pdmInsight – Predictive Maintenance Applications
Project Description
Predictive maintenance (PDM) is a method designed to find an optimal maintenance cycle for machines. Therefore, sensor values are included to find correlations between measured data and machine behavior.
This interdisciplinary approach includes knowledge about engineering, data mining, and management. We try to enrich manufacturing execution systems (MES) with the features of predictive maintenance for an advanced production control. The research focus is to include generic methods into production processes.
To connect machines to predictive maintenance application it is necessary to deal with machine communication protocols like OPC UA and MQTT. These techniques allow not only the information transfer but also the semantical modeling of machines.
Considering growing data logging, it is necessary to include data reduction techniques and distributed analyses. All collected information is used to train the application and forecast machine behavior.
Project Details
Project Team
| Ulm University | |
 |  Burkhard HoppenstedtUlm University, Institute of Databases and Information Systems |
 | Dr. Rüdiger Pryss Ulm University, Institute of Databases and Information Systems |
 | Klaus Kammerer Ulm University, Institute of Databases and Information Systems |
 | Prof. Dr. Manfred Reichert Ulm University, Institute of Databases and Information Systems |
Funding
The project is partially funded by atr Software GmbH.
Duration
The pdmInsight project has been running since 2016.