Optimization of the accumulative roll bonding process parameters and SiC content for optimum enhancement in mechanical properties of Al-Ni-SiC composites

Accumulative Roll Bonding (ARB) is one of the main techniques to manufacture nanocomposites, however, due to the large number of parameters that control this process, its application is relatively expensive. The present work considers a simple response surface methodology to study the interaction effect between the selected ARB parameters on the tensile strength and the hardness of the ARBed composite sheets. We investigated the characterization, modeling, and numerical optimization of the accumulative roll-bonded (ARBed) AA1050 composite sheets produced using a number of passes ranging from 1 to 7 and reinforced with different SiC content (0, 1, 3, and 5 wt%). The effect of the number of passes and SiC content on the microstructure, phase analysis, tensile, and hardness properties have been investigated for the ARBed sheets and their composites. Also, the fracture surface of the tensile-tested specimens was studied using SEM analysis. Numerical optimization was conducted using the developed model to determine the optimum parameters of the ARB process in the designed experiments. The modelling analysis results confirm the significance of the applied ARB parameters on the properties of the ARBed sheet composites. The numerical optimization analysis indicates the optimum ARB factors are 7

Automated summary

Accumulative Roll Bonding (ARB) is an expensive technique due to the large number of controlling parameters, but a response surface methodology is used in this study to analyze the interaction effect between ARB parameters on the tensile strength and hardness of composite sheets. By investigating the microstructure, phase analysis, and mechanical properties of ARBed AA1050 composite sheets produced with different passes and SiC content, the significance of ARB parameters on the properties of the composites is confirmed. Numerical optimization reveals that the optimum ARB factors are 7.