Machine Tool Component Health Identification with Unsupervised Learning

Machine Tool Component Health Identification with Unsupervised Learning

Unforeseen machine tool component failures cause considerable losses. This study presents a new approach to unsupervised machine component condition identification. It uses test cycle data of machine components in healthy and various faulty conditions for modelling. The novelty in the approach consi...

Full description

Bibliographic Details
Main Authors: Thomas Gittler, Stephan Scholze, Alisa Rupenyan, Konrad Wegener
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Journal of Manufacturing and Materials Processing
Subjects:
condition monitoring
machine learning
prognostics and health monitoring
unsupervised learning
machine tools
manufacturing
Online Access:https://www.mdpi.com/2504-4494/4/3/86

Internet

https://www.mdpi.com/2504-4494/4/3/86

Similar Items