Mohammad Khoran - Lecturer of Esfarayen university, Esfarayen. Iran
Pouyan Ghabezi - Young Researchers and Elites club, Science and Research Branch, Islamic Azad University, Tehran
Eisa Khoran - Master student of Material Engineering, Bahonar University of Kerman, Kerman, Iran

Stainless Steels have several uses in different industries and include an extensive area of steels, and because of many differences between mechanical and physical properties of different kinds of stainless steels, it is still necessary to study this type of steels. The surface roughness has been regarded by many researchers since many years ago, because of its high importance in the efficiency of final product, and also because it is considered as a main parameter in examining machinability of metals. In this paper, the experimental reports about optimizing roughness of final surface in milling stainless steel X22 Cr Mo V 12 1, has been carried out using multiple regression technique and ANN(Artificial Neural network). The second order mathematical model has been attained from input parameters of process including cutting speed; Feed rate, radial and axial depths of cut. Each of these inputs of the research has been studied in 3 levels and for this purpose totally 81 experiments have been performed. After measuring the surface roughness caused by milling, the obtained model has been used for scrutinizing the effects of different parameters, and also for predicting the optimal milling parameters in order to obtain ideal surface Roughness

Stainless steel, Milling Parameters, Multiple regression, Artificial Neural network, Surface roughness