Tungsten heavy alloys are widely used in the manufacturing of weights for aircraft, missiles, boats and race cars; penetrators; radiation shielding; and radioisotope containers. Manufacturing these components needs machining as a secondary operation. Since tungsten heavy alloys are difficult to machine, the in-depth analysis of tool wear growth and mechanism during machining of these alloys becomes essential. Hence, this work focuses on the experimental study of flank wear growth and its effect on other machining outputs for two different tool geometries (−5° and 2° rake angles) during turning of 90 tungsten heavy alloys. The predominant wear mechanism was identified as adhesion based on scanning electron microscopic analysis. Finally, three commonly used analytical tool wear rate models and one newly proposed model (modified Zhao model) were utilized for the prediction of flank wear growth and tool life. It was observed that the modified Zhao model could predict tool flank wear fairly well within error percentage of 4%–7% and thus could be used as a benchmark while machining difficult-to-cut alloys.

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The present work attempts to assess the machinability of tungsten heavy alloys (WHAs) with varying tungsten content in terms of different machining characteristics such as chip thickness, material removal rate, cutting force and surface roughness under varied cutting conditions. The feed rate is found to have major influence on the machining characteristics; whereas the effect of rake angle appears to be marginal. With increase in W content both cutting force and material removal rate increase whereas surface roughness decreases. Since WHAs are difficult to machine, an additional objective of the study is to optimize machining parameters. An optimal balance of the experimental cutting parameters using Grey relational analysis has been achieved, which can be effectively employed for the machining of the alloys with close dimensional tolerances and desirable surface finish.

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