Fuzzy Logic Model for Combined Monitoring of Weld Strength and Nugget Hardness of Friction Stir Weld
Keywords:
Friction stir welding, fuzzy logic, aluminum alloys, tensile strength, hardnessAbstract
In this paper, the development of a fuzzy logic model to monitor the weld tensile strength and nugget hardness of Friction Stir Welding (FSW) is reported. AA6063-T6 aluminum alloy plates, of 6 mm thickness, were joined, using the FSW process. FSW is a complex solid-state process, and the process parameters, spindle rotational speed, traverse feed rate, and tool shoulder plunge depth, are significant in deciding the mechanical properties of FSW joints. For these 3 significant process parameters and their 3 levels, the most suitable array, Taguchi's L27 orthogonal array, was selected for the experiments. Based on the experimental results, a Mamdani type fuzzy model was developed to forecast the combined FSW weld tensile strength and nugget hardness. The developed fuzzy model was experimentally validated. As compared with the experimental results, the fuzzy model results exhibit errors of 2.13 and 1.31 % for weld tensile strength and nugget hardness, respectively. The proposed approach could be employed for the online monitoring and control of the FSW process within the range of the process parameters.
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