Abstract
This research focuses on material removal rate in abrasive jet machining (AJM) of zirconia ceramic under varying process conditions (grain size of silicon carbide abrasive, air pressure, stand-off-distance). Combined approach of orthogonal array, and response surface methodology are respectively, applied for assessment, predictive modelling as well as response optimization. The influence of air pressure emerged as the most critical factor in enhancing MRR during AJM of zirconia ceramic. At elevated pressures, the surface morphology exhibits characteristic deep chipping and larger crater marks. The proposed predictive model for MRR utilizing the regression method proves effective, demonstrating adequacy, statistical significance, and probabilistic validation, indicated by its high R2-value (0.995), P-value below 0.05 (0.016), and substantial AD-test P-value (0.327). By employing DFA to solve the response optimization problem, optimal MRR (0.0000619 gm/min) for AJM of zirconia ceramic is achieved at abrasive grain size of 750 μm, air pressure of 7 kgf/cm2, and stand-off distance of 2 mm.
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