Cutting tool wear minimization in drilling operations of titanium alloy Ti-6Al-4V

Abstract

Cutting tool wear during drilling operations can cause damage to cutting tools, machine tools, and workpieces which should be analyzed and minimized. Cutting tool wear impacts not just tool life but also the quality of the final product in terms of dimensional accuracy and surface integrity. High mechanical and thermal loads are generated during drilling operations of difficult-to-cut materials such as Ti-6Al-4V alloy which can reduce the life of cutting tool during chip formation process. Thus, to increase the accuracy of drilled parts from titanium alloy Ti6-Al-4V, the cutting tool wear during drilling operations should be accurately predicted in order to be minimized. Application of virtual machining systems is developed in the study in order to predict and minimize the cutting tool wear during drilling operations of titanium alloy Ti-6Al-4V. To predict the tool wear during drilling operations, cutting forces and temperature are calculated. Then, the finite element method (FEM) is utilized to predict the tool wear using the analytical model of Takeyama–Murata and updating the cutting tool geometry during chip formation process. To minimize the cutting tool wear during drilling operations, the optimum drilling parameters of feed rate and spindle speed are obtained using the Taguchi method-based response surface analysis algorithm. As a result, optimized drilling parameters are used in order to minimize the cutting tool wear during drilling operations. To validate the study, the experimental works are implemented to the sample workpiece from titanium alloy Ti6-Al4-V and the values of tool wear are then measured. To present the effectiveness of the proposed virtual machining system in minimization of cutting tool wear, the obtained results with and without optimized machining parameters are evaluated and compared. So, precision and productivity in drilling operations of titanium alloy Ti6-Al4-V can be enhanced using the developed virtual machining system in the study.