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Friction welding parameter for AA6063 using ANFIS prediction
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Friction welding parameter for AA6063 using ANFIS prediction
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Journal Article
Friction welding parameter for AA6063 using ANFIS prediction
2023
Overview
It is generally accepted in the field of friction welding that the parameters of rotary friction welding affect mechanical properties. Accurate input is crucial at each process stage, especially in smart factories that use automated machines to produce workpieces. The input for each parameter must be precise. This research proposes a prediction parameter for rotary friction welding for aluminium round bar AA6063, which uses the adaptive-network-based fuzzy inference system (ANFIS) method. The condition, which includes rotational speed, welding time, and friction pressure was used to input the membership function. The ultimate tensile strength of the weld joint was used for the output of ANFIS. The results show that prediction can contribute to industrial applications by determining which parameters can be adapted to the application control for the automatic rotary friction welding process in a Smart Factory.
Publisher
Springer Nature B.V
