The Combination of Taguchi and Proximity Indexed Value Methods for Multi-criteria Decision Making When Milling

Abstract

Milling is a commonly used method in mechanical machining. This is considered to be the method for the highest productivity among cutting methods. Moreover, the quality of the machined surface is increasingly improved as well as the machining productivity is increasingly enhanced thanks to the development of machine tool and cutting tool manufacturing technology. Therefore, in each specific processing condition (about machine, tool and part material, and other conditions), specific studies are required to determine the value of technological parameters in order to improve productivity and machining accuracy. Only in this way can we take full advantage of the capabilities of modern equipment. The process parameters in the milling method in particular and in the machining and cutting methods in general can be easily adjusted by the machine operator as the parameters of the cutting parameters or the change of tool types. In this article, the combination of Taguchi and Proximity Indexed Value (PIV) methods is presented for multi-criteria decision making in milling. An experimental matrix was designed according to Taguchi method with five input parameters, including the insert materials (TiN, TiCN, and TiAlN), nose radius, cutting velocity, feed rate and depth of cut. The total number of experiments that were performed was twenty-seven. The workpiece used during the experiment was SCM440 steel. At each experiment, the surface roughness was measured and the Material Removal Rate (MRR) was calculated. The weights of these two parameters have been chosen by the decision maker on the basis of consultation with experts. The PIV method was applied to determine the experiment at which the minimum surface roughness and the maximum MRR were simultaneously guaranteed. In addition, the influence of input parameters on surface roughness was also found in this study.