Smart Manufacturing and Autonomous Systems for Sustainable Development
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 4032
Special Issue Editors
Interests: robotics and autonomous systems; artificial intelligence and machine learning; control systems engineering; constrained optimistion; estimation and control
Interests: smart and sustainable manufacturing; life cycle engineering and optimisation; digital product development and manufacturing; cost modelling & engineering economic analysis; circular economy
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligent for condition monitoring; fault diagnosis; prognostic health management; especially for deep learning; transfer learning; few-shot learning method and their application for the large industrial environment; reinforcement learning for control and its applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Technologies play a vital role in meeting the 2030 Agenda for Sustainable Development. Among these technologies, smart manufacturing and autonomous systems, as well as other emerging digital technologies, are being put into practice to improve energy efficiency, reduce carbon emissions, create a circular economy and conduct environmental conservation, in addition to other activities. Their impact on sustainability is yet to be widely publicized, which is important for the promotion of further research in this field.
The aim of this Special Issue is to publish the latest developments in the application of digital technologies and autonomous systems to address sustainable development issues such as energy efficiency, circular economy, and environmental conservation. Some related fields include, but are not limited to, the following:
- Smart manufacturing for energy efficiency;
- Remanufacturing for circular economy;
- Robotics and autonomous systems for environmental conservation;
- Artificial intelligence and machine learning for situation awareness;
- Industry 4.0;
- Digital technologies for sustainability.
We look forward to receiving your contributions.
Dr. Jian Wan
Prof. Dr. Yuchun Xu
Dr. Ming Zhang
Guest Editors
Manuscript Submission Information
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Keywords
- sustainability
- smart manufacturing
- autonomous systems
- machine learning
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