Optimization of cutting parameters to reduce cutting tool temperature in a dry turning process using genetic algorithm - Muhammad Waseem (2014)
High cutting temperatures in dry turning processes increase tool wear and affect the quality of the work piece. This project presents the optimization of cutting parameters in a dry turning process in order to reduce the cutting temperature using mild steel as the work piece and carbide insert cutting tool. The optimization has been carried out by manipulating the feed rate, depth of cut and cutting speed using Genetic Algorithm. GA was processed using MATLAB and the values of cutting speed, depth of cut and the feed rate were varied between constraints of 50 - 200 m/min, 0.5 - 2 mm and 0.05 to 0.25 mm/rev. respectively. The effects of varying cutting speed, depth of cut and feed rate on the cutting temperature were analyzed and the optimal parameters resulting in the lowest temperatures for different production volumes were then selected from the results.