[HTML][HTML] Research and application of machine learning for additive manufacturing

J Qin, F Hu, Y Liu, P Witherell, CCL Wang… - Additive …, 2022 - Elsevier
Additive manufacturing (AM) is poised to bring a revolution due to its unique production
paradigm. It offers the prospect of mass customization, flexible production, on-demand and …

Defect sensitivity and fatigue design: Deterministic and probabilistic aspects in AM metallic materials

X Niu, C He, SP Zhu, P Foti, F Berto, L Wang… - Progress in Materials …, 2024 - Elsevier
Fatigue performance in both traditional and additively manufactured materials is severely
affected by the presence of defects, which deserve special attention to ensure the in-service …

Machine learning model towards evaluating data gathering methods in manufacturing and mechanical engineering

M Amini, K Sharifani, A Rahmani - International Journal of Applied …, 2023 - papers.ssrn.com
Abstract Supervised Machine Learning (ML) models require extensive training data to
properly approximate the behavior of complex mechanical processes and systems. Real …

[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review

L **, X Zhai, K Wang, K Zhang, D Wu, A Nazir, J Jiang… - Materials & Design, 2024 - Elsevier
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

Machine learning process evaluating damage classification of composites

M Amini, A Rahmani - International Journal of Science and …, 2023 - papers.ssrn.com
Composite materials have tremendous and ever-increasing applications in complex
engineering systems; thus, it is important to develop non-destructive and efficient condition …

In-situ monitoring of sub-surface and internal defects in additive manufacturing: A review

Y AbouelNour, N Gupta - Materials & Design, 2022 - Elsevier
Abstract Additive Manufacturing (AM), or 3D printing, processes depend on a user-defined
set of optimized process parameters to create a component. Monitoring and control of AM …

Recent applications of machine learning in alloy design: A review

M Hu, Q Tan, R Knibbe, M Xu, B Jiang, S Wang… - Materials Science and …, 2023 - Elsevier
The history of machine learning (ML) can be traced back to the 1950 s, and its application in
alloy design has recently begun to flourish and expand rapidly. The driving force behind this …

When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development

C Liu, W Tian, C Kan - Journal of Manufacturing Systems, 2022 - Elsevier
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …

Optimization with artificial intelligence in additive manufacturing: a systematic review

F Ciccone, A Bacciaglia, A Ceruti - Journal of the Brazilian Society of …, 2023 - Springer
In situations requiring high levels of customization and limited production volumes, additive
manufacturing (AM) is a frequently utilized technique with several benefits. To properly …

A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management

Y Zhang, M Safdar, J **e, J Li, M Sage… - Journal of Intelligent …, 2023 - Springer
Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the
industry. With more and more design, process, structure, and property data collected …