Optimization paper production through digitalization by developing an assistance system for machine operators including quality forecast: a concept

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 d...

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Bibliographic Details
Published in:arXiv.org 2022-06
Main Authors: Schroth, Moritz, Hake, Felix, Merker, Konstantin, Becher, Alexander, Klaeger, Tilman, Huesmann, Robin, Eichhorn, Detlef, Oehm, Lukas
Format: Article
Language:English
Subjects:
Algorithms
Digitization
Energy consumption
Flood forecasting
Greenhouse gases
Machine learning
Operators
Optimization
Paper machines
Online Access:Get full text
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Summary: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.
ISSN:2331-8422