exchanges. SmartEM will use AI-assisted methods to create surrogate models from heterogeneous data sources and allow their re-combination within a given engineering domain. The project will develop use-case model spaces to manage reusable and transferable engineering models for various domains and provide solutions for IP management to enable model exploitation in an increasingly digital engineering market.

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.

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.

Fraunhofer SCAI coordinates the COMMUTE project, backed by a grant from the European Commission. Over the next four years, an interdisciplinary team of top-tier experts will explore whether COVID-19 infections increase the risk of acquiring neurodegenerative diseases. An innovative AI-driven system is being developed to provide tailored risk assessments for individuals who have recovered from COVID-19.

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.