Multi - Objective Optimization of Milling Parameters in HCHCr (D3) Steel by Genetic Algorithm

Abraham Gilbert, Shamnadh. M
2015 International Journal of Engineering Research and  
This work presents an experimental study and optimization of milling operation in HCHCr D3 grade steel using intelligent Genetic Algorithm. The aim of the work was to minimize the surface roughness and cutting force simultaneously, thus making the milling operation more economic and productive. The dry milling operation was done under regulated cutting parameters comprising Spindle Speed, Feed Rate and Depth of Cut. The experiments were designed using Taguchi's orthogonal array consisting of 9
more » ... xperimental runs. The experimental output were analysed using ANOVA to determine the most significant parameter that affects the surface roughness and cutting force. Then using Regression analysis, a mathematical model of the milling operation is formulated to predict the performance measures of surface roughness and cutting force. Optimization was done using the Genetic Algorithm by the mathematical model formulated under the selected parameter constraints.
doi:10.17577/ijertv4is080511 fatcat:dn6bn3dxibfdlpfhimezjnpfee