Deep learning based real-time and in-situ monitoring of weld penetration: Where we are and what are needed revolutionary solutions?

R Yu, Y Cao, H Chen, Q Ye, YM Zhang - Journal of Manufacturing …, 2023 - Elsevier
Abstract Welding Procedure Designed assures the desired weld penetration be produced
under nominal welding conditions. When conditions deviate from the nominal, penetration …

A critical review on applications of artificial intelligence in manufacturing

O Mypati, A Mukherjee, D Mishra, SK Pal… - Artificial Intelligence …, 2023 - Springer
The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI),
and machine learning (ML) concepts into manufacturing. There is an immediate need to …

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 …

In situ detection of welding defects: A review

AS Madhvacharyula, AVS Pavan, S Gorthi, S Chitral… - Welding in the …, 2022 - Springer
Weld defect detection is a crucial aspect for improving the productivity and quality of the
welding process. Several non-destructive methods exist for the identification of defects post …

Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data

M Garouani, A Ahmad, M Bouneffa, M Hamlich… - Journal of Big Data, 2022 - Springer
Advanced analytics are fundamental to transform large manufacturing data into resourceful
knowledge for various purposes. In its very nature, such “industrial big data” can relay its …

Machine learning for multi-dimensional optimisation and predictive visualisation of laser machining

MDT McDonnell, D Arnaldo, E Pelletier… - Journal of Intelligent …, 2021 - Springer
Interactions between light and matter during short-pulse laser materials processing are
highly nonlinear, and hence acutely sensitive to laser parameters such as the pulse energy …

Recent developments in computer vision and artificial intelligence aided intelligent robotic welding applications

B Eren, MH Demir, S Mistikoglu - The International Journal of Advanced …, 2023 - Springer
The welding process, which is an indispensable part of the manufacturing industry, has
been in demand for years and continues to attract the attention of researchers. With the …

[HTML][HTML] Inference of highly time-resolved melt pool visual characteristics and spatially-dependent lack-of-fusion defects in laser powder bed fusion using acoustic and …

H Liu, C Gobert, K Ferguson, B Abranovic, H Chen… - Additive …, 2024 - Elsevier
With a growing demand for high-quality fabrication, the interest in real-time process and
defect monitoring of laser powder bed fusion (LPBF) has increased, leading manufacturers …

Ensemble-based deep learning model for welding defect detection and classification

V Vasan, NV Sridharan, RJ Balasundaram… - … Applications of Artificial …, 2024 - Elsevier
This study introduces an ensemble-based deep learning approach for monitoring and
detecting submerged arc weld defects in weld beads and adjacent zones during Non …

Inline defective laser weld identification by processing thermal image sequences with machine and deep learning techniques

D Buongiorno, M Prunella, S Grossi, SM Hussain… - Applied Sciences, 2022 - mdpi.com
The non-destructive testing methods offer great benefit in detecting and classifying the weld
defects. Among these, infrared (IR) thermography stands out in the inspection …