DrillProcess Timeseries MachineLearning

RADAR4ING

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].

Authors 1

1. Sven Münker corresponding Aachen Laboratory for Machine Tools and Production Engineering (WZL)

   RWTH Aachen University

   Affiliation as printed

   Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University