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Optimization paper production through digitalization by developing an assistance system for machine operators including quality forecast: a concept
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Datum
2022
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Gesellschaft für Informatik e.V.
Zusammenfassung
Nowadays cross-industry ranging challenges include the reduction of greenhouse gas emission and enabling a circular economy. However, the production of paper from waste paper is still a highly resource intensive task, especially in terms of energy consumption. While paper machines produce a lot of data, we have identified a lack of utilization of it and implement a concept using an operator assistance system and state-of-the-art machine learning techniques, e.g., classification, forecasting and alarm flood handling algorithms, to support daily operator tasks. Our main objective is to provide situation-specific knowledge to machine operators utilizing available data. We expect this will result in better adjusted parameters and therefore a lower footprint of the paper machines.
emission and enabling a circular economy. However, the production of paper from waste paper is
still a highly resource intensive task, especially in terms of energy consumption. While paper
machines produce a lot of data, we have identified a lack of utilization of it and implement a concept
using an operator assistance system and state-of-the-art machine learning techniques, e.g.,
classification, forecasting and alarm flood handling algorithms, to support daily operator tasks. Our
main objective is to provide situation-specific knowledge to machine operators utilizing available
data. We expect this will result in better adjusted parameters and therefore a lower footprint of the