Modelling the effect of surface roughness factors in the machining of 2024Al/Al2O3 particle composites based on orthogonal arrays

This study presents an experimental investigation of the effects of cutting speed, size and volume fraction of particle on the surface roughness in turning of 2024Al alloy composites reinforced with Al2O3 particles. A plan of experiments, based on Taguchi method, was performed machining with different cutting speeds using coated carbide tools K10 and TP30. The objective was to establish a correlation between cutting speed, size and volume fraction of particle with the surface roughness in workpieces. These correlations were obtained by multiple linear regression. The analysis of variance was also employed to carry out the effects of these parameters on the surface roughness. The test results revealed that surface roughness increased with increasing the cutting speed and decreased with increasing the size and the volume fraction of particles for both cutting tools. The average surface roughness values of TP30 cutting tools were observed to be lower than those of K10 tools. For the average surface roughness values of TP30 tool, cutting speed was found to be the most effective factor while the volume fraction of particle was the most effective factor for those of K10 tool. A good agreement between the predicted and experimental surface roughness was observed within a reasonable limit.