Flehmke, MalteMalteFlehmkeRomanenko, DenysDenysRomanenkoRosenthal, OliverOliverRosenthalDege, Jan HendrikJan HendrikDege2023-06-092023-06-092023-05-16ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb 118 (5): 302-306 (2023)http://hdl.handle.net/11420/15392About one third of rivet holes in aircraft assembly are manufactured using semi-automatic drilling units. These machines can be equipped with internal sensors for measuring process data. In this work, reliable and efficient methods for process state prediction based on internal measurement data using machine learning classification methods are identified for use in aerospace applications. The methods can be used to implement process monitoring, discover anomalies and ensure work piece integrity.de2511-089620235302306De GruyterAircraft AssemblyAutoencoderDrillingMachine LearningProcess MonitoringMLE@TUHHInformatikTechnikIngenieurwissenschaftenJournal Article10.1515/zwf-2023-1054Journal Article