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

• URL: http://arxiv.org/abs/2206.11581v1
• Date: Thu, 23 Jun 2022 09:54:35 GMT
• Title: Optimization paper production through digitalization by developing an assistance system for machine operators including quality forecast: a concept
• Authors: Moritz Schroth, Felix Hake, Konstantin Merker, Alexander Becher, Tilman Klaeger, Robin Huesmann, Detlef Eichhorn, Lukas Oehm
• Abstract summary: The production of paper from waste paper is still a highly resource intensive task, especially in terms of energy consumption. 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. Our main objective is to provide situation-specific knowledge to machine operators utilizing available data.
• Score: 50.591267188664666
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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