Forecasting the Shredder Output Volume Flow Towards Dynamic Control in Waste Management
2025
Tatjana Lasch | Jason Imhof | Lisa Kandlbauer | Renato Sarc | Karim Khodier
The digitalization of mechanical waste treatment can have a supporting effect in recovering valuable raw materials from mixed solid waste, achieving the EU&rsquo:s recycling targets, and developing the waste industry into a circular economy. Therefore, influencing factors on machines and the entire plant must be known. Furthermore, optimization potentials can be developed with the help of digital approaches, such as dynamic control of machine and plant operation, to be able to control the heterogeneous material streams to enable optimized treatment and preserve valuable materials. To establish dynamic control in waste treatment machines, sensors are required to record the necessary variable parameters. In this work, the focus of those variables is placed on the volume flow leaving the shredding machine, where a volume flow sensor is used as a sensor system. To predict the volume flow of the shredder&rsquo:s output to create a possible dynamic control, forecasting with ARIMA models is used. Initial results show that it is possible to predict a heterogeneous material stream with a selected model, currently over a time period of 10 s. However, the testing of additional prediction models still offers the opportunity of predicting the material stream over a longer period of time to enable dynamic control.
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