Multiple-response modelling and optimisation of micro-turning machining parameters using response surface method

Response surface methodology (RSM) helps the engineers to raise a mathematical model to represent the behaviour of system as a convincing function of process parameters. This paper investigated the influence of three micro-turning process parameters, which were cutting speed (A), feed rate (B) and depth of cut (C). The response variables were average surface roughness ( R a ), tool wear ratio (TWR) and metal removal rate (MRR). Statistical models of these output responses were developed using three-level full factorial design of experiment. The developed models were used for multi-response optimisation by desirability function approach to obtain minimum R a , TWR and maximum MRR. Maximum desirability was found to be 86.63%. The optimised values of R a , TWR and MRR were 0.0295 µm, 0.0272, 0.098 mg/min respectively for 1101.94 rpm cutting speed, 10 µm/sec feed rate, 0.20 µm depth of cut. Optimised machining parameters were used in verification experiments, where the responses were found very close to the p...