MULTI OBJECTIVE OPTIMIZATION OF CUTTING PARAMETERS DURING TURNING OF EN31 ALLOY STEEL USING ANT COLONY OPTIMIZATION

In this paper, an attempt is made to optimize the selected turning cutting parameters (cutting speed, feed rate, depth of cut, nose radius of insert edge) to get optimal values of the two chosen response characteristics or objectives (Surface Roughness and Material Removal Rate) and solve the Multi Objective Optimization (MOO) problem. Ant Colony Optimization (ACO), an Evolutionary Algorithm is utilized to find the optimal treatment and the results are compared against those of actual CNC turning. Input to the Algorithm is input parameter bounds, Regression of Material Removal Rate (fitting the MRR obtained by direct formula) and Regression Equation of Surface Roughness obtained by experiment. Obtaining the optimal parameters from the algorithm and using them in machining can help save time, effort, and cost. It also helps increase quality and profit in production.