Abstract: This study investigates the effects of fiber length and content on the mechanical properties of jute fiberreinforced polypropylene composites through advanced statistical modeling approaches. Jute fibers of varying lengths (3mm, 5mm, and 10mm) and weight contents (10%, 20%, and 30%) were incorporated into polypropylene matrices, and the resulting composites were systematically characterized for their tensile, flexural, and impact properties. Through Response Surface Methodology (RSM), Weibull statistical analysis, and Artificial Neural Network (ANN) modeling, we established that composites with 10mm fiber length and 10% fiber content exhibit optimal mechanical performance, with a tensile strength of 30.3 MPa. Weibull analysis confirmed significantly higher reliability for 10mm fiber composites (β=30.68) compared to shorter fiber alternatives, while ANN modeling effectively captured non-linear behaviors, particularly the distinctive dip-and-recovery pattern observed in 5mm fiber samples. Economic and environmental analyses demonstrate that these optimized composites offer substantial benefits, including a 26% reduction in global warming potential and a 10% cost advantage compared to conventional glass-fibre-reinforced alternatives. This research validates jute fiber-reinforced polypropylene composites as environmentally advantageous and economically viable options for applications where their specific performance characteristics are sufficient.

Keywords: Jute fiber, Polypropylene composites, Response Surface Methodology (RSM), Weibull statistical analysis, Artificial Neural Network (ANN) modelling, Sustainable composites

| DOI: 10.17148/IARJSET.2025.12217