Aluminum alloy-based additive manufacturing (AM) has emerged as a popular manufacturing process for the fabrication of complex parts in the automotive and aerospace industries. The addition of an inoculant to aluminum alloy powder has been demonstrated to effectively reduce cracking by promoting the formation of equiaxed grains. However, the optimization of the AM process parameters remains challenging owing to their variability. In this study, the response surface methodology (RSM) was used to predict the crack density of AM-processed Al alloy samples. RSM was performed by setting the process parameters and equiaxed grain ratio, which influence crack propagation, as independent variables and designating crack density as a response variable. The RSM-based quadratic polynomial models for crack-density prediction were found to be highly accurate. The relationship among the process parameters, crack density, and equiaxed grain fraction was also investigated using RSM. The findings of this study highlight the efficacy of RSM as a reliable approach for optimizing the properties of AM-processed parts with limited experimental data. These results can contribute to the development of robust AM processing strategies for the fabrication of highquality Al alloy components for various applications.

Processing and characterization of graphene (Gr)-reinforced aluminium alloy 7075 (AA7075) microcomposites and nanocomposites are reported in this work. Composites are fabricated by mechanical alloying process at wet conditions. The bulk composites are prepared by uniaxial die pressing to get higher densification and sintered in an inert atmosphere. Density of the nanocomposites is higher than the microcomposites due to the reduction of grain size by increased milling time. X-ray diffraction (XRD) analysis confirms graphene interaction with the AA7075 matrix lattice spaces. The effective distribution of graphene with aluminium alloy is further confirmed by the Transmission Electron Microscopy (TEM) analysis. The hardness of the composites proportionally increases with the graphene addition owing to grain refinement. Wear morphology is characterized using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Microcomposites reveal abrasive and ploughing wear mechanism of material removal from the surface. Nanocomposites show adhesive wear with delamination and particle pull-out from the material surface.