A comparison of anomaly detection methods for industrial screw tightening

Within the context of Industry 4.0, quality assessment pro- cedures using data-driven techniques are becoming more critical due to the generation of massive amounts of production data. In this paper, we address the detection of abnormal screw tightening processes, which is a relevant industrial task...

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Bibliographic Details
Main Author: Ribeiro, Diogo Aires Gonçalves (author)
Other Authors: Matos, Luís Miguel (author), Cortez, Paulo (author), Moreira, Guilherme (author), Pilastri, André Luiz (author)
Format: conferencePaper
Language:eng
Published: 2021
Subjects:
Autoencoder
Deep Learning
Industry 4.0
Isolation Forest
One-class classification
Random Forest
Unsupervised learning
Ciências Naturais::Ciências da Computação e da Informação
Science & Technology
Indústria, inovação e infraestruturas
Online Access:http://hdl.handle.net/1822/74067
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/74067

Internet

http://hdl.handle.net/1822/74067

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