FE analysis of the effects of process representations on the prediction of residual stresses and chip morphology in the down-milling of Ti6Al4V

Part I of these two-part papers will investigate the effect of three FEM representations of the milling process on the prediction of chip morphology and residual stresses (RS), when down-milling small uncut chips with thickness in the micrometer range and finite cutting edge radius. They are: i) orthogonal cutting with the mean uncut chip thickness t, obtained by averaging the uncut chip thickness over the cutting length, ii) orthogonal cutting with variable t, which characterizes the down-milling process and which is imposed on a flat surface of the final workpiece, and iii) modelling the true kinematics of the down milling process. The appropriate constitutive model is identified through 2D FEM investigation of the effects of selected constitutive equations and failure models on the prediction of RS and chip morphology in the dry orthogonal machining of Ti6Al4V and comparison to experimental measurements. The chip morphology and RS prediction capability of these representations is assessed using the available set of experimental data. Models featuring variable chip thickness have revealed the transition from continuous chip formation to the rubbing mode and have improved the predictions of residual stresses. The use of sequential cuts is necessary to converge toward experimental data.

Effects of Sequential Cuts on White Layer Formation and Retained Austenite Content in Hard Turning of AISI52100 Steel

This technical brief is the extension of our previous work developed by Zhang et al. (2016, “Effects of Process Parameters on White Layer Formation and Morphology in Hard Turning of AISI52100 Steel,” ASME J. Manuf. Sci. Eng., 138(7), p. 074502). We investigated the effects of sequential cuts on microstructure alteration in hard turning of AISI52100 steel. Samples undergone five sequential cuts are prepared with different radial feed rates and cutting speeds. Optical microscope and X-ray diffraction (XRD) are employed to analyze the microstructures of white layer and bulk materials after sequential cutting processes. Through the studies we first find out the increasing of white layer thickness in the sequential cuts. This trend in sequential cuts does work for different process parameters, belonging to the usually used ones in hard turning of AISI52100 steel. In addition, we find that the white layer thickness increases with the increasing of cutting speed, as recorded in the literature. To reveal the mechanism of white layer formation, XRD measurements of white layers generated in the sequential cuts are made. As a result retained austenite in white layers is identified, which states that the thermally driven phase transformations dominate the white layer formation, rather than the severe plastic deformation in cuts. Furthermore, retained austenite contents in sequential cuts with different process parameters are discussed. While using a smaller radial feed rate, the greater retained austenite content found in experiments is attributed to the generated compressive surface residual stresses, which possibly restricts the martensitic transformation.

Harvest scheduling with spatial aggregation for two and three strip cut system under shelterwood management

We propose a spatial aggregation method to solve an optimal harvest scheduling problem for strip shelterwood management. Strip shelterwood management involves either a two-cut system with a preparatory-removal cut cycle, or a three-cut system with a preparatory-establishment-removal cut cycle. In this study we consider these connected sequential cuts as one decision variable, then employ conventional adjacency constraints to seek the best combination of sequential cuts over space and time. Conventional adjacency constraints exclude any spatially-overlapped strips in the decision variables. Our results show the proposed approach can be used to analyze a strip shelterwood cutting system that requires "connectivity" of management units.