Optimization of environmentally benign micro-drilling process with nanofluid minimum quantity lubrication using response surface methodology and genetic algorithm

This paper discusses the optimization of environmentally benign nanofluid MQL micro-drilling process using nanodiamond particles based on a response surface methodology (RSM) and genetic algorithm (GA) in the cases of base fluid of paraffin oil and vegetable oil. In order to obtain regression functions of drilling torques and thrust forces in terms of process factors such as drill diameter, feed rate, spindle speed and nanofluid volumetric concentration, a series of micro-drilling experiments are conducted by using a design of experiment (DOE) approach. Then, the multi-objective optimization for minimizing drilling torques and thrust forces and maximizing material removal rate (MRR) is carried out by introducing GA, and the optimal values of process factors such as drill diameter, feed rate, spindle speed and nanofluid volumetric concentration are obtained. The micro-drilling experiments with the optimal process factors are conducted, and their results are very similar to calculated ones. Thus, the validity of the regression models of drilling torques and thrust forces are demonstrated.