Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement

Karin Hartl; Marcel Sorger; Helmut Weiß; Martin Stockinger

doi:10.1016/j.jmapro.2023.09.058

Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement

Karin Hartl, Marcel Sorger, Helmut Weiß, Martin Stockinger

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Begutachtung

Originalsprache	Englisch
Seiten (von - bis)	158-177
Seitenumfang	20
Fachzeitschrift	Journal of manufacturing processes
Jahrgang	106.2023
Ausgabenummer	24 November
DOIs	https://doi.org/10.1016/j.jmapro.2023.09.058
Publikationsstatus	Elektronische Veröffentlichung vor Drucklegung. - 5 Okt. 2023

Zugriff auf Dokument

10.1016/j.jmapro.2023.09.058

Dieses zitieren

Hartl, K., Sorger, M., Weiß, H., & Stockinger, M. (2023). Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement. Journal of manufacturing processes, 106.2023(24 November), 158-177. Vorzeitige Online-Publikation. https://doi.org/10.1016/j.jmapro.2023.09.058

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Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement. / Hartl, Karin; Sorger, Marcel; Weiß, Helmut et al.
in: Journal of manufacturing processes, Jahrgang 106.2023, Nr. 24 November, 05.10.2023, S. 158-177.

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Begutachtung

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AU - Weiß, Helmut

AU - Stockinger, Martin

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