摘要：In today's world of manufacturing by machining process two things are very important, one is productivity and the other one is quality. Quality of a product generally depends upon the surface finish and dimensional deviations. The productivity can be seen as a key economic indicator of innovation in terms of higher material removal rate with a less time and cost in machining industries. Taguchi method is a popular statistical technique for optimization of input parameters to get the best output results. Dry machining is a popular methodology for machining hard material and it has been accepted by many researchers to a great extent because of its low cost and safety. Many scientists have taken various input parameters and studied their effects on different ou tput responses. In the present paper an attempt has been made to study the effect of input parameters such as cutting speed, feed rate and depth of cut on Surface roughness, Tool wear, Power consumption and Chip reduction co - efficient under dry condition u sing uncoated carbide insert. Signal to noise ratio has been used to select the optimal condition for various output responses. ANOVA table has been drawn for each output responses and finally mathematical model of multiple regression analysis has been pre pared and authenticity of the statistical model have been checked by normal probability plot. It has been found from the experimental result that the power consumption and flank wear both were minimum at the cutting speed of 250 rpm and 400 rpm respectively. Chip reduction coefficient has been found minimum at a depth of cut of 0.3 mm and surface roughness was minimum at 0.1 mm/rev. feed rate.
