Dear Scholars,
We are delighted to announce a collaborative Special Issue between the journal Industries (ISSN 3042-9021) and the 2026 International Conference on Green Intelligent Manufacturing (GIM 2026).
Organized by the University of Birmingham and Cardiff University, United Kingdom, from July 14–16, 2026, GIM 2026 serves as a vital international platform for researchers, engineers, and managers to exchange cutting-edge ideas on sustainable and smart production systems. As global industries navigate the dual pressures of environmental responsibility and technological advancement, this conference fosters interdisciplinary dialogue on reshaping the future of manufacturing.
This Special Issue aims to capture and disseminate the highest-quality work presented at GIM 2026. We invite expanded and enhanced versions of selected conference papers that report original research, significant case studies, or comprehensive reviews. The focus will be on contributions that bridge the gap between green principles and intelligent technologies, aligning with the core themes of both the conference and this journal.
Topics of interest for this Special Issue include, but are not limited to, those highlighted in the conference tracks:
· Green Manufacturing: Energy-efficient processes, life cycle assessment, circular economy strategies, sustainable materials, and green supply chains.
· Additive Manufacturing (3D/4D Printing): Sustainable printing technologies, process optimization, lightweight design, and novel materials or methods.
· Intelligent Manufacturing: Applications of AI and machine learning, digital twins and cyber-physical systems (CPS), robotics and autonomous systems, predictive maintenance, and smart factory architectures for Industry 4.0/5.0.
· Mechanical Engineering & Design: Sustainable design approaches, system optimization, dynamics and control, thermal/fluid analysis, and reliability engineering for manufacturing.
We warmly welcome GIM 2026 participants and all researchers working at the intersection of green and intelligent manufacturing to contribute to this collection. Through this Special Issue, we aim to create a lasting resource that advances both academic knowledge and industrial practice toward a more sustainable and intelligent future.
Prof. Dr. Ying Liu
Guest Editor
