A hybrid approach to multi response optimization of micro milling process parameters using Taguchi method based graph theory and matrix approach (GTMA) and utility concept

Nowadays, it is required to produce micro products with high dimensional accuracy to use them in different applications like aerospace, electronic and optics. The objective of this study is to investigate influence of process parameters on surface roughness (Ra and Rq), tool wear and cutter vibration in micro milling of AISI304 stainless steel. According to orthogonal array of L27, twenty-seven experiments were conducted on the workpiece with carbide end mill cutter at different levels of spindle speeds, feeds and depth of cuts. A hybrid approach of Taguchi method based graph theory and matrix approach (GTMA) and utility concept was used for multi response optimization of process parameters. The GTMA was used to calculate weightage of four responses as per user's opinion or preference. The utility concept was used to calculate utility value of four responses using preference scale. Mean utility values of responses are analyzed with Taguchi method and analysis of variance. The optimum process parameters for the minimization responses were found to be 6000 rpm of spindle speed, 95 µm/teeth of feed and 50 µm of depth of cut. The predicted responses at optimal process parameters are Ra = 0.534 µm, VB = 70.861 µm, Amp = 54.395 µm and Rq = 0.894 µm. A confirmation test was also carried out to verify the results.