Circular Economy and Sustainability of Manufacturing

Deadline for manuscript submissions: 31 July 2024.

Guest 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

Special Issue Information

This Special Issue on Circular Economy and Sustainability of Manufacturing focuses on practical and forward-looking approaches to making manufacturing more sustainable. It welcomes research on life cycle assessment (LCA), traceability in production and supply chains, recycling, green manufacturing, and the use of renewable energy. Topics such as waste and secondary materials management, industrial pollution control, and sustainable supply chain strategies are also encouraged. We are particularly interested in work that connects policy, practice, and training to support long-term, system-wide change in the manufacturing sector toward circularity and environmental responsibility.

Published Papers (2 Papers)

Open Access

Article

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*
Adv. Mat. Sustain. Manuf.
2024,
1
(2), 10003; 
Open Access

Case Report

22 August 2025

Root Cause Identification of Vibration and Wear Due to Strainer Obstruction in Hydrocarbon Processing Compressors

This study examines the root causes of vibration and wear in centrifugal compressors, particularly emphasising strainer obstruction in hydrocarbon processing environments. Strainer fouling is primarily driven by deposits from inlet gas compositions and deviations in operating conditions, which restrict flow, increase vibration, and accelerate component degradation. A combined methodology was applied to investigate these issues, including baroscopic inspection of compressor internals, chemical analysis of deposited materials, and evaluation of operational records against design specifications. Maintenance histories and strainer cleaning frequencies were also reviewed to establish links between performance decline and operating practices. The findings show that chemical cleaning is the most effective and cost-efficient solution, outperforming high-pressure water jet cleaning and full compressor overhauls by minimising downtime, restoring flow dynamics, and improving mechanical stability. Successful implementation across multiple compressors confirmed its scalability and reliability. This research validates chemical cleaning as a preferred maintenance strategy, delivering significant operational and economic benefits while extending compressor service life.

Jamaladdin  NuraddinAslanov
Tarlan ElmanFarajov*
Adv. Mat. Sustain. Manuf.
2025,
2
(3), 10010; 
TOP