| About this Abstract |
| Meeting |
13th International Conference on the Technology of Plasticity (ICTP 2021)
|
| Symposium
|
13th International Conference on the Technology of Plasticity (ICTP 2021)
|
| Presentation Title |
Investigation of Machine Learning Models for a Time Series Classification Task in Radial-axial Ring Rolling |
| Author(s) |
Simon Fahle, Thomas Glaser, Bernd Kuhlenkötter |
| On-Site Speaker (Planned) |
Simon Fahle |
| Abstract Scope |
The great potential of machine learning models in different domains has been shown in recent years. Based upon initial research regarding preprocessing methods for time series classification in the hot forming technology of radial-axial ring rolling, this paper takes the next step to further investigate the suitability of different machine learning models for a classification task regarding the ovality of a formed ring. This is done by implementing several models of the time series classification domain in machine learning and training them on actual production data of thyssenkrupp rothe erde Germany. The data set consists of different production days and ring geometries. Different experiments will be performed, the results will be analyzed regarding performance, interpretability and usability in the production environment. Thus a suitable model for the underlying task will be investigated, which is essential for a future model deployment. |
| Proceedings Inclusion? |
Definite: At-meeting proceedings |