Understanding the micro milling phenomena involved in the process is critical and difficult through physical experiments. This study presents a 3D finite element modeling (3D FEM) approach for the micro end-milling process on Al6082-T6. The proposed model employs a Lagrangian explicit finite element formulation to perform coupled thermo-mechanical transient analyses. FE simulations were performed at different cutting conditions to obtain realistic numerical predictions of chip formation, temperature distribution, and cutting forces by considering the effect of tool run-out in the model. The radial run-out is a significant issue in micro milling processes and influences the cutting stability due to chip load and force variations. The Johnson–Cook (JC) material constitutive model was applied and its constants were determined by an inverse method based on the experimental cutting forces acquired during the micro end-milling tests. The FE model prediction capability was validated by comparing the numerical model results with experimental tests. The maximum tool temperature was predicted in a different angular position of the cutter which is difficult or impossible to obtain in experiments. The predicted results of the model, involving the run-out influence, showed a good correlation with experimental chip formation and the signal shape of cutting forces.
Ti-6Al-4 V titanium alloy is a popular material in industrial applications (e.g. aerospace, oil & gas, medical) due to its superior mechanical properties, although its low thermal conductivity and high chemical reactivity with other materials make it a hard-to-cut material. A finite element model (FEM) was developed in the present investigation to simulate dry and cryogenic orthogonal cutting of Ti-6Al-4 V by using TiAlN coated carbide inserts. Numerical prediction of the effect of the superior cryogenic cooling on chip formation, cutting and thrust forces were investigated. The simulations were validated by the comparison with experimental results. The model calibration was performed with experimental data on dry cutting and then the model was used for predicting the cryogenic cooling case. The validated FEM models were used to compare the chip formation in dry cutting and cryogenic cutting in order to point out some differences in terms of chip segmentation frequency and chip thickness and gain additional knowledge
Predictive models for machining operations have been significantly improved through numerous methods in recent decades. This study proposed a 3D finite element modeling (3D FEM) approach for the micro end-milling of Al6061-T6. Finite element (FE) simulations were performed under different cutting conditions to obtain realistic numerical predictions of chip flow, burr formation, and cutting forces. FE modeling displayed notable advantages, such as capability to easily handle any type of tool geometry and any side effect on chip formation, including thermal aspect and material property changes. The proposed 3D FE model considers the effects of mill helix angle and cutting edge radius on the chip. The prediction capability of the FE model was validated by comparing numerical model and experimental test results. Burr dimension trends were correlated with force profile shapes. However, the FE predictions overestimated the real force magnitude. This overestimation indicates that the model requires further development
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.