Abstract

In this study, Titanium Oxide (TiO₂) particulate filled e-glass fiber reinforced composites in the unsaturated polyester resin matrix were prepared and its dry sliding wear behavior was optimized. Composites of varying fiber lengths of 1, 2 and 3 cm, respectively with different fiber content of 30, 40 and 50 wt. %, respectively were made. The particulate was varied with 2, 5 and 9 wt. %, respectively. The hybrid reinforced composites were prepared by hand layup method and the wear was measured adopting pin-on-disk system. Taguchi’s experimental design approach was used to make a parametric analysis of the variable fiber length, fiber content and filler material content. The influencing parameter on the wear rate was determined using the Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA). The fiber content emerged as the most significant factor affecting the wear rate of the composites. The regression analysis was carried out to determine the nonlinear analysis for the prediction of the optimized model.

Keywords:

Analysis of Variance (ANOVA), , hybrid reinforced composites, , regression analysis, , Titanium Oxide (TiO₂),

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