Using Taguchi design of experiments (DoE), experiments were conducted with 3 factors and 3 levels. The factors were the depth of cut, spindle speed, and feed. The responses were surface roughness, flank wear, material removal rate, and spindle vibration along [Formula: see text] ([Formula: see text]), [Formula: see text] ([Formula: see text]), and [Formula: see text] ([Formula: see text]) axis. To convert the multi-response optimization problem into a single response optimization problem, the technique for order of preference by similarity to ideal solution (TOPSIS) was applied. The S/N of the closeness coefficients from TOPSIS was calculated and optimum machining conditions were obtained. Further, analysis of variance (ANOVA) was performed to verify which input parameter significantly affects the output responses. From TOPSIS optimization, the responses like surface roughness and flank wear were decreased by 0.99% and 2.55%. The vibration in [Formula: see text], [Formula: see text], and [Formula: see text]-axis decreased by 3.84%, 16.87% and 12.48% respectively. This optimization significantly enhances the machining characteristics.
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