English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Nowadays cross-industry ranging challenges include the reduction ofgreenhouse gas emission and enabling a circular economy. However, theproduction of paper from waste paper is still a highly resource intensive task,especially in terms of energy consumption. While paper machines produce a lotof data, we have identified a lack of utilization of it and implement a conceptusing an operator assistance system and state-of-the-art machine learningtechniques, e.g., classification, forecasting and alarm flood handlingalgorithms, to support daily operator tasks. Our main objective is to providesituation-specific knowledge to machine operators utilizing available data. Weexpect this will result in better adjusted parameters and therefore a lowerfootprint of the paper machines.

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