Machine Learning in Metal Additive Manufacturing
A special issue of Metals (ISSN 2075-4701).
Deadline for manuscript submissions: 30 June 2025 | Viewed by 622
Special Issue Editors
Interests: additive manufacturing; multiphysics modeling; machine learning; digital twins; real-time control of processes
Special Issues, Collections and Topics in MDPI journals
Interests: computational materials processing; numerical heat and mass transfer; welding and joining; 3D printing/additive manufacturing; optimization
Interests: materials science and engineering; mechanical and manufacturing engineering; interface of biology and engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are excited to announce a call for research articles for a Special Issue focused on “Machine Learning in Metal Additive Manufacturing”. As the field of metal additive manufacturing (AM) continues to evolve, the integration of machine learning (ML) techniques is proving to be transformative, offering unprecedented opportunities to optimize processes, enable in situ quality audits and adaptive controls, improve part quality, and predict outcomes (e.g., microstructures, defects formation, mechanical properties) with increased precision, discover optimal material compositions for printing, optimize part designs, to name just a few categories.
This Special Issue seeks to provide a comprehensive overview of the current state-of-the-art, offering insights into how the power of ML can be harnessed to push the boundaries of metal AM.
We invite original research articles, reviews, and case studies that showcase the application of ML in various aspects of metal AM. Submissions that explore novel ML algorithms, data-driven approaches, and hybrid modeling techniques to improve the efficiency, reliability, and scalability of metal AM processes are also encouraged.
Please submit your manuscripts by 30th June 2025 through the journal’s online submission system. All submissions will undergo a rigorous peer-review process to ensure the highest quality of published work. We look forward to receiving your valuable contributions to this Special Issue, which will serve as a vital resource for researchers and practitioners aiming to leverage ML in metal AM.
Dr. Dayalan Gunasegaram
Prof. Dr. T. DebRoy
Prof. Dr. Paulo J. Bártolo
Dr. Yang Du
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
- additive manufacturing
- machine learning
- optimization
- monitoring
- control
- microstructure prediction
- mechanical property prediction
- defect detection
- anomaly detection
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.
