Dataset for Model Predictive Force Control in Five-Axis Positional Milling using a Table Dynamometer

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Authors: Patrick Michael Ochudlo, Adrian Karl Rüppel, Lorenz Schmidt, Thomas Bergs, Heike Vallery, Sebastian Stemmler
Cited by: 1

Abstract

This dataset contains Axis Data Stream records and force measurement data during the experimental validation of a model predictive force controller for five-axis positional milling. The experiments were conducted on a five-axis Mazak VARIAXIS i‑600 machine tool (Yamazaki Mazak K.K., Oguchi, Japan) using a Kistler 9255B table dynamometer (Kistler Holding AG, Winterthur, Switzerland) to measure the process forces.The dataset includes machine tool signals such as axis positions, velocities, and accelerations, as well as measured process forces and all controller inputs and outputs used during closed-loop force control experiments.The experiments were performed using a 42CrMo4 steel workpiece and a two‑fluted cemented carbide end mill, and the dataset supports the evaluation and reproducibility of the model predictive force control strategy presented in the associated publication.

Fields of Study & Subjects

Advanced machining processes and optimization Mineral Processing and Grinding Iterative Learning Control Systems

Publication details

Journal / source
RWTH Publications (RWTH Aachen)
Publication date
1 January 2026
Language
EN
Document type
Dataset