Optimization of the High Energy Milling Process of Chips of a Stainless Steel Using the Response Surface Modeling

The present paper discusses response surface methodology as an efficient approach for predictive model building and optimization of the high energy milling process from the chip duplex stainless steel with a carbide vanadium addition willing to obtain the smaller particle size. The process parameters studied was milling time of 10 h and 50 h. Rotations were performed at 250 and 350 rpm. Vanadium carbide was added from 0% to 3% in weight, and a mass/ball ratio of 1/10 and 1/20. An analysis of particle size and a scanning electronic microscopy were used to measure and characterize particle size. With addition of carbide in milling process resulted on a reduction of particle size compared to the material without carbide added around 66%. The results predicted using factorial regression model showed high values of regression coefficients (R-2 = 0.952) indicating good agreement with experimental data. The minimum value of particle size was obtained for following optimal conditions: rotation of 325 rpm, time of 42 h, ball/mass 18:1 and carbide 2, 67%wt. The particle size of fabricated powders after 50 h of milling with 3% vanadium carbide addition was about 186 times lower than that the initial chips.