Investigations of performance parameters in NFMQL assisted turning of titanium alloy using TOPSIS and particle swarm optimisation method

This paper deals with the multi-response optimisation of process parameters during NFMQL assisted turning of titanium (grade-2) alloy using TOPSIS and PSO method. The cutting speed, feed rate, approach angle and different nano-fluids were considered as the input parameters, whereas tool wear (VBmax), main cutting force (Fc) and surface roughness (Ra) were output parameters. The response surface methodology is used and the multi-response fitness function is established with TOPSIS approach. Thereafter, the model significance and the influence of the process parameters have been investigated based on the ANOVA tests. In the end, the prediction of optimum parameters for multi-response characteristics has been performed by using PSO method. The outcome reveals that, the lower value of cutting speed (204 mm/min), lower value feed rate (0.11 mm/rev), moderate value of approach angle (75°) and graphite based nano-fluids are the optimum machining parameters.