Demo system as a database
All of this data is recorded and saved in the cloud synchronously. “The demo system essentially creates the basis for our data-led manufacturing research, for example by training self-learning algorithms”, the researchers explain. These algorithms are then to be applied to industrial applications at a later date. In this context, they will then not only be able to identify and localize any leakages, but at the same time provide a description and the serial number of the affected component via an app in future as well. The person attending to the compressor unit therefore no longer needs to search through a catalog. Instead, they can order a replacement in just a few clicks and keep the downtime to a minimum. “In addition to classifying the leakage, the focus is also on identifying the actuators present in the compressor network with minimal effort”, Dierolf explains.
However, as is the case with many other ideas that researchers have come up with, this is still some way off being a reality. The seminar “Intelligent Compressed Air – identify potential and increase efficiency with Industry 4.0 methods”, which is being held at Fraunhofer IPA in Stuttgart on November 6th, 2019, will showcase the methods that are already today being used to leverage efficiency potential and cut costs, with Industrie 4.0, among other concepts, playing a significant role in this.