Optimization of machining parameters and tool selection in 2.5D milling using Genetic Algorithm

Optimization of machining parameters for improving the machining efficiency is become important, when high capital cost NC machines have been employed for high precision and efficient machining. The strategy is to minimize the production time and cost by optimizing feed per tooth, speed, width of cut, depth of cut and tool diameter by satisfying all the constraints such as maximum machine power, maximum cutting force, maximum machining speed, feed rate, tool life and required surface roughness. The optimal End milling cutter diameter and radial depth of cut (step over) are also the key issues for minimization of total production cost. Therefore, in this paper an attempt has been made to include all major parameters such as feed per tooth, speed, width of cut (Step-over) and depth of cut along with diameter of tool for minimising the time and production cost during 2.5 D milling. Hence, a mathematical model has been developed and Genetic Algorithm (GA) has been proposed to solve the problem. Optimal values of machining parameters have been calculated for benchmark problems and compared with handbook recommendations. It has been found that approximately 13% of production cost can be reduced by choosing optimal cutter diameter and width of cut. Besides this 50% reduction in cost per unit volume and 61% increment in material removal rate has also been reported by selecting optimal cutting parameters over the handbook recommendations.