DrillProcess Timeseries MachineLearning
Year: 2026
Type: software
Abstract: Timeseries data of a drilling process for maschine learning The dataset is created by simulation, not by real-world measurement. Within this data package, the software for simulation is provided together with simulated data. The datasets (per day (YYYY-MM-DD), shift {01, 02, 03} and drilling maschine {01,02}) contains attributes: - Timestamp - Torque - Ambient Temperature - Rotation Speed - Process Temperature - Failure category The dataset is intended for demonstration and education purposes, e.g. within NFDI4ING's training format _RDM Basics for Engineers_ [DOI 10.5281/zenodo.21395410].
Source: RADAR4ING
Author: Münker, Sven
Institution: RWTH Aachen University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225175507