Autoencoders for learning latent information of cutting tool health
Published online on May 25, 2026
Abstract
Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
This article presents an unsupervised method for monitoring the health of cutting tools in precision machining processes. The method is developed and validated using the IEEE PHM 2010 data, which comprises three sets of cutting tool run-to-failure tests. ...
This article presents an unsupervised method for monitoring the health of cutting tools in precision machining processes. The method is developed and validated using the IEEE PHM 2010 data, which comprises three sets of cutting tool run-to-failure tests. ...