Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement
Research output: Contribution to journal › Article › Research › peer-review
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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, Vol. 106.2023, No. 24 November, 05.10.2023, p. 158-177.
In: Journal of manufacturing processes, Vol. 106.2023, No. 24 November, 05.10.2023, p. 158-177.
Research output: Contribution to journal › Article › Research › peer-review
Harvard
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, vol. 106.2023, no. 24 November, pp. 158-177. https://doi.org/10.1016/j.jmapro.2023.09.058
APA
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. Advance online publication. https://doi.org/10.1016/j.jmapro.2023.09.058
Vancouver
Hartl K, Sorger M, Weiß H, Stockinger M. 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. 2023 Oct 5;106.2023(24 November):158-177. Epub 2023 Oct 5. doi: 10.1016/j.jmapro.2023.09.058
Author
Bibtex - Download
@article{102d082e6acd4787b11bb7da02dbf3e0,
title = "Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement",
author = "Karin Hartl and Marcel Sorger and Helmut Wei{\ss} and Martin Stockinger",
year = "2023",
month = oct,
day = "5",
doi = "10.1016/j.jmapro.2023.09.058",
language = "English",
volume = "106.2023",
pages = "158--177",
journal = "Journal of manufacturing processes",
issn = "0278-6125",
publisher = "Elsevier",
number = "24 November",
}
RIS (suitable for import to EndNote) - Download
TY - JOUR
T1 - Machine learning driven prediction of mechanical properties of rolled aluminum and development of an in-situ quality control method based on electrical resistivity measurement
AU - Hartl, Karin
AU - Sorger, Marcel
AU - Weiß, Helmut
AU - Stockinger, Martin
PY - 2023/10/5
Y1 - 2023/10/5
U2 - 10.1016/j.jmapro.2023.09.058
DO - 10.1016/j.jmapro.2023.09.058
M3 - Article
VL - 106.2023
SP - 158
EP - 177
JO - Journal of manufacturing processes
JF - Journal of manufacturing processes
SN - 0278-6125
IS - 24 November
ER -
