Additively manufactured materials and structures: A state-of-the-art review on their mechanical characteristics and energy absorption

Y Wu, J Fang, C Wu, C Li, G Sun, Q Li - International Journal of Mechanical …, 2023 - Elsevier
Lightweight materials and structures have been extensively studied for a wide range of
applications in design and manufacturing of more environment-friendly and more …

[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 …

Machine learning in additive manufacturing: State-of-the-art and perspectives

C Wang, XP Tan, SB Tor, CS Lim - Additive Manufacturing, 2020 - Elsevier
Additive manufacturing (AM) has emerged as a disruptive digital manufacturing technology.
However, its broad adoption in industry is still hindered by high entry barriers of design for …

Metallurgy, mechanistic models and machine learning in metal printing

T DebRoy, T Mukherjee, HL Wei, JW Elmer… - Nature Reviews …, 2021 - nature.com
Additive manufacturing enables the printing of metallic parts, such as customized implants
for patients, durable single-crystal parts for use in harsh environments, and the printing of …

Towards the next generation of machine learning models in additive manufacturing: A review of process dependent material evolution

M Parsazadeh, S Sharma, N Dahotre - Progress in Materials Science, 2023 - Elsevier
Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …

[HTML][HTML] Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

S Kumar, T Gopi, N Harikeerthana, MK Gupta… - Journal of Intelligent …, 2023 - Springer
For several industries, the traditional manufacturing processes are time-consuming and
uneconomical due to the absence of the right tool to produce the products. In a couple of …

Machine learning in additive manufacturing: a review

L Meng, B McWilliams, W Jarosinski, HY Park, YG Jung… - Jom, 2020 - Springer
In this review article, the latest applications of machine learning (ML) in the additive
manufacturing (AM) field are reviewed. These applications, such as parameter optimization …

[HTML][HTML] Machine learning in predicting mechanical behavior of additively manufactured parts

S Nasiri, MR Khosravani - Journal of materials research and technology, 2021 - Elsevier
Although applications of additive manufacturing (AM) have been significantly increased in
recent years, its broad application in several industries is still under progress. AM also …

Deep materials informatics: Applications of deep learning in materials science

A Agrawal, A Choudhary - Mrs Communications, 2019 - cambridge.org
The growing application of data-driven analytics in materials science has led to the rise of
materials informatics. Within the arena of data analytics, deep learning has emerged as a …

A digital twin hierarchy for metal additive manufacturing

A Phua, CHJ Davies, GW Delaney - Computers in Industry, 2022 - Elsevier
Digital twins present a conceptual framework for product life-cycle monitoring and control
using a simulated replica of the physical system. Since their emergence, they have garnered …