In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: a critical review

L Chen, G Bi, X Yao, J Su, C Tan, W Feng… - Journal of Manufacturing …, 2024 - Elsevier
Abstract Laser Additive Manufacturing (LAM) presents unparalleled opportunities for
fabricating complex, high-performance structures and components with unique material …

A Review of In Situ Defect Detection and Monitoring Technologies in Selective Laser Melting

X Peng, L Kong, H An, G Dong - 3D printing and additive …, 2023 - liebertpub.com
The additive manufacturing (AM) technique has received considerable industrial attention,
as it is capable of producing complex functional parts in the aerospace and defense …

Real-time identification of molten pool and keyhole using a deep learning-based semantic segmentation approach in penetration status monitoring

W Cai, P Jiang, L Shu, S Geng, Q Zhou - Journal of Manufacturing …, 2022 - Elsevier
Due to the complexity and diversity of disturbances in the monitoring signals, it is still a
challenge to accurately real-time monitor penetration statues in laser welding …

Online defect detection method and system based on similarity of the temperature field in the melt pool

W Feng, Z Mao, Y Yang, H Ma, K Zhao, C Qi, C Hao… - Additive …, 2022 - Elsevier
Additive manufacturing (AM) is an important production trend. Meanwhile, the lack of an
online defect detection technology is a key problem that limits the further development of …

Real-time laser keyhole welding penetration state monitoring based on adaptive fusion images using convolutional neural networks

W Cai, P Jiang, LS Shu, SN Geng, Q Zhou - Journal of Intelligent …, 2023 - Springer
In laser keyhole welding process, the penetration state is an important index to evaluate the
quality of weld seam. In this paper, an innovative deep learning-based monitoring system …

Two-stage fusion framework driven by domain knowledge for penetration prediction of laser welding

J Li, Y Zhang, Y Xu, C Chen - Optics & Laser Technology, 2024 - Elsevier
To solve the problem of industrial application difficulties caused by insufficient depth
exploration and poor interpretability of the pure data drive neural network. A two-stage …

[HTML][HTML] Welding Defect Monitoring Based on Multi-Scale Feature Fusion of Molten Pool Videos

C Shi, L Wang, C Zhu, T Han, X Zhang, D Wang… - Sensors, 2024 - mdpi.com
Real-time quality monitoring through molten pool images is a critical focus in researching
high-quality, intelligent automated welding. However, challenges such as the dynamic …

Prediction of Coefficient of Friction and Wear Rate of Stellite 6 Coatings Manufactured by LMD Using Machine Learning

RA Cázares-Vázquez, V Humarán-Sarmiento… - … Conference on Artificial …, 2023 - Springer
Abstract Laser Metal Deposition (LMD) is a Direct Energy Deposition (DED) technique,
which uses a laser source to melt the input material layer by layer, creating the desired …

A closed-loop intelligent adjustment of process parameters in precise and micro hot-embossing using an in-process optic detection

K Lu, J **e, R Wang, L Li, W Li, Y Jiang - Journal of Intelligent …, 2022 - Springer
In rapid hot-embossing of microarray products, sensors accuracy drifts, mechanical wears
and environmental changes produce the nonlinear relationship between micro-forming …

Multi-sensor monitoring for in-situ defect detection and quality assurance in laser-directed energy deposition

L Chen - 2024 - dr.ntu.edu.sg
Additive manufacturing (AM), specifically laser-directed energy deposition (LDED), has
evolved rapidly as a pivotal technology in the realm of Industry 4.0, gaining significant …