Optimization of Turning Process and Cutting Force Using Multiobjective Genetic Algorithm

Application of artificial intelligence in manufacturing process has great impact factor. This work paper is focused into optimization of machining by turning process regarding to the analysing of tool selection (TS), tool path length (TPL) and machining parameters for turning operation using the artificial Intelligence. Except of solving of problems for tool selection and tool path length, here also will be analysed the cutting force (Fc) by turning process whereas as case of research material is steel C45. The results of measurement of the main cutting force Fc, are compared and predicted in theoretical and practical way. Also, all of requirements are fulfilled in regard of the expression. In same time are optimized the main machining parameters regarding to the cutting force with utilization of the Multi-Objective Genetic Algorithm (MOGA). Results for cutting power Pc and Metal removal rate MRR using Pareto Front are obtained using MOGA.