Summary: The dataset comprises experimental data from milling operations, focusing on the wear of milling inserts at different speeds, feeds, and depths of cut. It's aimed at studying the degradation patterns to predict and understand wear mechanisms.
| Parameter | Value |
|---|---|
| Name | Milling Wear |
| Labeled | Yes |
| Time Series | Yes |
| Simulation | No |
| Missing Values | No |
| Dataset Characteristics | Time-Series, Multivariate |
| Feature Type | Real |
| Associated Tasks | Regression, Anomaly Detection |
| Number of Instances | INA |
| Number of Features | INA |
| Date Donated | 2022-11-22 |
| Source | NASA |
Experiments on a milling machine for different speeds, feeds, and depth of cut. Records the wear of the milling insert, VB. The data set was provided by the UC Berkeley Emergent Space Tensegrities (BEST) Lab.
Milling operations, Tool wear analysis, Degradation study, Predictive maintenance, Operational efficiency