Analyzing empirically and optimizing surface roughness and tool wear during turning aluminum matrix/rice husk ash (RHA) composite

This research studied the effect of rice husk ash (RHA) during the turning of AlSi10Mg aluminum alloy. Stir casting was the chosen fabrication technique for this investigation. The combined effects of the following turning process parameters including cutting speed (s), feed (f), depth of cut (d), and weight fraction of reinforcement (wt\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${w}_{t}$$\end{document}) on the responses; that is the tool wear and surface roughness were studied. Taguchi L16\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{L}}_{16}$$\end{document} orthogonal array was adopted to determine the experimental runs. The analysis of variance (ANOVA) for the tool wear and the surface roughness showed that the feed and the cutting speed were the most significant factors influencing the tool wear and surface roughness, respectively. Using single objective optimization also affirmed the feed and cutting speed as the most influencing parameters for the tool wear and surface roughness, respectively. The predicted model for tool wear and surface roughness obtained from the regression equation shows a 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.