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 …

Top ten intelligent algorithms towards smart manufacturing

M Zhang, F Tao, Y Zuo, F Xiang, L Wang… - Journal of Manufacturing …, 2023 - Elsevier
Intelligent algorithms can empower the development of smart manufacturing, since they can
provide optimal solutions for detection, analysis, prediction and optimization. In recent ten …

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Z Ren, L Gao, SJ Clark, K Fezzaa, P Shevchenko… - Science, 2023 - science.org
Porosity defects are currently a major factor that hinders the widespread adoption of laser-
based metal additive manufacturing technologies. One common porosity occurs when an …

In-situ crack and keyhole pore detection in laser directed energy deposition through acoustic signal and deep learning

L Chen, X Yao, C Tan, W He, J Su, F Weng… - Additive …, 2023 - Elsevier
Cracks and keyhole pores are detrimental defects in alloys produced by laser directed
energy deposition (LDED). Laser-material interaction sound may hold information about …

[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 …

Multisensor fusion-based digital twin for localized quality prediction in robotic laser-directed energy deposition

L Chen, G Bi, X Yao, C Tan, J Su, NPH Ng… - Robotics and Computer …, 2023 - Elsevier
Early detection of defects, such as keyhole pores and cracks is crucial in laser-directed
energy deposition (L-DED) additive manufacturing (AM) to prevent build failures. However …

On the application of in-situ monitoring systems and machine learning algorithms for developing quality assurance platforms in laser powder bed fusion: A review

K Taherkhani, O Ero, F Liravi, S Toorandaz… - Journal of Manufacturing …, 2023 - Elsevier
Laser powder bed fusion (LPBF) is one class of metal additive manufacturing (AM) used to
fabricate high-quality complex-shape components. This technology has significantly …

[HTML][HTML] Key enabling technologies for smart factory in automotive industry: status and applications

J Lee, PC Chua, L Chen, PHN Ng, Y Kim… - International Journal of …, 2023 - ijpem-st.org
In line with the unpredictable variety of demands and acceleration into the electric vehicle
era, automakers have efforted on smart factories utilizing new manufacturing platforms with …

Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing

SS Babu, AHI Mourad, KH Harib… - Virtual and Physical …, 2023 - Taylor & Francis
The application of three-dimensional (3D) printing/Additive Manufacturing (AM) for
developing multi-functional smart/intelligent composite materials is a highly promising area …

[HTML][HTML] Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

V Pandiyan, R Wróbel, C Leinenbach… - Journal of Materials …, 2023 - Elsevier
Abstract Metal-based Laser Powder Bed Fusion (LPBF) has made fabricating intricate
components easier. Yet, assessing part quality is inefficient, relying on costly Computed …