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Item type:Publication, Access status: with files , Feeling machines: Prediction of thin-walled workpiece deflection by monitoring variations in tool bending moment pattern during circumferential milling(Elsevier, 2026-06-30); ; ; In circumferential milling, the in-process deflection of thin-walled workpieces induced by feed normal forces results in reduced material removal, leading to geometric errors after machining. With the increasing use of additive manufacturing technologies and the production of near-net-shape structures, this problem is gaining increasing importance. Various strategies attempt to compensate for this geometric errors, for example by modeling the occurring cutting forces and workpiece deflection and then applying countermeasures during machining. However, this requires a high level of process understanding, and multiple parameters need to be considered, including material properties, cutting edge geometry as well as wear state of the tool. This paper examines a novel approach to predict workpiece deflection state by analyzing the bending moment pattern measured by an in-process sensor system located in the tool holder. It could be demonstrated that features extracted and evaluated from the bending moment signal can represent the current deflection state of the workpiece in an offline approach, enabling future in-situ toolpath adaptation to reduce geometric errors without relying on time-consuming simulation of the workpiece stiffness and with minimal signal processing effort.Publicationtype: Journal Article38 16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Control loop based dimensional error compensation for milling of near-net-shaped, thin-walled structures(Springer, 2025); ; ; ; 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.Publicationtype: Conference Paper48 26