Automatic Anomaly Detection on In-Production Manufacturing Machines Using Statistical Learning Methods

Anomaly detection is becoming increasingly important to enhance reliability and resiliency in the Industry 4.0 framework. In this work, we investigate different methods for anomaly detection on in-production manufacturing machines taking into account their variability, both in operation and in wear...

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Detalles Bibliográficos
Autores principales: Pittino, Federico, Puggl, Michael, Moldaschl, Thomas, Hirschl, Christina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219248/
https://www.ncbi.nlm.nih.gov/pubmed/32326029
http://dx.doi.org/10.3390/s20082344

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219248/
https://www.ncbi.nlm.nih.gov/pubmed/32326029
http://dx.doi.org/10.3390/s20082344

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