Multi objective optimization of turning parameters for Al 6061 using genetic algorithm

Aluminum alloys such as Al 6061 is most widely used alloy in Aviation industry for construction of aircraft wings and fuselages. It also has its applications in automobiles, shipping, general purpose applications, packaging, etc. This project aims at reducing the machining time for turning of Aluminum 6061 T6 alloy, simultaneously giving a better surface finish to the work piece. Design of experiments was formulated according to Taguchi's method of DOE, where 16 experiments are performed with 3 control factors having 4 levels each. Material Removal Rate (MRR) and Surface Roughness (Ra) are responses. Multiple Regression Analysis was performed on both the responses to evaluate the fittest mathematical models. These models were used to formulate a multi objective problem, which is used for carrying out optimization of the control variables using Multi Objective Genetic Algorithm (GA). The maximum MRR obtained was 3468.37 mm^3/min with least surface roughness value as 0.7568μm when cutting conditions were set to speed -1000rpm , feed - 0.606 mm/rev and Depth of cut - 0.5 mm. GA is an efficient and effective optimization tool for finding the optimum machining parameters . The results give a positive indication of the potential offered by GA.