Advanced Materials & Sustainable Manufacturing

Guide for Authors Submit to AMSM

AI-based Sustainable Smart Industrial Systems

Deadline for manuscript submissions: 30 November 2024.

Guest Editors (4)

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
Website: https://www.researchgate.net/profile/Zhenglei-He
Matilde Santos
Prof. Dr. Matilde Santos 
Instituto de Tecnología del Conocimiento, Computer Sciences Faculty, University Complutense of Madrid, Madrid, Spain
Interests: Intelligent Control; Modeling and Simulation; Soft Computing; Engineering Applications; Floating Wind Turbines
Website: http://www.dacya.ucm.es/msantos/indexe.html
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
Website: https://www.gemtex.fr/gemtex-members/phuc-tran/
Xianyi Zeng
Prof. Dr. Xianyi Zeng 
University of Lille - ENSAIT, GEMTEX laboratory, F-59100 Roubaix, France
Interests: Fashion Digitalization; Wearable Systems; Decision Support Systems
Website: https://www.gemtex.fr/gemtex-members/xianyi-zeng/

Topic Collection Information

The last decades have witnessed the rapid growth of Artificial Intelligence (AI) and its applications that add intelligence into industrial applications to drive continuous improvement, knowledge transfer, and data-based decision making, leading to development of modern industries towards sustainable and smart innovative manufacturing and management models. Multiple sustainable criteria, including product quality, environmental impacts, recycling capacity, should be simultaneously considered in these models. A huge volume of data collected from various industrial process can feed real-time analytic solutions provided by AI and Decision Support Systems (DSS), which can lead to optimal industrial operations.

In this context, extended from the related papers presented in the international conference of FLINS-ISKE 2024, this special Issue aims to offer a systematic overview of AI-based sustainable smart industrial systems and provide innovative computational intelligent approaches, to effectively support decision making in big data environments. The concerned industrial applications will include quality control, manufacturing process optimization, recycling, environmental impacts evaluation, and so on.

Published Papers (0 papers)

TOP