Circular Economy and Sustainability of Manufacturing

Deadline for manuscript submissions: 31 July 2024.

Topic Editors (5)

Zhenglei  He
Prof. Dr. Zhenglei He 
State Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou, 510640, China
Interests: Intelligent Manufacturing; Industrial Engineering; Simulation and Optimization
Vijay  Kumar
Prof. Dr. Vijay Kumar 
Department of Business Administration and Textile Management, Faculty of Textiles, Engineering and Business, University of Boras, Sweden
Interests: Nonwovens materials; Micromechanics; Image Processing; Artificial Intelligence and Machine Learning; Supply Chain Management; Supply Chain Traceability
Anne  Perwuelz
Prof. Dr. Anne Perwuelz 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Ecodesign; Green Chemistry; Sustainable Process; Life Cycle Assessment; Circular Economy
Sébastien  Thomassey
Prof. Dr. Sébastien Thomassey 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Supply chain; Production management; Sales forecasting
Zhebin  Xue
Prof. Dr. Zhebin Xue 
College of Textiles and Clothing Engineering, Soochow University, No. 1 Street Shizi, Suzhou, China
Interests: Data-driven Intelligent Manufacturing; Circular Economy; Sustainable Fashion; Smart Wearable Systems

Topic Collection Information

Published Papers (1 papers)


27 February 2024

Knowledge-data Collaborated Digital Twin Model of Papermaking Process

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.

Zejun Liu
Mengna  Hong
Jigeng Li*
Advanced Materials & Sustainable Manufacturing-logo