Selection of optimal machining parameters for multi-tool milling operations using a memetic algorithm

An Experimental Study on Effect of Process Variables on Surface Roughness, Tool Vibrations and Elastic Spring Back in Milling of Aisi 316 Stainless Steel

“…The cutting speed, feed rate and depth of cut were found to be significant cutting parameters on surface roughness, amplitude and elastic spring back has been proved. 4. The multi objective technique shows at a particular cutting speed, feed rate and depth of cut are the optimal combination of milling parameters for minimum surface roughness (R a ), amplitude of cutter vibration along feed and depth of cut directions (V x ,V y ) and maximum elastic spring back effect(S) has been proved in our study.…”

“…RSM was used to optimize cutting parameters for minimum surface roughness and amplitude of cutter vibration. Baskar et al [4] have developed optimization strategy with hill climbing algorithm and genetic algorithm for the optimization of parameters in face milling, corner milling, pocket milling and slot milling. They have obtained maximum profit with the help of developed strategy through optimization of cutting parameters.…”

Optimization of Milling Operation Using Genetic and PSO Algorithm

“…The formula used for calculating the total profit rate is given by M. Tolouei-Red et al [12] (1) The unit cost can be represented by [3] (2)…”

A study on the optimal selection of spur slice cutter parameters and machining parameters

“…Zhang et al [5] used augmented Lagrangian function to optimize the machining parameters of the chatter-free milling process. Some similar methods for parameter optimization were presented in [6][7][8][9][10][11][12][13][14][15][16][17][18]. However, these methods cannot be applied to the optimization of slicing parameters directly.…”