Quality prediction for milling processes: automated parametrization of an end-to-end machine learning pipeline
Crossref DOI link: https://doi.org/10.1007/s11740-022-01173-4
Published Online: 2022-11-29
Published Print: 2023-04
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Fertig, Alexander http://orcid.org/0000-0003-4278-0562
Preis, Christoph
Weigold, Matthias
Funding for this research was provided by:
Bundesministerium für Bildung und Forschung (02P17D123)
Technische Universität Darmstadt
Text and Data Mining valid from 2022-11-29
Version of Record valid from 2022-11-29
Article History
Received: 13 September 2022
Accepted: 21 November 2022
First Online: 29 November 2022