In this present study, a high‐performance structural epoxy biocomposite has been prepared and characterized for its mechanical, wear, and fatigue behavior. The main aim of this research was to determine the effect of fiber stacking order and the biosilica addition in the epoxy hybrid composite when it is subjected to external loading. The research also focused on how the surface treatment process on fiber and particle affects the mechanical, wear, and fatigue behavior of composite. The biosilica particles were synthesized from black rice husks and then surface treated with 3‐aminopropyltriethoxysilane. Similarly, a base treatment was applied to fiber mats and the composite laminates for this investigation were fabricated by hand layup process. It is noted that the composite designations E12 and E22 exhibited an improved tensile strength of 58, 62% and flexural strength of 45, 51% for 1.0 vol% biosilica in both staking sequence models. Similarly, in inter‐laminar shear strength the composites E2, E21 and E22 outperformed than E1, E11, and E12. In terms of Izod impact toughness and hardness, composite designation E22 provides maximum increment of about 94% and 5%. The wear resistance of composite E22 exhibited lower wear loss and COF. The highest fatigue life count of 41,782 was observed for the composite designation E22 in tension‐tension fatigue mode. Overall the stacking order R/A/G/A/R gives better results than others. These load bearing properties enhanced hybrid composites might be employed in structural, industrial, automotive, home appliance, defense, and lightweight industrial applications.

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The current research deals on Taguchi coupled grey relational analysis (GRA) multi-objective optimization of Wire Electric Discharge Machining (WEDM) for better surface roughness (Ra) and Material Removal Rate (MRR) over Magnesium/Halloysite Nano Tube/Zirconium (Mg/HNT/Zr) Metal Matrix Composite (MMC). Hybrid Composites are created through the powder metallurgy route by varying the weight percent of reinforcements HNT (5 & 10%) and Zr (0.5 & 1%) to the weight of the base material magnesium. Machining is carried out by varying the factors such as reinforcement’s weight percentage, pulse OFF time, pulse ON time, and wire feed (Wf) based on Taguchi's L27 orthogonal array. The responses surface roughness (Ra) and Material Removal Rate (MRR) were studied through Taguchi coupled GRA to evaluate the optimized machining parameters. ANOVA results reveal the percentage contribution of certain factors over the machining of composites. The developed regression model proved that the predicted values are merely similar to the experimental values of MRR and Ra. The best parametric combinations obtained from optimization are inline as the minimum weight percentage of reinforcements, higher Pon, higher Wf, and the lowered Poff to attain the best rate of MRR during machining and for minimized surface roughness.