Energy Cost Optimization in High Speed Hard Turning Using Simulated Annealing Algorithm

Abstract

Selecting the cutting conditions to optimize the economics of machining process as assessed by energy machining cost is essential. The aim of this research is to determine the optimum cutting parameters that minimize the energy cost needed for removing one cubic centimetre of material in High Speed Hard Turning (HSHT) process. To achieve that, a set of experimental machining data to cut hardened steel AISI 4340 was obtained with different ranges of cutting speed, feed rate, depth of cut and negative rake angle using mixed ceramic as a cutting tool. Regression models have been developed by using Box-Behnken design as a design of experiment. Then, the Simulated Annealing Algorithm (SAA) has been used to optimize the cutting parameters. The data collected was statistically modelled. The results show that the range of minimum energy cost to remove one cubic centimetre of material for the three techniques can be achieved in the range of 300 to 308 as a cutting speed, -12 for cutting rake angle, 0.125 as a feed rate and 0.15 as a depth of cut.