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Author

  • Arndt, Tobias (1)
  • Conzen, Max (1)
  • Elsen, Ingo (1)
  • Ferrein, Alexander (1)
  • Galla, Oskar (1)
  • Köse, Hakan (1)
  • Schiffer, Stefan (1)
  • Tschesche, Matteo (1)

Year of publication

  • 2023 (1)

Institute

  • Fachbereich Elektrotechnik und Informationstechnik (1)

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  • English (1)

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  • Conference Proceeding (1)

Keywords

  • Anomaly detection (1)
  • Datasets (1)
  • Neural networks (1)
  • Process optimization (1)
  • Quality control (1)

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Anomaly detection in the metal-textile industry for the reduction of the cognitive load of quality control workers (2023)
Arndt, Tobias ; Conzen, Max ; Elsen, Ingo ; Ferrein, Alexander ; Galla, Oskar ; Köse, Hakan ; Schiffer, Stefan ; Tschesche, Matteo
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
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