Abstract
In this study, fuzzy logic neural networks were employed to optimize the friction stir welding (FSW) process parameters in the joining of copper plates. The FSW parameters were considered as the input variables, for which micro-hardness, nano-hardness, and yield strength of the joints were the responses. The micro-hardness and nano-hardness were measured by Vickers hardness and nanoindentation tests, respectively. The microstructure and substructure of the joints were evaluated by optical, scanning electron, and orientation imaging microscopes. The optimum process parameters through which the maximum strength was achieved were the tool rotational rate of 560 rpm, tool traverse speed of 175 mm/min, and tool axial force of 2.27 kN. The low heat input joints, owing to the finer grain sizes, high density of dislocations, and larger Taylor factors, indicated greater strength relative to the high input joints. Microstructure characterization revealed that dominant strengthening mechanisms of the joints were dislocation density, texture effect, and grain boundary hardening.
Highlights
Copper and copper alloys have attracted attention due to their distinctive characteristics, such as high mechanical strength and excellent electrical conductivity
The Fuzzy Logic Toolbox in Matlab R2013a software was used for solving the fuzzy inference system (FIS)
The definition stated in Equation (1) was used for defuzzification
Summary
Copper and copper alloys have attracted attention due to their distinctive characteristics, such as high mechanical strength and excellent electrical conductivity. Owing to their face-centered cube (FCC) crystallographic structure, they present high formability, which makes them suitable in the production of various final shapes such as plates, profiles, tubes, bars, etc [1]. Thanks to its single-phase structure, copper is usually used as a material for fundamental research investigations [2]. Due to these unique characteristics, there is a surging demand for joining copper and copper alloys. High heat inputs cause a wider heat-affected zone (HAZ), through which the microstructure and mechanical properties can be deteriorated [3]
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