Statistical modeling of main cutting force produced by wet turning using soluble oil-water mixture lubricant

In this paper, we present machining tests by turning En-31 steel alloy with tungsten carbide inserts using soluble oil-water mixture lubricant under different machining conditions. Firstorder and second-order cutting force prediction models were developed by using the experimental data by applying response surface methodology combined with factorial design of experiments. Analysis of variance (ANOVA) is also employed to check the adequacy of the developed models. The established equations show that feed rate and depth of cut are the main influencing factors on the cutting force followed by tool nose radius and cutting velocity. It increases with increase in the feed rate, depth of cut and tool nose radius but decreases with an increase in the cutting velocity. The predicted cutting force values of the samples have been found to lie close to that of the experimentally observed values with 95% confident levels. Moreover, the surface response counters have been generated from the model equations. Desirability function is used for single response optimization.