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Knowledge-data Collaborated Digital Twin Model of Papermaking Process

Advanced Materials & Sustainable Manufacturing. 2024, 1(1), 10003; https://doi.org/10.35534/amsm.2024.10003
Zejun Liu    Mengna Hong    Jigeng Li *   
State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510640, China
*
Authors to whom correspondence should be addressed.

Received: 13 Dec 2023    Accepted: 23 Jan 2024    Published: 27 Feb 2024   

(This article belongs to the Topic Collection Circular Economy and Sustainability of Manufacturing )
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Abstract

The structure of the drying section in papermaking process is complex and too compacted to install sensors. In order to monitor the parameters in dynamic and manage the process practically with virtual simulations instead of physical experiments, a digital twin-based process parameter visualization model is constructed in this study. Regarding to the possible missing data in the modeling framework, it is proposed to combine industrial data, and knowledge of mechanism with intelligent algorithms to fill in the missing parameters. Upon which, a digital twin-based data visualization model is established using CADSIM Plus simulation software. Both of the knowledge -based mechanism solution model and the random forest-based parametric prediction model perform well, and the predicted parameters can support the digital twin visualization model in CADSIM Plus. Visual modeling of surface condenser in the paper drying section was realized for example, and results show that the model is capable of monitoring the dynamic changes of parameters in real time, so as to support the optimization and decision making of papermaking process such as formation, drying, et al.

Keywords

Digital twin; Model; Papermaking; Parameter prediction; Simulation

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© 2024 by the authors; licensee SCIEPublish, SCISCAN co. Ltd. This article is an open access article distributed under the CC BY license (https://creativecommons.org/licenses/by/4.0/).