Enhanced classification of hydraulic testing of directional control valves with synthetic data generation

Production environments bring inherent system challenges that are reflected in the high-dimensional production data. The data is often nonstationary, is not available in sufficient size and quality, and is class imbalanced due to the predominance of good parts. Data-driven manufacturing analytics re...

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Veröffentlicht in:	Production engineering (Berlin, Germany) Jg. 17; H. 5; S. 669 - 678
Hauptverfasser:	Neunzig, Christian, Möllensiep, Dennis, Hartmann, Melanie, Kuhlenkötter, Bernd, Möller, Matthias, Schulz, Jürgen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023 Springer Nature B.V
Schlagworte:	Computer Assisted Approaches in Production Engineering Directional control Engineering Generative adversarial networks Industrial and Production Engineering Industrial applications Machine learning Manufacturing Mathematical analysis Prediction models Production Synthetic data Conditional tabular generative adversarial networks Tabular variational autoencoder Predictive quality Semi-supervised learning Quality control Machine learning
ISSN:	0944-6524, 1863-7353
Online-Zugang:	Volltext
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