Application of response surface methodology in the optimization of cutting conditions for surface roughness

This paper focuses on the development of an effective methodology to determine the optimum cutting conditions leading to minimum surface roughness in milling of mold surfaces by coupling response surface methodology (RSM) with a developed genetic algorithm (GA). RSM is utilized to create an efficient analytical model for surface roughness in terms of cutting parameters: feed, cutting speed, axial depth of cut, radial depth of cut and machining tolerance. For this purpose, a number of machining experiments based on statistical three-level full factorial design of experiments method are carried out in order to collect surface roughness values. An effective fourth order response surface (RS) model is developed utilizing experimental measurements in the mold cavity. RS model is further interfaced with the GA to optimize the cutting conditions for desired surface roughness. The GA reduces the surface roughness value in the mold cavity from 0.412 μm to 0.375 μm corresponding to about 10% improvement. Optimum cutting condition produced from GA is verified with the experimental measurement.