Enhancing industrial maintenance through intelligent data analysis

Authors Patrick Praher
Bernhard Freudenthaler
Werner Schröder
Florian Sobieczky
Editors R. Moreno-Díaz
F. Pichler
A. Quesada-Arencibia
Title Enhancing industrial maintenance through intelligent data analysis
Booktitle Computer Aided Systems Theory – Proc. EUROCAST 2019, Part II
Type in proceedings
Publisher Springer
Series Lecture Notes in Computer Science
Volume 12014
ISBN 978-3-030-45095-3
DOI 10.1007/978-3-030-45096-0_57
Month April
Year 2020
Pages 469-476
SCCH ID# 18091
Abstract

For years, the amount of data generated in many industrial production plants has been said to have great potential for improving maintenance processes. In order to leverage this potential in practice, however, it is necessary to overcome a number of hurdles from automated data exchange, linking separate data sources, evaluating the actual data quality to the automated evaluation of existing data. In the project “Smart Maintenance” together with our industrial partners BMW Motors Steyr and BRP Rotax, we have developed a practical procedure to analyze the operating-, error- and sensor-data in a user-friendly web interface. This enables us to make the data utilizable for improving maintenance processes. The core functionality consists of various filter and aggregation mechanisms. Based on these different forms of visualization allow the intuitive interpretation of events in order to integrate new contexts into the daily routine of maintenance planning.