State-of-the-art review of machine learning applications in additive manufacturing; from design to manufacturing and property control

GK Sarkon, B Safaei, MS Kenevisi, S Arman… - … Methods in Engineering, 2022 - Springer
In this review, some of the latest applicable methods of machine learning (ML) in additive
manufacturing (AM) have been presented and the classification of the most common ML …

[HTML][HTML] Deep learning-based monitoring of laser powder bed fusion process on variable time-scales using heterogeneous sensing and operando X-ray radiography …

V Pandiyan, G Masinelli, N Claire, T Le-Quang… - Additive …, 2022 - Elsevier
Harnessing the full potential of the metal-based Laser Powder Bed Fusion process (LPBF)
relies heavily on how effectively the overall reliability and stability of the manufactured part …

A convolutional neural network-based multi-sensor fusion approach for in-situ quality monitoring of selective laser melting

J Li, Q Zhou, L Cao, Y Wang, J Hu - Journal of Manufacturing Systems, 2022 - Elsevier
Selective laser melting (SLM) is an emerging and popular metal additive manufacturing
(AM) technique to fabricate advanced metal components with complex geometries …

[HTML][HTML] A novel machine learning-based approach for in-situ surface roughness prediction in laser powder-bed fusion

S Toorandaz, K Taherkhani, F Liravi, E Toyserkani - Additive Manufacturing, 2024 - Elsevier
Controlling and optimizing surface roughness remain a significant challenge in laser powder
bed fusion (LPBF). Surface roughness affects printed part quality, particularly fatigue life …

DLAM: Deep learning based real-time porosity prediction for additive manufacturing using thermal images of the melt pool

S Ho, W Zhang, W Young, M Buchholz… - IEEE …, 2021 - ieeexplore.ieee.org
This paper presents an investigation of the rapid variations in the temperature of metal melt
pool for Additive Manufacturing (AM) processes. The melt pool is created by scanning a high …

Computer vision-aided bioprinting for bone research

C Liu, L Wang, W Lu, J Liu, C Yang, C Fan, Q Li… - Bone Research, 2022 - nature.com
Bioprinting is an emerging additive manufacturing technology that has enormous potential in
bone implantation and repair. The insufficient accuracy of the shape of bioprinted parts is a …

[HTML][HTML] Self-Supervised Bayesian representation learning of acoustic emissions from laser powder bed Fusion process for in-situ monitoring

V Pandiyan, R Wróbel, RA Richter, M Leparoux… - Materials & Design, 2023 - Elsevier
This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-
borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process …

A review on in-situ process sensing and monitoring systems for fusion-based additive manufacturing

T Özel - International Journal of Mechatronics and …, 2023 - inderscienceonline.com
In additive manufacturing (AM), parts suffer from quality variations, defects, intricate surface
topography, and anisotropy in properties that are known to be influenced by factors …

Multi-source information fusion for enhanced in-process quality monitoring of laser powder bed fusion additive manufacturing

T Shen, B Li, J Zhang, F Xuan - Additive Manufacturing, 2024 - Elsevier
Defects such as lack of fusion, porosity, and keyhole generated during the laser powder bed
fusion (L-PBF) additive manufacturing process pose a challenge, with the absence of …