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Featured Application: Prediction and selection of the clamping conditions of large-size workpieces for the purpose of milling, based on modal tests and milling simulations. Vibrations occurring during milling operations are one of the main issues disturbing the pursuit of better efficiency of milling operations and product quality. Even in the case of a stable cutting process, vibration reduction is still an important goal. One of the possible solutions to obtain it is selection of the favorable conditions for clamping the workpiece to the machine table. In this paper, a method for predicting and selecting the clamping condition of a large-size workpiece for the reduction in vibrations during milling is presented. A modal test of the workpiece is performed first for a selected set of tightening screw settings. Next, one milling pass is performed to obtain reference data which are then used to tune the hybrid computational model. In the subsequent step, milling simulations are performed for a set of tightening variants, and the best one is selected, providing the lowest vibrations, assessed as the root mean square (RMS) of vibration displacements. In this paper, the description of the clamping selection procedure, key elements of the simulation model, and simulation and experimental results obtained for the milling of the test workpiece performed for a set of different clamping conditions are provided. The proposed method accurately predicts not only the best but also the worst clamping conditions. [ABSTRACT FROM AUTHOR]

The article introduces a method for selecting the best clamping conditions to obtain vibration reduction during the milling of large-size workpieces. It is based on experimental modal analysis performed for a set of assumed, fixing conditions of a considered workpiece to identify frequency response functions (FRFs) for each tightening torque of the mounting screws. Simulated plots of periodically changing nominal cutting forces are then calculated. Subsequently, by multiplying FRF and spectra of cutting forces, a clamping selection function (CSF) is determined, and, thanks to this function, vibration root mean square (RMS) is calculated resulting in the clamping selection indicator (CSI) that indicates the best clamping of the workpiece. The effectiveness of the method was evidenced by assessing the RMS value of the vibration level observed in the time domain during the real-time face milling process of a large-sized exemplary item. The proposed approach may be useful for seeking the best conditions for fixing the workpiece on the table. [ABSTRACT FROM AUTHOR]

Modern industry expectations in terms of milling operations often demand the milling of the flexible details by using slender ball-end tools. This is a difficult task because of possible vibration occurrence. Due to existence of certain conditions (small depths of cutting, regeneration phenomena), cutting process may become unstable and self-excited chatter vibration may appear. Frequency of the chatter vibration is close to dominant natural frequency of the workpiece or the tool. One of the methods of chatter vibration avoidance is matching the spindle speed to the optimum phase shift between subsequent cutting edges passes (i.e. the Liao-Young condition). However, the set of optimum spindle speeds from the point of view of vibration reduction may be not optimum one from other points of view. For example milling efficiency or machine tool capabilities cannot be assured. This article presents the idea of a workpiece holder with adjustable stiffness and discusses a new variant of its realization. In the holder, milling process is performed at constant spindle speed and feed speed. In order to avoid vibration the holder stiffness is modified. Stiffness changes modify natural frequencies of the workpiece and thus it is possible to modify dynamic properties of the workpiece in such a way that arbitrary chosen, constant spindle speed will be optimum, due to the Liao-Young condition performance. Calculation of the optimum stiffness is performed before milling, based on the workpieces modal identification results and the finite element model simulations.