Abstract
Composites reinforced with natural fibers are increasingly progressively in diverse engineering practices for their remarkable attributes, including weight reduction, high strength, cost-efficiency, biodegradability, and renewability. This research explores the mechanical attributes of epoxy composites fortified with jute fiber and alumina. Employing Response Surface Methodology (RSM) with a three-factor, three-level design, the research examines independent variables including orientation (A), size of particle (S), and weight% of particle (W) to optimize process parameters for these composites. It evaluates how these variables influence mechanical properties such as tensile strength, tensile modulus, flexural strength, flexural modulus, and water absorption capacity, aiming to enhance composite performance both economically and effectively. The combination of 0/90° fiber orientation, 106-micron particle size, and 8% weight fraction yields composites with optimized flexural and tensile properties. It is critical to effectively and affordably enhance artificial intelligence tools to establish sound mechanical properties. The Jaya algorithm, developed based on Grey-ANFIS, is utilized for process optimization, applying grey theory to establish a multi-performance index that is rigorously assessed through statistical error analysis. Based on experimental results, the study identifies optimal process variable combinations that ensure superior and enhanced multi-performance characteristics in the fabricated composites.