Machine learning in additive manufacturing: State-of-the-art and perspectives
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 …
However, its broad adoption in industry is still hindered by high entry barriers of design for …
About metastable cellular structure in additively manufactured austenitic stainless steels
D Kong, C Dong, S Wei, X Ni, L Zhang, R Li… - Additive …, 2021 - Elsevier
The quick-emerging paradigm of additive manufacturing technology has revealed salient
advantages in enabling the tailored-design of structural components with more exceptional …
advantages in enabling the tailored-design of structural components with more exceptional …
Control of grain structure, phases, and defects in additive manufacturing of high-performance metallic components
T Mukherjee, JW Elmer, HL Wei, TJ Lienert… - Progress in Materials …, 2023 - Elsevier
The properties and serviceability of 3D-printed metal parts depend on a variety of attributes.
These include the chemical composition, phases, morphology, spatial distributions of grain …
These include the chemical composition, phases, morphology, spatial distributions of grain …
Towards the next generation of machine learning models in additive manufacturing: A review of process dependent material evolution
Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …
wide range of applications. Despite considerable advancements in additive manufacturing …
Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …
for quality prediction and process optimization of metal additive manufacturing (AM) …
[HTML][HTML] Powders for powder bed fusion: a review
S Vock, B Klöden, A Kirchner, T Weißgärber… - Progress in Additive …, 2019 - Springer
The quality of powder used in powder bed-based additive manufacturing plays a key role
concerning process performance and end part properties. Even though this is a generally …
concerning process performance and end part properties. Even though this is a generally …
[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 …
recent years, its broad application in several industries is still under progress. AM also …
A review of machine learning applications in additive manufacturing
SS Razvi, S Feng, A Narayanan… - International …, 2019 - asmedigitalcollection.asme.org
Variability in product quality continues to pose a major barrier to the widespread application
of additive manufacturing (AM) processes in production environment. Towards addressing …
of additive manufacturing (AM) processes in production environment. Towards addressing …
A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing
Laser beam powder bed fusion (LB-PBF) is a widely-used metal additive manufacturing
process due to its high potential for fabrication flexibility and quality. Its process and …
process due to its high potential for fabrication flexibility and quality. Its process and …
Process modeling in laser powder bed fusion towards defect detection and quality control via machine learning: The state-of-the-art and research challenges
In recent years, machine learning (ML) techniques have been extensively investigated to
strengthen the understanding of the complex process dynamics underlying metal additive …
strengthen the understanding of the complex process dynamics underlying metal additive …