3 papers
cs.LG2025
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…
cs.LG2024
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…
cs.LG2024
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…