Replication Data for: A framework to decompose process noise in fineblanking

Dataset Description This dataset contains features extracted with the Python library catch22 with sliding windows (window size 50, stride 10) from force profiles acquired from 39,941 fineblanking shearing phases during a continuous (i.e., one complete tool lifecycle without disassembly of the tool during or between machine runs) experiment. The raw data was preprocessed with drift and tilt correction before feature extraction. The features were provided for: The full shearing path (fullsignal) Extracted between 1.5 mm and 4.5 mm of the shearing path (croppedsignal) Furthermore, tearing data was visually evaluated every 200th process cycle and interpolated. Additionally, SHAP values from feature importance analysis of XGBoost regression models that regressed the features to the tearing data are contained within the dataset both for 'fullsignal' and 'croppedsignal'. All files are .npy arrays with the shape (n_samples, n_features).