[HTML][HTML] Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing
In metal additive manufacturing (AM), the material microstructure and part geometry are
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
Real-time in-process control methods of process parameters for additive manufacturing
Additive Manufacturing, also known as 3D printing, fabricates objects in a layer-by-layer
manner. In recent years, extensive efforts have been made to evolve 3D printing …
manner. In recent years, extensive efforts have been made to evolve 3D printing …
Unsupervised fault detection in automated sequential manufacturing processes through image analysis and convolutional LSTM-based next visual status prediction
NH Yu, S Baek - The International Journal of Advanced Manufacturing …, 2024 - Springer
With the advancement of information and communication technology, the integration of
smart systems into discrete sequential processes has been realized in manufacturing …
smart systems into discrete sequential processes has been realized in manufacturing …
Additive Manufacturing Processes: A Systematic Literature Review
Additive Manufacturing (AM) has made a giant leap across numerous fields and industries,
enabling the manufacturing of complex components in layer-by-layer form customized to the …
enabling the manufacturing of complex components in layer-by-layer form customized to the …
An Analysis of Partition Tree Clustering Techniques for Automated Classification of Hyper Spectral Scans
AS Priya, KS Selvan, P Jeevananthan… - … on Power Energy …, 2023 - ieeexplore.ieee.org
This paper analyzes partition tree clustering strategies for a computerized class of
hyperspectral scans. Partition tree clustering (percent) strategies are unsupervised getting-to …
hyperspectral scans. Partition tree clustering (percent) strategies are unsupervised getting-to …
[PDF][PDF] Additive manufacturing modification by artificial intelligent, machine learning and deep learning, A
The manufacturing sector has undergone a transformation due to additive manufacturing
(AM), which makes it possible to create intricate, personalized items with little wastage of …
(AM), which makes it possible to create intricate, personalized items with little wastage of …
Multi-Modal Spatio-Temporal Learning for Defect Recognition of Substation Equipment Using Tri-Modality Videos
Y Yao, Z Du, X Wang, Q Wang - Available at SSRN 4805668 - papers.ssrn.com
The utilization of infrared, visible light, and ultraviolet in recognizing defects in electrical
equipment is already well-established, mostly focusing on static measurements and lacking …
equipment is already well-established, mostly focusing on static measurements and lacking …