TY - JOUR A1 - Piendl, Daniel A1 - Radtke, Maximilian-Peter A1 - Jacobsen, Hendrik A1 - Bock, Jürgen A1 - Zaeh, Michael T1 - Predictive Maintenance of Ball Screws: A Comparative Study Using Real-World Industrial Data JF - Procedia CIRP N2 - Ball screws are widely used in machine tool feed drives. With increasing degradation of the ball screws, machining accuracy and economic efficiency decrease. Past investigations have shown that condition monitoring models can predict this degradation. However, these models are typically trained and evaluated using datasets derived from test benches, questioning their applicability to real machine tools. In this article, a comparative evaluation of a selection of these condition monitoring models using an industrial dataset is described. This dataset consists of measurement data from a total of nine ball screws used in three machine tools until failure. It was shown that when using data of multiple ball screws or machines, artificial neural networks or automated machine learning methods achieve a higher accuracy than statistical methods. However, for smaller datasets, statistical methods perform almost as well. The results provide an insight into the industrial applicability of the evaluated condition monitoring models. UR - https://doi.org/10.1016/j.procir.2025.02.135 Y1 - 2025 UR - https://doi.org/10.1016/j.procir.2025.02.135 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-61629 SN - 2212-8271 VL - 2025 IS - 134 SP - 390 EP - 395 PB - Elsevier CY - Amsterdam ER -