Characterization and machine learning based optimization of banana and paddy straw fiber reinforced epoxy hybrid composites.

This paper investigates a novel hybrid epoxy composite reinforced with cellulose-rich banana and paddy straw fibers, focusing on its fabrication and machining characteristics. While natural fibers have been widely studied, hybrid epoxy composites reinforced with banana and paddy straw fibers remain underexplored. The composites were evaluated for mechanical properties (tensile, flexural, and impact), thermal stability, and water absorption, revealing that the formulation with 30% banana fiber and 10% paddy straw fiber (BP2) provided the best overall balance of tensile, flexural, impact, thermal, and moisture-resistance properties among the compositions studied. Machinability was assessed using Abrasive Water Jet Machining (AWJM), where process parameters, abrasive flow rate (AFR), traverse speed (TS), and standoff distance (SoD), were optimized using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN). The optimal conditions (AFR = 400 g/min, TS = 250 mm/min, SoD = 3 mm) resulted in reduced surface roughness (SR = 3.60 μm) and kerf angle (Kf = 1.56°). SEM, FTIR, and XRD analyses confirmed improved fiber-matrix bonding in BP2, correlating with enhanced machining performance. AWJM provided good machining performance for the developed hybrid composite, achieving low surface roughness and a controlled kerf angle under optimized conditions. This study demonstrates the potential of hybrid banana-paddy straw composites in sustainable engineering, particularly when optimized machining techniques are applied.