Influence of work material microstructure on vibrations when machining cast Ti-6Al-4V

Abstract

Listen

Translate article

Titanium alloys are known to produce shear-localized chips during machining, resulting in cyclic variations in cutting forces which in turn could cause severe problems with vibrations. However, at low cutting speeds and feed rates, continuous chips are formed, with an increase in both parameters favoring the transition to shear-localized chips. This transition is affected by work material microstructure, where a coarse microstructure gives anisotropic effects, e.g., when the size of alpha colonies is on the same order of magnitude as the primary cutting zone. The change in chip morphology with an increase in cutting parameters will then be dependent on the orientation of alpha colonies within the cutting zone. The microstructure of work material can show large variations depending on product form, e.g., cast, wrought, or sheet material, thus affecting whether the chip formation is isotropic or anisotropic. Other sources of variations also exist that can be found within the same component, such as segregation of alloying elements and differences in thermo-mechanical history during processing due to geometry. In this study, the interaction between work material microstructure, process parameters, and the machining system’s structural characteristics is studied. The aim is to further increase the knowledge about vibrations during machining of titanium and the role of microstructure and machining system properties. Different microstructures were produced by adding boron to cast Ti-6Al-4V material, where the resulting colony sizes gave both isotropic and anisotropic chip formation within the chosen cutting data range. The machining systems dynamic properties were varied by using different tool overhangs, thereby simulating different configurations of natural frequencies and stiffness. The results show the influence of both microstructure and machining system’s structural characteristics on the dynamic response of the system for different process parameters. This information can be used to increase robustness of machining operations taking into consideration this three-way relationship.