Optimization of micro-grinding process with compressed air using response surface methodology

Abstract

This paper addresses the optimization of a micro-grinding process using compressed air to minimize specific grinding forces and surface roughness while maximizing specific material removal rate (MRR). The design-of-experiments (DOE) approach and response surface methodology (RSM) are introduced to obtain the optimal grinding conditions. In the DOE approach, a central composite design approach is used for experimental design. Micro-grinding experiments are conducted, and the experimental results are used to obtain response surface models of specific grinding forces and surface roughness in terms of depth of cut, feed rate and air temperature. Multi-objective optimization is then conducted by introducing desirability functions, and the optimal values of depth of cut, feed rate and air temperature are obtained for minimum specific grinding forces and surface roughness and maximum specific MRR. The experimental results under the optimal grinding conditions are similar to those estimated from the response surface models, and thus the validity of the models is verified.