Smart Tool Wear Monitoring of CFRP/CFRP Stack Drilling Using Autoencoders and Memory-Based Neural Networks
Alessandra Caggiano(Fraunhofer Italia Research), Luigi Nele(University of Naples Federico II), Giulio Mattera(University of Naples Federico II)
Cited by 34
Related Papers
Monitoring and control the Wire Arc Additive Manufacturing process using artificial intelligence techniques: a review
|Journal of Intelligent Manufacturing|2023|108
Optimal data-driven control of manufacturing processes using reinforcement learning: an application to wire arc additive manufacturing
|Journal of Intelligent Manufacturing|2024|60
Semi-supervised learning for real-time anomaly detection in pulsed transfer wire arc additive manufacturing
|Journal of Manufacturing Processes|2024|48
Towards the application of machine learning in digital twin technology: a multi-scale review
|Discover Applied Sciences|2024|44
Monitoring the gas metal arc additive manufacturing process using unsupervised machine learning
|Welding in the World|2024|43