Intelligent and Sustainable Welding: State of the Art, Challenges and Prospects
A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Welding and Joining".
Deadline for manuscript submissions: 15 July 2025 | Viewed by 631
Special Issue Editors
Interests: arc welding & additive manufacturing; robotic & intelligent welding; welding process control and automation
Interests: laser welding; laser welding of dissimilar materials; numerical simulation of welding process; welding defect detection
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Intelligent and sustainable welding technology is at the forefront of the current welding field. It integrates modern control theory, artificial intelligence, material science, and environmental science to improve the efficiency, accuracy, and environmental sustainability of the welding process, particularly in metal fabrication. The ability to optimize welding processes for different metals, such as high-strength steels, aluminum alloys, and titanium, is key to advancing industries like the aerospace, automotive, and manufacturing industries.
Intelligent welding incorporates advanced technologies such as robotics, artificial intelligence, and machine learning algorithms to enhance the precision and quality of metal welding. By considering the unique properties of various metals, such as their thermal conductivity and mechanical strength, intelligent welding systems can adapt in real time to ensure optimal results. Sustainability is also a crucial aspect of intelligent welding. It aims to minimize the environmental impact of welding operations by reducing energy consumption, waste generation, and emissions, particularly when working with energy-intensive metals like steel and aluminum.
This Special Issue aims to collate recent research studies on intelligent welding systems (such as power supplies, robotic systems, and control systems), multi-information fusion sensing technologies (including visual, acoustic, electrical, spectral, optical, infrared, etc.), advanced welding quality control algorithms (weld seam tracking, in-process welding quality monitoring, welding defect detection, etc.), teaching-free programming technologies (offline programming, adaptive path planning and tracking, the online adjustment of welding parameters, etc.), welding IoT, green welding methods, and welding consumables, with a focus on metals.
We also welcome reviews and papers on new processing technologies used to manufacture and join metallic materials, including steels, aluminum alloys, titanium alloys, and other advanced metals.
Dr. Qiang Wang
Dr. Yanxi Zhang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- intelligent robotic welding
- artificial intelligence
- multi-information fusion
- weld seam tracking
- defect detection
- path planning
- green welding
- welding Internet of Things
- metal joining
- advanced welding techniques
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