Special Issue

Topic: Convenient, Reliable, Green Innovation of Assembly Technology in the Age of Artificial Intelligence

A Special Issue of Green Manufacturing Open

ISSN 2835-7590 (Online)

Submission deadline: 31 Jul 2025

Guest Editor(s)

Prof. Dr. Xiaokai Mu
School of Mechanical Engineering, Dalian University of Technology, Dalian, Liaoning, China. 
Prof. Dr. Hao Gong
Beijing Institute of Technology, School of Mechanical Engineering, Beijing, China.

Guest Editor Assistant(s)

Dr. Qingyuan Lin
State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Special Issue Introduction

Since the 21st century, the relationship between social development and environmental change has become an important topic of common reflection for humankind. The environmental impact of the manufacturing industry has aroused strong concern. In response, the environment-friendly manufacturing principle urges enterprises to mitigate environmental pollution and resource waste caused by the manufacturing process, promoting a shift towards green and sustainable manufacturing. Assembly is the final part of the equipment manufacturing process. For large-scale equipment such as aircraft and ships, the assembly process can account for over half of the entire production cycle. With the requirements of green manufacturing, assembly technologies are undergoing transformative innovation. The emergence and rapid development of artificial intelligence (AI) provides a strong basic support and means of realization for the change of assembly technology.

The Special Issue, "Convenient, Reliable, Green Innovation of Assembly Technology in the Age of Artificial Intelligence", explores the innovation of assembly technology brought about by AI in the manufacturing industry. The featured papers cover a range of topics, including but not limited to assembly process design methods using machine learning, virtual assembly experiments using digital twins, and AI-driven monitoring and optimization of assembly results. Together, these contributions highlight innovations that make assembly more efficient, reliable, and environmentally friendly. Overall, this Special Issue provides valuable insights and practical guidance to researchers, practitioners, and decision-makers seeking to realize cost reduction, reliability enhancement, and green transformation of assembly technologies.

Keywords

Assembly process design, assembly quality control, system reliability, non-destructive testing, digital twin, virtual reality interaction

Submission Deadline

31 Jul 2025

Submission Information

Ten articles in the Special Issue are exempt from article processing charges.
For Author Instructions, please refer to https://www.oaepublish.com/gmo/author_instructions
For Online Submission, please login at https://oaemesas.com/login?JournalId=gmo&SpecialIssueId=GMO240923
Submission Deadline: 31 Jul 2025
Contacts: Lily Ji, Assistant Editor, gmo@oaemesas.com

Published Articles

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Green Manufacturing Open
ISSN 2835-7590 (Online)
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