Modeling and optimization of machine parameters using simulated annealing algorithm (SAA)

The present work deals with the mathematical modeling and analysis of machining response such as the surface roughness in the milling of aluminum alloy (AA6061). There are several machining variables like rotational speed, depth of cut and feed rate used to find the quality of surface quality. Simulated Annealing Algorithm (SAA) is utilized to develop an effective mathematical model to predict optimum level. In simulated annealing algorithm (SAA), an exponential cooling program depending on Newtonian cooling is applied and experimentation is done on choosing the number of iterations for each step. The SAA is used to predict the cutting variables (rotational speed, feed rate and depth of cut) on product quality in dry milling of Al 6061 based on Taguchi‘s orthogonal array of L9 and analysis of variance (ANOVA) were apply to determination the important factors that effect on surface quality. At last, tests were conducted to confirm by making a comparison between the experimental results and the model developed. The experimental results have shown the performance of machining in the milling can be improved effectively using this algorithm