Modeling the machining mechanics of additively manufactured parts

Additive manufacturing (AM) enables the production of metallic components with customized geometries and offers solutions for part repair through its layer-by-layer fabrication process. Despite these advantages, AM parts typically require post-machining to achieve the required dimensional accuracy, surface quality, and functional performance. Reliable prediction of cutting forces during machining is therefore essential for effective process planning and maintaining component integrity. The machining response of AM metals is influenced by variations in mechanical behavior arising from AM-induced microstructural features. Experimental studies have examined the influence of these microstructural variations on cutting forces during machining. However, the reported trends are highly inconsistent, ranging from negligible force sensitivity to pronounced changes, with some studies observing force variations approaching a factor of two. While these differences are often attributed to build orientation or microstructural characteristics, the explanations remain largely qualitative. Consequently, existing experimental evidence does not provide a quantitative basis for predicting how microstructure-driven property variations affect cutting forces. To address this limitation, this thesis presents an integrated analytical framework for predicting cutting forces in the machining of AM metals considering microstructural effects. Accurate force prediction requires modeling both the shear angle and material resistance to deformation in machining. Accordingly, the proposed framework couples a physics-based shear angle model with a microstructure-informed constitutive model to describe chip formation and material response under machining conditions. The shear angle model accounts for the finite thickness of the primary shear zone and stress transformation within the shear zone, enabling material-dependent prediction of shear angle. The constitutive model incorporates the effects of strain, strain rate, temperature, and dominant microstructural strengthening mechanisms of the AM parts under machining-related environment. The framework is first developed and validated for orthogonal cutting, where predicted shear angles, flow stresses, and cutting forces show good agreement with experimental results. It is then extended to milling by incorporating time-varying chip thickness and geometrical transformations, enabling analytical prediction of milling forces without reliance on empirical force coefficients. This helps avoid extensive trial-and-error when selecting suitable cutting conditions and recalibrating the model as changes in AM parameters alter the resulting microstructural features.