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Ti6Al4V is the most widely used titanium alloy and is a demanding material in applications requiring high specific strength and corrosion resistance, that is, aerospace, automobile and biomedical industries. However, the poor machinability of this alloy, resulting from its low thermal conductivity, high hardness at elevated temperatures, high chemical reactivity with the cutting tool and low elastic modulus, restricts its usage. As a result, the tool life in machining of Ti6Al4V is substantially less than conventional materials such as steel and aluminium. This work reviews the various techniques employed in improving the machinability of Ti6Al4V alloy, from the perspective of cutting tool technology. The focus is onto the parameters affecting tool life in machining of Ti6Al4V alloy with some trending techniques and their feasibility, considering the economics to develop the best techno-economic method.

Titanium alloy, Ti6Al4V, is an exceptional material with several desirable properties, namely, high specific strength, high corrosion and heat resistance, which make it a promising contender in number of demanding applications. However, it has poor machinability, resulting from low thermal conductivity, high chemical reactivity with tool and spring effect during cutting. These properties lead to reduced tool life during machining, due to which its usage is limited despite excellent mechanical properties. Therefore, optimization of process parameters using response surface methodology in face milling of Ti6Al4V alloy with uncoated carbide tools has been investigated experimentally in this work. This article is focused on developing mathematical relation between input factors and response parameters, namely, surface roughness (R a), tool wear (T w) and tool vibration (T v). The machining parameters are optimized for minimum R a , T w and T v values. The optimal parameters are validated experimentally which showed a good agreement with the predicted results. The feed rate was found to be the most influential parameter affecting R a and T v , whereas cutting speed is the most effective in influencing T w .

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