Modeling and optimization of tool parameters in friction stir lap joining of aluminum using RSM and NSGA II

被引:33
作者
Akbari, Mostafa [1 ]
Asiabaraki, Hossein Rahimi [1 ]
机构
[1] Tech & Vocat Univ TVU, Dept Mech Engn, Tehran, Iran
关键词
Friction stir welding; shoulder diameter; probe diameter temperature; force; ARTIFICIAL NEURAL-NETWORK; FORCE;
D O I
10.1080/09507116.2022.2164530
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Friction stir welding (FSW) success depends heavily on the temperature and strain the FSW/FSP tool induces. This study examined the influence of FSW tool characteristics like shoulder and probe diameter and probe height on temperature, forces and failure load of welding of AA5083 alloy using the response surface methodology (RSM). The study's setup consisted of three factors, three levels, and 17 experimental runs. In order to determine the welding temperature, a thermocouple was placed inside the samples. Also, the force during the process was measured using a fixture designed for this purpose. The generated model's suitability at a 95% confidence level was assessed using an analysis of variance. Using RSM, a relationship was discovered between input parameters, including tool settings and output responses, such as temperature, force, and joint mechanical properties. This relationship was then used to discover the best process parameters using a hybrid multiobjective optimization. Hybrid multiobjective optimization recommends a probe diameter of 5.1 mm, a shoulder diameter of 17.63 mm, and a probe height of 3.86 mm as the optimum tool. This study discovered that the most important factors influencing temperature force and failure load were shoulder diameter, probe diameter, and probe height, respectively.
引用
收藏
页码:21 / 33
页数:13
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