Press Release
Self-learning machines
symmedia and the university OWL research a
smart maintenance system
symmedia and the university Ostwestfalen-Lippe research together to
develop an assistant platform for automatic recognition of defective
machine conditions. The basis of the project is the service solution
symmedia SP/1 by the Bielefeld company. In the scope of research, is used
to collect data and analyse operating conditions in high-pressure pumps.
Based on this, a procedure is developed in which machines can
independently recognise faults in the process. The target for symmedia is
expanding its own service solution by this intelligent diagnosis assistant in
future to offer its customers a decisive added value for machine
maintenance. The transfer project also contributes to the top cluster it’s
OWL.
Identification of operating conditions and preventive maintenance of highpressure pumps, in short: IDAHO. This is the title of the transfer project that was
recently started by the university of Ostwestfalen-Lippe and symmedia. At the
Institut für industrielle Informationstechnik of the university of Ostwestfalen-Lippe,
both project participants research a smart assistant system for machines. This
happens based on a specific application project at KMT Waterjet Systems,
market leader in the production of high-pressure pumps for water-jet cutting and
a customer of symmedia. The idea is to observe machines, collect data with
symmedia SP/1 and use them to recognise the "normal condition" of the machine
using methods of artificial intelligence, and teach it to the machine. Based on this
model, deviations during operation of a system can be quickly recognised and
reacted to in time.
"The interaction between the many components in a high-pressure pump is
complex. In addition to the target of recognising unforeseen fault conditions in
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Press Release
time, the challenge is also in performing target-group-oriented stress
measurements," said Dr. Andre Skusa, software architect and research manager
at symmedia. "It is important to measure the wear of individual components and
to draw conclusions from this. Only this way can we develop indicative
maintenance forecasts." In future, the service solution symmedia SP/1 is to be
supplemented by this smart data analysis procedure - and then be usable
independently of the machine type. Machine manufactures are thus given another
service tool to support troubleshooting and for preventive maintenance planning
for their machines.
symmedia is a member in the top cluster it’s OWL (intelligent technical systems
in Ostwestfalen-Lippe). Together with 200 other companies from business and
sciences, the technology network wants to create innovations for industry 4.0 and
design the digital future together.
As of:
2 November 2015
Scope:
2,819 characters, including spaces
Photos:
1. Machine at KMT
2. Visualisation of maintenance manager
3. iPad visualisation at KMT
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Digital text and image material for your article is available online at:
www.symmedia.de/pressemitteilungen/