Statistical Multi-Response Optimization and Prediction of Abrasive Water Jet Machining Process Parameters for HRS Fiber/CNT/Epoxy Hybrid Composites

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Abstract
This paper investigates the AWJ machinability of Hibiscus Rosa-Sinensis/carbon nanotube (CNT) fiber/epoxy-based hybrid composites by analyzing key machinability metrics such as kerf width (KW), material removal rate (MRR), and surface roughness (Ra). Various process parameters including CNT weight percentage, CNT diameter, stand-off distance, and traverse speed have been varied to optimize the machining performance. Experimental analysis suggested that increasing the CNT weight percentage significantly enhanced material hardness, thereby reducing both the MRR and surface roughness. Moreover, adjusting the stand-off distance and traverse speed further improved the machinability of the composite. ANOVA results highlighted that CNT weight percentage was a significant factor, accounting for 94.17% of the variation in MRR and 93.72% of the variation in surface finish, while the stand-off distance influenced 87.03% of the variation in kerf width. Additionally, response surface methodology (RSM) was utilized to develop predictive models that estimated KW, MRR, and Ra with error rates of 2.95%, 2.23%, and 5.65%, respectively. These insights offer a valuable framework for tailoring the AWJ process to achieve optimal machining outcomes in HRS/CNT/epoxy composite materials

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