4 papers · 1 filter
An Unsupervised Time Series Anomaly Detection Approach for Efficient Online Process Monitoring of Additive Manufacturing
Frida Cantu, Salomon Ibarra, Arturo Gonzales +3
Online sensing plays an important role in advancing modern manufacturing. The real-time sensor signals, which can be stored as high-resolution time series data, contain rich inform…
ADs: Active Data-sharing for Data Quality Assurance in Advanced Manufacturing Systems
Yue Zhao, Yuxuan Li, Chenang Liu +1
Machine learning (ML) methods are widely used in industrial applications, which usually require a large amount of training data. However, data collection needs extensive time costs…
Advancing Additive Manufacturing through Deep Learning: A Comprehensive Review of Current Progress and Future Challenges
Amirul Islam Saimon, Emmanuel Yangue, Xiaowei Yue +2
This paper presents the first comprehensive literature review of deep learning (DL) applications in additive manufacturing (AM). It addresses the need for a thorough analysis in th…
Pseudo Replay-based Class Continual Learning for Online New Category Anomaly Detection in Advanced Manufacturing
Yuxuan Li, Tianxin Xie, Chenang Liu +1
The incorporation of advanced sensors and machine learning techniques has enabled modern manufacturing enterprises to perform data-driven classification-based anomaly detection bas…