Particularly in multi-stage manufacturing processes, the focus of manufacturing execution systems is no longer just on control, but above all on working with data that can be obtained from the process. Both during the start-up of new plants and in stable operation, advanced analytics models can help to actively identify deviations and error focal points in this data in order to take countermeasures more quickly in the right place. Markus Hummel from Dürr uses the example of paint shops to show how data can be used to identify and analyze quality problems, thereby uncovering hidden optimization potential and efficiently eliminating the causes by correlating it with anomalies from upstream process steps.
|November 22, 2021
|14:45 pm - 15:15 pm