Production and quality management

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.

Development and innovation

Logistics and merchandise management

Marketing and communication

Production and quality management

Administration and organization

AI industrialization support for galvanic processes

In the introduction of a new Cr(III)-based electroplating hard chrome plating process, machine learning is used to analyse complex process relationships and accelerate industrialization. The aim is to increase the efficiency and quality of the process by accurately predicting the electrolyte composition.

AI Competence in Customer Support

In the project, potentials for the use of AI in customer service were identified and prioritized to sustainably increase service efficiency through forward-looking planning, intelligent automation, and improved information utilization. Based on a structured analysis, concrete implementation concepts are being developed for the three most promising use cases: social workforce planning, predictive maintenance, and an AI-powered assistance system.

AI potential

The AI Innovation Center develops solutions to optimize production at Ansmann AG, including predicting production times and detecting installation errors in battery cells.

Source: Fraunhofer IPA / Rainer Bez

AI-ready machining

The integration of AI in the mechanical engineering industry requires standardized interfaces for reliable data transmission. A technology comparison identifies suitable protocols for optimizing process monitoring and control.

Decorative image AI Innovation Center

AI use cases for the h-aero® platform

The AI Explorer identifies and prioritizes promising AI use cases for the h-aero® platform in order to make optimal use of resources and promote rapid implementation.

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.

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.

ML-supported prediction of screw straightening quality

ML-supported prediction of screw straightening quality Quick Check Initial situation In the production of screws, slight initial bends regularly occur, which are corrected manually before further processing in a hydraulic press machine. The screws...