Unscheduled machine downtimes due to delayed maintenance cause costs and bottlenecks in production and, in the worst case, reduces delivery reliability. Predictive maintenance significantly reduces or eliminates these issues. Prerequisite, however, is the targeted evaluation of machine data. An optimized visualization and remote services make it possible to carry out the maintenance work within a short time. This article describes the key criteria for developing a predictive maintenance strategy and discusses current trends in the visualization of available data.
|Translated title of the contribution||Increased productivity by predictive maintenance and data visualization|
|Original language||German (Austria)|
|Number of pages||3|
|Journal||ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb|
|Publication status||Published - 2019|