A review of in-situ monitoring and process control system in metal-based laser additive manufacturing

Y Cai, J Xiong, H Chen, G Zhang - Journal of Manufacturing Systems, 2023 - Elsevier
Metal-based laser additive manufacturing (MLAM) is receiving significant attention in
industrial fields due to its capacity to manufacture complex and high-performance metal …

[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review

L Jin, X Zhai, K Wang, K Zhang, D Wu, A Nazir, J Jiang… - Materials & Design, 2024 - Elsevier
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

An effective MID-based visual defect detection method for specular car body surface

Y He, B Wu, J Mao, W Jiang, J Fu, S Hu - Journal of Manufacturing Systems, 2024 - Elsevier
The quality control of car body surfaces is one of the most important tasks in automotive
manufacturing, which can directly affect the appearance of cars and purchasing experience …

Deep pattern matching for energy consumption prediction of complex structures in ecological additive manufacturing

K Wang, Y Zhang, Y Song, J Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
We propose a novel and effective deep learning method, called deep pattern matching, for
predicting the energy consumption of complex structures, which helps designers to develop …

Welding defect detection based on phased array images and two-stage segmentation strategy

Y Chen, D He, S He, Z Jin, J Miao, S Shan… - Advanced Engineering …, 2024 - Elsevier
The rail transit vehicle body is composed of numerous welded structures, and to prevent
failures during operation, it is essential that each weld undergoes strict and accurate quality …

AEKD: Unsupervised auto-encoder knowledge distillation for industrial anomaly detection

Q Wu, H Li, C Tian, L Wen, X Li - Journal of Manufacturing Systems, 2024 - Elsevier
Abstract Unsupervised Anomaly Detection (UAD) has achieved promising results in
industrial Surface Defect Detection. Knowledge-Distillation (KD) based UAD became a …

A fault diagnosis method for few-shot industrial processes based on semantic segmentation and hybrid domain transfer learning

Y Tian, Y Wang, X Peng, W Zhang - Applied Intelligence, 2023 - Springer
Fault diagnosis of industrial processes plays an important role in avoiding heavy losses and
ensuring production safety. Complex industrial processes often have many working …

Economically evaluating energy efficiency performance in fused filament fabrication using a multi-scale hierarchical transformer

K Wang, J Xu, S Zhang, J Tan - The International Journal of Advanced …, 2023 - Springer
In recent years, fused filament fabrication (FFF) has become the most popular additive
manufacturing (AM) process due to its low cost and relative simplicity, which incorporates a …

Deep learning-based image segmentation for defect detection in additive manufacturing: An overview

S Deshpande, V Venugopal, M Kumar… - The International Journal …, 2024 - Springer
Additive manufacturing (AM) applications are rapidly expanding across multiple domains
and are not limited to prototyping purposes. However, achieving flawless parts in medical …

Monitoring of extrusion filament state for fused filament fabrication: A super-resolution image monitoring approach based on degradation pattern learning

H Li, Z Yu, F Li, Z Yang, E Yu, J Tang, Q Kong - Journal of Manufacturing …, 2024 - Elsevier
Extrusion filament is the fundamental unit of the fused filament fabrication process (FFF). Its
state stability directly affects the product quality. Therefore, a reliable method is required to …