Prediction and optimization of machining forces using oxley's predictive theory and RSM approach during machining of WHAs

Abstract

Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition. Machining is mandatory for obtaining the final shapes of such kind of ammunitions. However, due to high density and elastic stiffness of WHAs, cutting forces will be higher than for most of the metals and alloys; thus, making the machining operation challenging. The machining variable, namely, cutting force components are significantly influenced by the cutting parameters. This paper makes use of Oxley's predictive analytical model in conjunction with Johnson-Cook constitutive equation to predict forces under different speed and feed combinations during machining of 95 W tungsten heavy alloy. The cutting forces, so predicted by M1, are considered as input data for the optimization of cutting parameters (cutting speed and feed) using Response Surface Method (RSM).