Thin-walled blades, critical components in aerospace and energy applications, are subject to challenges during the machining process. The inherent flexibility of these parts, combined with the complexities of varying dynamics and complex geometries, leads to issues such as tolerance violations due to excessive deflections and chatter vibration marks that lead to unacceptable surface finish. This thesis proposes and validates a comprehensive digital model of the process chain to enhance the machining efficiency and quality of milling flexible thin-walled blades. The research integrates three key aspects:​ updating position-dependent structural dynamic parameters of the blade as the metal is removed, modeling the mechanics and dynamics of the ball-end milling of blades, and cutting parameter optimization.

A hybrid model is proposed for updating the structural dynamics of thin-walled workpieces during machining. The initial workpiece is modeled by shell finite elements, and its stiffness and mass matrices are used to determine the eigenvalues (natural frequencies) and mode shapes. The model is calibrated using the experimentally measured (Frequency Response Function) FRF, which reduces the errors contributed by the uncertainties in the material properties. The calibrated model is then perturbed at discrete cutting locations to obtain the updated modes and mode shapes without solving the computationally prohibitive eigenvalue problem.

The cutting forces are predicted from the cutter-blade engagement maps along the toolpath. The forces are applied on the blade to predict the forced vibrations and chatter stability at each tool location. A simplified method to update the cutter-workpiece engagement is used to obtain the three-dimensional stability lobe diagram at desired points on the blade.

An algorithm is developed to update tool orientation and spindle speed based on workpiece dynamics, aiming to enhance stability and surface quality. The thesis also introduces an algorithm for segmentation of stock removal during five-axis finish machining of blades, considering tool flexibility and position-dependent blade dynamics. By optimizing the stock with variable thickness, the algorithm mitigates chatter and reduces surface error and machining time.

The proposed digital model is assessed through experiments on thin-walled twisted fan blades and can be integrated into current CAM software to help the process planning of blades.