Statistical Modeling of the Machinability of an In-Situ Synthesized RZ5/TiB2 Magnesium Matrix Composite in Dry Turning Condition

Machinability analyses of metal matrix composites are essential for manufacturing industries. The current study is focused on the mathematical modeling of the machinability of an in-situ synthesized RZ5-8 wt.% TiB2 composite using the Taguchi design statistical tools and analysis of variance (ANOVA). Taguchi's method indicates that the feed rate is the most influential parameter, followed by the depth of cut and cutting speed in determining the cutting force and surface roughness during the machining of the RZ5/8 wt.% TiB2 composite. A regression analysis of the experimental data was carried out using ANOVA, and regression equations were established to estimate cutting force and surface roughness under different parametric conditions. The regression model was validated for other test conditions and the maximum deviation observed was +/- 10%. Main effects plots and response surface plots were developed to analyze the machining parameters' individual and combined effects on the RZ5/8 wt.% TiB2 composite's machinability. The chip morphology and tool wear of the RZ5/8 wt.% TiB2 composite were analyzed using FESEM under different machining conditions.

Automated summary

The current study focuses on the mathematical modeling of the machinability of an in-situ synthesized RZ5-8 wt.% TiB2 composite using Taguchi design and analysis of variance (ANOVA). The study reveals that the most influential parameter in machining the composite is the feed rate, followed by the depth of cut and cutting speed. Regression equations are established using ANOVA to estimate the cutting force and surface roughness under different parametric conditions. The regression model is validated and shows a maximum deviation of +/- 10%. The effects of machining parameters on the composite's machinability are analyzed using main effects plots and response surface plots. Chip morphology and tool wear are also analyzed under different machining conditions using FESEM.