Optimization and Prediction of Cutting Force for Sustainable Turning of Ti-6Al-4V under Different Lubricant Viscosity Conditions

It is well known that automobile and aerospace industries explicitly work under mechanical and thermal conditions. To withstand these conditions, it is desirable that it’s mechanical and machinability properties to be understood for providing efficient and long performance. Titanium alloys, regardless of its outstanding properties it has been considered as difficult to machine materials.This paper deals with Taguchi’s design of experiments (TDOE), Response surface methodology (RSM) and Desirability Function Analysis (DFA) for “optimization of cutting force during machining of Ti-6Al-4V” under different lubricant viscosity conditions such as Dry, Oil Water Emulsion (OWE) and Minimum Quantity Lubrication (MQL). In continuation to this analysis, this paper also deals with the effect of process input parameters and its optimisation for minimizing the cutting force and second-order model generation. Finally, a multi responsed cutting force is combined as composite desirability using desirability function analysis. From the analysis through TDOE, RSM and DFA, it was observed that the cutting force was lower in MQL application having viscosity of 20m²/s compared to 0 m²/s (dry) and 10 m²/s (oil water emulsion).