Predictive maintenance is the concept of analyzing sensor and production data in order to recognize or forecast wear processes and malfunctions in machinesat an early stage. The main objective of predictive maintenance is to optimally time maintenance measures such that they are carried out before actual machine failure in order to keep damage and downtimes to a minimum.
of machine failure
In addition to a suitable IT infrastructure for data storage and analysis and presentation of results, implementing predictive maintenance solutions requires first and foremost smart data. Smart data includes the necessary relationships and properties for describing wear processes and malfunctions. In some cases this is very simple. For instance, a change in vibration in a bearing can be a sign of wear. However, for wear processes that underlie more complex, physical processes, we need a deeper understanding of the processes themselves in order to be able to identify variables through which the wear can be characterized.
Permanent and automated monitoring of systems can identify disruptions in systems at an early stage so they can be resolved faster, which results in greater availability of the machines and systems. The analysis of relevant key variables (smart data) within a predictive maintenance service can more quickly identify causes of errors (see root cause analysis), which lowers service costs and improves customer satisfaction through better service.
We are happy to consult with you regarding proper selection of your predictive maintenance use cases, to work with you on suitable analytic solutions, and integrate them in your systems. You can thereby receive a complete predictive maintenance solution from a single source.
Das Kernelement der Wirtschaft von morgen ist die ‚Intelligente Vernetzungʻ: Wenn Mensch zu Maschine oder Maschine zu Maschine kommuniziert, entstehen neue Wertschöpfungspotenziale. Maschinenbauer werden so zu den Goldgräbern der Zukunft.
Katana, the data analytics segment of the USU Group, has extensive experience in the application of machine learning methods in the industrial sector. Take advantage of our knowledge and our solutions for building your data-driven business models to reduce your costs and improve your quality and value added.