Optimisation and modelling of burr formation during face milling of rolled steel (AISI 1040) using Taguchi approach

Abstract

ABSTRACT Burr formation on the edge of the machined part during face milling is a common phenomenon. Highly precise and accurate parts are required to be burr free. Generally, deburring (secondary operation) is performed to remove the burr, which leads to the cost of the part. The aim of this study is to obtain minimum exit burr by optimising the input parameters at primary stage of the face milling operation. Effect of machining parameters (cutting velocity, feed per tooth, axial depth of cut), and machining strategies (rolling direction, cutter offset, soaking time during heat treatment) are taken into consideration. Taguchi’s L27 matrix is selected for the design of experiments. Face milling of rolled steel (AISI 1040) is performed on vertical milling centre using titanium nitride coated carbide inserts. Exit burr is evaluated as a signal to noise ratio. The significance level and percentage contribution of parameters are calculated using analysis of variance. Cutter offset has shown maximum contribution followed by cutting velocity. Burr reduction of 58.4% is observed during a confirmation test. Finally, multi-variable linear regression is employed to generate second-order empirical model. Adequacy of model is checked by residual analysis.