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Control loop based dimensional error compensation for milling of near-net-shaped, thin-walled structures
Citation Link: https://doi.org/10.15480/882.15340
Publikationstyp
Conference Proceedings
Date Issued
2025-06-27
Sprache
English
TORE-DOI
Start Page
399
End Page
407
Citation
Decarbonizing Value Chains, ed. by Holger Kohl, Günther Seliger, Franz Dietrich, Ha Thuc Vien: 399-407 (2025)
Contribution to Conference
Publisher DOI
Publisher
Springer
ISBN
978-3-031-93891-7
978-3-031-93890-0
Additive manufacturing has the potential to save resources in the pro-duction of lightweight aerospace structural components made of Ti-6Al-4V. Cur-rently, these components are milled out of plate-material, resulting in up to 95% of the material being converted into chips that can only be downcycled. However, machining near-net-shape parts poses new challenges. For example, commonly used methods such as the “waterline”-path approach, which uses the residual stiff-ness of the plate-material to reduce the deflection of the thin-walls due to process forces, can no longer be applied. In this paper, a dimensional error compensation method is presented, that measures the deflection of the workpiece during helical end mill finishing using eddy current sensors. The sensor values are used within a control loop to adjust the toolpaths width of cut and inclination in real time to minimize dimensional error. Next to adjusting for different compliant states of the workpiece, this method adjusts for increasing tool wear states, that produce higher process forces and thereby larger dimensional errors. The presented compensation is compared to a conventional machining approach to demonstrate its capability to enable finishing of near-net-shape parts within tight tolerances while maintaining high material removal rates.
Subjects
milling | thin-wall machining | deflection | additive manufacturing | control loop | energy and resource efficiency | waste reduction
DDC Class
600: Technology
Publication version
publishedVersion
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Name
978-3-031-93891-7_44.pdf
Type
Main Article
Size
2.26 MB
Format
Adobe PDF