Comparison between Taguchi Method and Response Surface Methodology (RSM) In Optimizing Machining Condition

The application of Taguchi method and RSM to optimize the milling parameters when machining Aluminum silicon alloy (AlSic) matrix composite reinforced with aluminum nitride (AlN) with three types of carbide inserts is presented. Experiments were conducted at various cutting speeds, feed rates, and depth of cut according to Taguchi method using a standard orthogonal array L9 (34) and RSM historical data. The effects of cutting speeds, feed rates, depth of cut and types of tool on the surface roughness in milling operation were evaluated using Taguchi optimization methodology by utilizing the signal-to-noise (S/N) ratio and RSM optimization. Surface finish produced is very important in determining the quality of the machined part is within the specification and permissible tolerance limit. The analysis of results using S/N ratio concludes that the combination of low feed rate, low depth of cut, medium cutting speed and uncoated tool give a remarkable surface finish. Desirability criterion in RSM shows the optimum condition is at combination of high feed rate, high depth of cut, medium cutting speed and uncoated tool. In this case, the optimum condition obtained using Taguchi method is more accurate than RSM. Therefore it can be concluded that Taguchi method requires less number of experiment than RSM to determine an accurate optimum machining condition.