Intelligent design of Ni-Cu alloys: friction-based processing enhanced by fuzzy logic and microstructural insights

This study investigates the friction stir processing (FSP) of Monel 400 alloy, a corrosion-resistant nickel-copper alloy used in chemical applications. Fusion-based processing of Monel 400 can result in defects due to its high thermal conductivity, making FSP a promising alternative. A fuzzy logic-based modeling approach combined with the Complex Proportional Assessment (COPRAS) method was employed to optimize FSP parameters and enhance mechanical properties. Experiments were designed using a central composite matrix, considering tool rotational speed, traverse speed, and axial force as control factors. Microstructure and mechanical properties were evaluated using Electron Backscatter Diffraction (EBSD) and Transmission Electron Microscopy (TEM). Optimal parameters (1200 rpm, 50 mm/min, and 2 kN) produced refined grains with a high fraction of high-angle grain boundaries (HAGBs), leading to enhanced properties: microhardness of 191 HV, nanohardness of 2.44 GPa, and yield strength of 252 MPa. In contrast, higher heat input led to grain coarsening and reduced dislocation density. The fuzzy logic model accurately predicted output responses with minimal deviation from experimental results. COPRAS was applied to rank the parameter sets based on utility degree, enabling multi-criteria decision-making. This integrated framework effectively improves parameter selection and mechanical performance through controlled heat input during the FSP of Monel 400.