%0 Thesis %1 Agne2020 %A Agne, Joachim %C Am Hubland, Informatikgebäude, 97074 Würzburg, Germany %D 2020 %K Industry_4_0 Thesis_supervised_by_Marwin_Zuefle Online_monitoring_and_forecasting descartes feature_engineering Thesis_supervised_by_SE_member Cyber-Physical_Systems se2_mastersthesis %T Predicting Failures by Means of Machine Learning Methods on the Example of an Industrial Press

@mastersthesis{Agne2020, added-at = {2020-04-20T14:47:33.000+0200}, address = {Am Hubland, Informatikgeb{\"a}ude, 97074 W{\"u}rzburg, Germany}, author = {Agne, Joachim}, biburl = {https://www.bibsonomy.org/bibtex/22085dffa2e9aa58880d5b86725dc306a/se-group}, interhash = {e85a886a3ee42dab8c089577b690e44e}, intrahash = {2085dffa2e9aa58880d5b86725dc306a}, keywords = {Industry_4_0 Thesis_supervised_by_Marwin_Zuefle Online_monitoring_and_forecasting descartes feature_engineering Thesis_supervised_by_SE_member Cyber-Physical_Systems se2_mastersthesis}, month = {February}, school = {University of W{\"u}rzburg}, timestamp = {2020-05-13T11:56:51.000+0200}, title = {{Predicting Failures by Means of Machine Learning Methods on the Example of an Industrial Press}}, type = {{MasterThesis}}, year = 2020 }