2025_02_19-20_Maintenance EN

Dortmund / Fair / February 19, 2025 - February 20, 2025

Maintenance 2025

Leading Trade Fair for Industrial Maintenance

We are on site at the joint stand of the Fraunhofer Smart Maintenance Community: Hall 4 Stand number: 4-D01

Maintenance in Dortmund is the leading trade fair for industrial maintenance, where experts from various sectors come together every year to present and exchange innovations and trends.

Together with the Fraunhofer Institute for Material Flow and Logistics IML, we present innovative solutions for smart maintenance. Our joint stand offers insights into data-based systems that improve overall equipment effectiveness (OEE). Visit us to learn more about predictive maintenance strategies and modern technologies!

Our colleagues Tobias Wolf, Dr. Benjamin Adrian, Mark Maasland and Markus Rauhut are on site at the Fraunhofer Smart Maintenance Community stand to present data-based solutions and software systems from the institute that sustainably improve overall equipment effectiveness (OEE) in manufacturing:

Monitoring Drive Shafts: With the magnetostrictive sensor, we demonstrate how torsion and speed can also be integrated into condition monitoring at a later stage in typical drive trains. The software enables the detection of dynamic and static torsional loads.
Integrated Quality Monitoring: Using image processing techniques, we demonstrate the integration of quality control into condition monitoring to detect quality defects at an early stage and thus reduce avoidable rejects.
Predictive Maintenance: We show how to build step-by-step AI models that use mathematical methods to capture and predict the wear and tear of machinery, taking into account utilisation.

Demonstrator VibDemo — © Fraunhofer ITWM
We demonstrate these solutions using the example of a miniaturized VibDemo drive train to show interactively how machine states can change in different load scenarios and still be monitored.

Our Topics

Predictive Maintenance

Industry 4.0 and digitalization increase production efficiency through predictive maintenance and condition monitoring, which minimizes downtimes and optimizes maintenance. Our solutions use intelligent algorithms and multi-sensor technology for condition monitoring, automated KPI collection and effective maintenance strategies, which saves costs.

Project »EMILIE«

In the »EMILIE« project (Embedding Machine Intelligence Logic and IT Security into Edge Devices), we are working with our partners to improve the electronics used for this purpose and the so-called edge gateways. These are designed to securely and robustly collect information, process it based on artificial intelligence (AI) and optimally control and monitor production processes.

AI Applications for Industry with Little Data

Artificial intelligence is revolutionizing industrial quality control with flexible systems. Despite the challenge of generating sufficient defect images, we successfully use innovative approaches such as synthetic data and transfer learning. Our projects demonstrate the practical use of AI in quality control.

Inline Quality Control for Production

We offer customized solutions for automated quality control in production that combine classic image processing and machine learning.

Fair

Dortmund / Fair / February 19, 2025 - February 20, 2025

Maintenance 2025

More Information

Our Topics

Predictive Maintenance

Project »EMILIE«

AI Applications for Industry with Little Data

Inline Quality Control for Production

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Dr. Benjamin Adrian

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Dipl.-Math. Mark Maasland

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Dipl.-Inf. Markus Rauhut

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Tobias Wolf