Isolation forests and deep autoencoders for industrial screw tightening anomaly detection
Within the context of Industry 4.0, quality assessment procedures 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 key industrial task. Since...
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| Outros Autores: | , , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2022
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| Assuntos: | |
| Texto completo: | https://hdl.handle.net/1822/79806 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/79806 |