| Zugehörige Institution(en) am KIT | Institut für Produktionstechnik (WBK) |
| Publikationstyp | Forschungsdaten |
| Publikationsdatum | 01.07.2025 |
| Erstellungsdatum | 26.06.2025 |
| Identifikator | DOI: 10.35097/hvvwn1kfwf7qt48z KITopen-ID: 1000182633 |
| Lizenz | Creative Commons Namensnennung 4.0 International |
| Projektinformation | DatAmount (BMWE, BG08653/22) |
| Schlagwörter | Machine Tool, Process Monitoring, Anomaly Detection, Machine Learning, Milling, CNC |
| Liesmich | This dataset contains process data from around six hours of milling operations performed on a three-axis horizontal milling machine (DMC 60 H, Deckel Maho). The data was collected in a laboratory setting using industry relevant components, tools and machining strategies in order to reflect the diversity and variability of practical milling scenarios. Controller-side process signals were acquired from the Siemens SINUMERIK 840D CNC system via the SINUMERIK Edge app "Analyze MyWorkpiece/Capture", which enables high-frequency data export at 500 Hz. Additional force measurements were recorded using a force measurement platform (Kistler Type 9255C), and accelerations were captured using a sensor mounted on the main spindle (PCB Type 356A33). The force platform signals were amplified using a charge amplifier (Kistler Type 5015A1000 K) before being acquired at a sampling rate of 10 kHz useing a data acquisition card (Data Translation DT9836; referred to as DAC). The acceleration sensor was connected to the same DAC via a Kistler coupler (type 5122). Raw data from the force and acceleration sensors is provided in the form of MATLAB timetable files (.mat). The process signals from the Siemens SINUMERIK Edge are stored in JSON format (.json). Preprocessed Edge data is also available as structured CSV files:
A total of, 33 milling experiments are included, covering three component types and eight anomaly types. NC programs, 3D CAD models (.stp), and detailed documentation are provided to support full reproducibility and benchmarking applications. Documents:
Experimental Setup:
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| Art der Forschungsdaten | Dataset |
| Nachgewiesen in | OpenAlex |
| Relationen in KITopen |