STATISTICAL MODELING OF SYNTHESIZING OF ALUMINUM BASED NANOCOMPSOITE PARTICLES REINFORCED BY SiC VIA MECHANICAL ALLOYING PROCESS

In this study, mechanical alloying process for producing of aluminum-based nanocomposites reinforced by SiC nanometric particles was modeled by using statistical methods. First, more effective parameters have been selected for analyzing. Since, in order to obtain nanocomposit powder, practical experiments have been planned and carried out. Because, the mechanical alloying process is affected by many complex parameters, complete physical modeling of the process seems to be almost impossible in current condition. Therefore, in this study, statistical modeling was used to analyze the process. By performing statistical analysis of the obtained parameters from experiments, variation trend and mean particle size were perceived. Then, using the regression method, the desired mechanical alloying process was modeled by considering the selected input and output parameters. Statistical analysis was performed in order to make sure about the suitability of this model and it has become clear that the mean particle size is affected by ball to powder weight ratio, squared the ball to powder weight ratio, and the interaction of multiplication of milling speed by milling time. Other input variables in regression model were of little importance and the effect of these terms in the final regression model was neglected.