EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH DECISION TREE ALGORITHM

Abstract

The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed ([Formula: see text]), feed ([Formula: see text]), and depth of cut ([Formula: see text]) on surface roughness (Ra) of turning AA7075 filled with 10[Formula: see text]wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner within the matrix material. The machining of composite was carried out by using the CNC turning center and tungsten carbide insert as tool material. This experimental work was designed on L27 (33) orthogonal array using Taguchi’s design of experiments. From its signal-to-noise (S/N) ratio study, the minimum surface roughness (Ra) was obtained at the optimum level of parameters with the cutting speed at 1500[Formula: see text]rpm, feed at 0.15[Formula: see text]mm/rev and depth of cut at 0.3[Formula: see text]mm. Analysis of variance (ANOVA) and decision tree (DT) algorithm were used to identify the significant effect of parameters. The experimental result shows that depth of cut was the major significant parameter on surface roughness (Ra) when compared to cutting speed and feed.