Projects

A central focus of the AI Innovation Center is direct cooperation with industrial companies: Feasibility studies (Quick Checks) and projects to develop initial prototypes (Exploring Projects) of AI applications. In addition, consortium projects and innovation networks are aimed at cross-company exchange.

Evaluation of the relevance of image data in the training of neural networks

A method for evaluating the quality of image data when training neural networks is being developed in order to identify inferior images at an early stage and reduce costs and training time.

DASH Board: Data Analytics for Sustainable Healthcare

The DASH Board pursues the analysis and use of patient data to develop innovative digital health solutions that optimize healthcare and ensure data security.

DIEFEDA - direct error feedback during assembly

An AI-supported assistance system improves assembly processes through real-time feedback, minimizes error rates, relieves skilled workers and optimizes the final inspection to increase quality and competitiveness.

Digital integration

A linked knowledge database for the injection molding process is being set up to detect anomalies at an early stage and learn robust parameters. AI optimizes system parameters for new products.

Drag & Imitate - Human-centered robot programming

Intuitive robot programming through the combination of programming-by-demonstration and a user-friendly interface enables even non-experts to create intelligent robot programs efficiently.

Recognition and evaluation of future theses

Reliable early indicators emerge from large data streams: Algorithms discover new topic clusters, check hypotheses with contextual understanding and provide compact situational pictures for better planning, innovation and decisive management.

Explainable AI: Evaluation of explainability methods in the application

Explainable AI methods enable the traceability of AI decisions, especially in regulated industries. The project develops best-practice approaches for the use of XAI in real applications.

Vehicle part segmentation for improved damage detection

AI-based vehicle part segmentation improves damage detection by precisely assigning defects to vehicle parts, reducing misclassifications and estimating repair costs more accurately.

FlexCab - flexible, intelligent cable assembly

A flexible, intelligent robot system for the automated assembly of high- and low-voltage connectors is being developed to reduce manual labor and increase efficiency.

FOCUS Bikes Service Assist

Teaching faults via a single sensor on the bike offers the opportunity to increase the quality of bikes, service and safety.