Analyzing empirically and optimizing surface roughness and tool wear during turning aluminum matrix/Bio-ash composite

Abstract

The effect of biomaterial that is rice husk ash (RHA while turning aluminum alloy (AlSi10Mg) was investigated in this study. Stir casting was the chosen fabrication technique. On the responses of tool wear and surface roughness, the combined effects of the following turning process parameters were examined: cutting speed (s), feed (f), depth of cut (d), and weight fraction of reinforcement (\({w}_{t}\)). Taguchi \({\text{L}}_{16}\) orthogonal array was adopted to determine the experimental runs. The results of the tool wear and surface roughness were documented. Analysis of variance (ANOVA) indicated that the most important factors influencing each of the tool wear and surface roughness were the feed and the cutting speed respectively. Applying single objective optimization also affirmed feed and cutting speed as the most impacting parameters for the tool wear and surface roughness respectively. The predicted model for tool wear and surface roughness obtained from the regression equation shows good correlation with the experimental results. A correlation of 95% and 94% of tool wear and surface roughness was determined between the predicted and corresponding experimental results.