Abstract
In today’s world, there is a growing emphasis on using fiber-reinforced composites carefully across diverse sectors like automotive, construction, machinery and appliances. These materials are valued for their capacity to be efficiently repurposed, recycled or disposed of with minimal ecological consequences. Thus, integrating sustainable, eco-friendly and environmental mindful approaches into developing new materials and processes has become increasingly imperative. This study aims to analyze the impact strength, inter laminar shear strength and water absorption capacity of the jute fiber composite filled with the particles like alumina (Al2O3), boron carbide (B4C) and silicon carbide (SiC). The response surface methodology (RSM), employing three levels and three parameters, enables the identification of distinct combinations of input parameters essential for the fabrication of suitable polymer composites. The effects of process factors on interlaminar shear strength (ILSS), impact strength and % weight increase are examined. For each output measures, the connotation of the input parameters is determined by analysis of variance (ANOVA). To establish multiple performance indexes, a hybrid model called adaptive neuro-fuzzy inference system (ANFIS) based on Grey theory is developed. The model’s capability is validated and the results confirm the effective prediction of the preferred performance indicator.
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