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1 Ergebnisse
1
Tool Wear Prediction in the End Milling Process of Ti-6Al-4..:
, In:
2022 International Conference on Advanced Mechatronic Systems (ICAMechS)
,
Kim, Gyeongho
;
Yang, Sang Min
;
Kim, Sinwon
... - p. 64-69 , 2022
Link:
https://doi.org/10.1109/ICAMechS57222.2022.10003325
RT T1 <cTitle>2022 International Conference on Advanced Mechatronic Systems (ICAMechS)</cTitle>: T1 <Title>Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10003325&Exemplar=1&LAN=DE A1 Kim, Gyeongho A1 Yang, Sang Min A1 Kim, Sinwon A1 Kim, Dong Min A1 Lim, Sunghoon A1 Park, Hyung Wook YR 2022 SN 2325-0690 K1 Productivity K1 Titanium alloys K1 Uncertainty K1 Milling K1 Predictive models K1 Thermal conductivity K1 Probabilistic logic K1 tool wear prediction K1 Bayesian learning K1 deep learning K1 machining process SP 64 OP 69 LK http://dx.doi.org/https://doi.org/10.1109/ICAMechS57222.2022.10003325 DO https://doi.org/10.1109/ICAMechS57222.2022.10003325 SF ELIB - SuUB Bremen
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