Refine
Year of publication
- 2023 (1)
Institute
Has Fulltext
- no (1)
Language
- English (1)
Document Type
Keywords
- Neural networks (1) (remove)
Zugriffsart
- campus (1)
Is part of the Bibliography
- yes (1)
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.
