Application of Statistical Design Methods and Simulated Annealing Algorithm in Milling Process Optimization

摘要

Investigating of cutting forces and vibrations has a critical significance in analyzing and understanding of machining processes as it can provide more details about the cutting tool life, and surface quality and integrity. The purpose of this work is to find the optimal milling process parameters in order to reduce the effect of the forced vibrations induced from the cutting process. Minimizing the cutting forces fluctuation can result in a constant deflection during the milling process, so it can lead to eliminating the chatter and resonance phenomena during the machining process. In order to determine the optimal process parameters, cutter diameter, helix angle and depth of cut have been considered as input design factors and the average surface roughness as a machining characteristic which can be used to evaluate the induced cutting vibrations. Experimental tests have been performed based on Taguchi experimental design meth od. A mathematical regression model has been developed and used as an objective function in the simulated annealing algorithm for the process optimization. In addition, Analysis of variance (ANOVA) has been implemented to find the highest significant parameters and the optimal parameters levels. Another technique has been performed too based on the mechanistic cutting force model in order to simulate the cutting forces which indicate the forces fluctuations at the optimal parameters levels. The results from the previous three techniques show the same optimal milling parameters which can be used in designing new tools in order to eliminate the effect of chatter and forced vibrations.