This project presents the prediction the grinding machining parameters for ductile cast iron using water based Zinc Oxide (ZnO) nanoparticles as a coolant. Studies were made to investigate the experimental performance of ductile cast iron during grinding process based on design of experiment. Response surface modeling (RSM) is practical, economic and relatively easy for use. The experimental data was utilized to develop the mathematical model for first- and second order model by regression method. Contour plot is a helpful visualization of the surface when the factors are no more than three and in order to locate the optimum value. The quality of product was determined by output criteria that are minimum temperature rise, minimum surface roughness and maximum material removal rate. Based on prediction data, the second-order gives the good performance of the grinding machine with the significant p-value of analysis of variance that is below than 0.05 and support with R-square value nearly 0.99. From the model profiler and contour plot, the optimum parameter for grinding model is 20m/min table speed and 42.43μm depth of cut could for single pass grinding. For multiple pass grinding it optimized at the table of speed equal to 35.11m/min and 29.78μm depth of cut could for has best quality of product. As the conclusion, objectives were achieved where the grinding parameters were optimized, grinding performance was investigated and mathematical model for abrasive machining parameter was developed. The model was fit adequate and acceptable for sustainable grinding using 0.15% volume concentration of zinc oxide nanocoolant.
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