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Dataset for Potential of Model Predictive Force Control in Five-Axis Positional Milling Considering Tool Wear

Ochudlo, Patrick Michael (Corresponding author)^RWTH* ; Rüppel, Adrian Karl^RWTH* ; Plum, Franziska^RWTH* ; Bergs, Thomas^RWTH* ; Vallery, Heike^RWTH* ; Stemmler, Sebastian^RWTH*

2026

Online
DOI: 10.18154/RWTH-2026-05233
URL: https://publications.rwth-aachen.de/record/1035975/files/Data_Potential_MPFC_Considering_Tool_Wear.zip

Einrichtungen

1. Lehrstuhl und Institut für Regelungstechnik (416610)
2. Manufacturing Technology Institute – MTI (417400)

Projekte

1. DFG project G:(GEPRIS)450794086 - Modellbasierte prädiktive Kraftregelung für das mehrachsige Schruppfräsen (450794086) (450794086)

Inhaltliche Beschreibung (Schlagwörter)
Five-axis positional milling (frei) ; Tool wear (frei) ; Force control (frei) ; Table dynamometer (frei) ; Model predictive control (frei)

Kurzfassung
This dataset contains axis data stream records and force measurement data collected during the experimental comparison of a model predictive force controller and feedrate scheduling. Both a new and a severely worn tool were used. 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 in five-axis positional milling. The experiments were performed using a 42CrMo4 steel workpiece and two‑fluted cemented carbide end mills, one unused and one severely worn. The dataset supports the experimental results presented in the associated publication.

OpenAccess:
ZIP
(additional files)

Dokumenttyp
Dataset

Format
online

Sprache
English

Interne Identnummern
RWTH-2026-05233
Datensatz-ID: 1035975

Beteiligte Länder
Germany