Sustainable Data-driven Intelligent Manufacturing Systems

Deadline for manuscript submissions: 31 May 2024.

Topic Editors (4)

Sébastien  Thomassey
Prof. Dr. Sébastien Thomassey 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Supply chain; Production management; Sales forecasting
Kim-Phuc  TRAN
Prof. Dr. Kim-Phuc TRAN 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France 
Interests: Industrial AI; Statistical Computing; Embedded AI; Human-centered AI; Decision Support Systems
Xuyuan  Tao
Prof. Dr. Xuyuan Tao 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Smart Textile; Virtual Textile
Xianyi  Zeng
Prof. Dr. Xianyi Zeng 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Fashion Digitalization; Wearable Systems; Decision Support Systems

Topic Collection Information

As the fourth industrial revolution has passed an early stage of development, many companies are developing data-driven decision-making approaches with Artificial intelligence (AI) and cutting-edge innovations of Industry 4.0 to improve productivity and quality. Meanwhile, the next phase of industrialization has been introduced, known as Industry 5.0 which focuses on humans, resilience, and sustainability. One of the most prominent features of Industry 5.0 is that it places humans at the center of an everything-connected intelligent manufacturing process , a concept of human-robot- product/material interaction and collaboration, and long-term sustainability considering material recycling and environmental impact minimization . Moving to Industry 5.0, with the human-centric orientation, AI was developed in combination with human intelligence (HI), leading to the new concept of Augmented Intelligence (AuI). AI and AuI algorithms are expected to bring significant benefits for enabling Sustainable Data-driven Intelligent Manufacturing Systems in Industry 5.0. The special session aims at collecting papers on Sustainable Data-driven Intelligent Manufacturing Systems in Industry 5.0. This special section will bring together researchers and practitioners to discuss and explore the most promising industrial applications of data-driven decision-making approaches for Sustainable Data-driven Intelligent Manufacturing Systems. Topics include but are not limited to:

- Digital twin, Internet of Things, and big data-driven Intelligent Manufacturing Systems
- Augmented Intelligence-enabled data-driven Intelligent Manufacturing Systems
- Industry 5.0 and the future of sustainable manufacturing
- Decarbonization and Industry 5.0
- Sustainable multicriteria product and process design
- Intelligent Life Cycle Analysis (LCA)
- Material recycling and AI techniques
- Human-Centered Design of AI and Explainable AI for Industry 5.0
- Cybersecurity in Intelligent Manufacturing Systems
- Quantum machine learning for sustainable manufacturing
- Wearable technology for sustainable Data-driven Intelligent Manufacturing Systems in Industry 5.0

Published Papers (2 papers)


17 January 2024

A Review on Significant Role of Additive Manufacturing in Biomedical Applications

The rapid development of manufacturing sector has created a platform for implementing novel technologies such as additive manufacturing (AM). AM or 3D printing, has generated a lot of interests in biomedical applications during the last decade with a variety of novel printed polymeric materials. 3D printing fabricates 3D object with layer-by-layer processing through computer-controlled programming software. It has innumerable applications including electronics, aerospace engineering, automobile industry, architecture and medical sectors. One of the most demanding sectors of 3D printing is biomedical engineering applications such as medicines, drug delivery system, surgical instruments, orthopedics, scaffolds, implants etc. The clinical ramifications of AM-made healthcare goods are being catalyzed by recent developments in biomaterials. This review paper aims to explain the concept of 3D printing and its significance in developing polymeric materials for biomedical applications. An inclusive survey has been conducted on the various techniques involved in printing the biomedical devices. The proper selection of polymeric materials is important for biomedical applications, especially from 3D printing point of view and this vital parameter has been considered in this review paper. According to our findings, more breakthroughs in biomaterials, are required for the success and expansion of AM technology in the biomedical applications.

Tanusree Bera*
Advanced Materials & Sustainable Manufacturing-logo


30 May 2024

A Review on Design of Sustainable Advanced Materials by Using Artificial Intelligence

This paper gives a comprehensive review of scientific interests and current methodologies of artificial intelligence applied to advanced material design and discovery by taking into account multiple sustainable design criteria such as functionalities, costs, environmental impacts, and recyclability. The main research activities include predicting material properties, compositions, and structures with data mining, new material discovery, hybrid modeling approaches combining AI techniques and classical computational formulations based on physical and chemical laws, and multicriteria optimization of materials. Based on this review, a short analysis is provided on the perspectives of this research area in the future, aiming at creating an everything connected material life cycle with real-time traceability systems

Xianyi Zeng*
Advanced Materials & Sustainable Manufacturing-logo