%0 Journal Article
%1 Reeber_2024
%A Reeber, Tim
%A Henninger, Jens
%A Weingarz, Niklas
%A Simon, Peter M.
%A Berndt, Maximilian
%A Glatt, Moritz
%A Kirsch, Benjamin
%A Eisseler, Rocco
%A Aurich, Jan C.
%A Möhring, Hans Christian
%D 2024
%I Elsevier BV
%J Procedia CIRP
%K analysis anomaly condition detection learning machine machining manufacturing monitoring networks neural process series time tool
%P 216–221
%R 10.1016/j.procir.2023.08.066
%T Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data
%U http://dx.doi.org/10.1016/j.procir.2023.08.066
%V 121
@article{Reeber_2024,
added-at = {2024-02-02T08:07:58.000+0100},
author = {Reeber, Tim and Henninger, Jens and Weingarz, Niklas and Simon, Peter M. and Berndt, Maximilian and Glatt, Moritz and Kirsch, Benjamin and Eisseler, Rocco and Aurich, Jan C. and Möhring, Hans Christian},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2bf17e993f626a2b1aa67f853fc1fb2ed/treeber},
doi = {10.1016/j.procir.2023.08.066},
interhash = {e3a1289eb25f61b42c18d8b1c809b89a},
intrahash = {bf17e993f626a2b1aa67f853fc1fb2ed},
issn = {2212-8271},
journal = {Procedia CIRP},
keywords = {analysis anomaly condition detection learning machine machining manufacturing monitoring networks neural process series time tool},
pages = {216–221},
publisher = {Elsevier BV},
timestamp = {2024-02-02T08:07:58.000+0100},
title = {Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data},
url = {http://dx.doi.org/10.1016/j.procir.2023.08.066},
volume = 121,
year = 2024
}