Optimization of cutting parameters in milling process using genetic Algorithm and anova (March 2020)‎

Abstract EN

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear.

The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool.

Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that issimultaneously optimized.

Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear.

The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool.

Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that issimultaneously optimized.

Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work