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.

KIAFAM (AI-based assistance functions in facility management)

Process data from facility management is analyzed with process mining in order to gain valuable insights into workflows and enable sustainable process optimizations.

Collaboration between man and machine 2.0

The final acceptance requirements for employees were reviewed with the help of UNAs. AI potentials were identified and suggested.

Design of special tools with AI

By building on the extensive design knowledge already available, AI can reduce the number of prototypes and tests required and thus also cut costs.

Position-invariant classification of teeth

An AI-based system for automated tooth classification is being developed that analyzes images of teeth in different orientations and achieves an accuracy of 99.6 %, regardless of tooth color.

Supplier monitoring with AI

In the quick check, historical data from purchasing was analyzed and dashboards were designed to enable more effective supplier monitoring.

Decorative image from project - start a brushing process

Localization of deep boreholes

By calculating the angle between a cleaning tool and the orthogonal viewing angle of the bore, an automated cleaning process is to be made possible.

Machine learning with embedded devices

AI accelerator chips enable lower latencies and higher throughput rates for industrial applications. An analysis of the Hailo-8 AI chip shows great potential for increasing efficiency in machine control.

MRK application for equipping machines

As part of the Quick Check, a concept for equipping machines for punching screw heads has been developed as a collaborative application. The application is designed as a mobile robot platform and by means of a bin-picking solution.

NeuraConnect: Outsourcing compute-intensive operations to a 5G edge cloud

Outsourcing of compute-intensive operations to a 5G edge cloud.

Optical quality control of surfaces

The defects of the thermal deformation of aircraft landing gear are detected by the SFS algorithm. The results of the SFS algorithm can be further processed using AI algorithms. Material defects can be visualized with suitable lighting.