Real-Time Detection in Additive Manufacturing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Additive Manufacturing Technologies".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 754
Special Issue Editors
Interests: additive manufacturing; predictive modeling; in situ monitoring; real-time control; data management; data registration and fusion
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Interests: additive manufacturing; advanced manufacturing; multiscale modeling and simulations of advanced engineering materials and structures; engineering numerical methods and their applications; digital material representation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue focuses on advancements in real-time detection systems within additive manufacturing (AM), offering an in-depth exploration of the tools and technologies necessary to drive this field forward. As AM evolves, real-time detection is becoming increasingly critical for improving process efficiency, product quality, and reducing costs. However, its application remains limited due to challenges such as sensor implementation, data transfer and storage, computational costs, and accuracy. One of the primary barriers is the lack of reliable, real-time data from sensors, which constrains the ability to monitor and analyze processes effectively. Additionally, the large volume of data generated during AM processes presents new challenges in processing and analysis.
Overcoming these challenges is essential to advancing AM, and this Special Issue seeks contributions that address these issues. Topics include real-time sensor implementation, in situ monitoring techniques, real-time data management, anomaly detection, predictive modeling, design rules, measurement techniques, metrology, and uncertainty quantification. Review papers and case studies that explore solutions to these critical problems are also encouraged, as they will help drive AM toward greater adoption and capability in real-time process detection.
Dr. Zhuo Yang
Prof. Dr. Richard (Chunhui) Yang
Guest Editors
Manuscript Submission Information
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Keywords
- real-time monitoring
- anormaly detection
- in situ data
- process control
- sensors
- modeling
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