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Multi-Objective Optimization of Process Parameters in Resistance Spot Welding of A36 Mild Steel and Hot Dipped Galvanized Steel Sheets Using Non-dominated Sorting Genetic Algorithm
Metals and Materials International ( IF 3.5 ) Pub Date : 2021-07-04 , DOI: 10.1007/s12540-021-00986-9
B. V. Feujofack Kemda 1 , N. Barka 1 , M. Jahazi 2 , D. Osmani 3
Affiliation  

Industry is constantly moving towards an increasing of production speed while minimizing production costs. This paper presents an efficient method for minimizing production times and energies through optimization of process parameters in resistance spot welding (RSW). Two grades of steel were used in this study, ASTM A36 steel and A653 hot dipped galvanized steel. Welding was done in overlap configuration, grade for grade, while following complete factorial plans. Micrographic analysis revealed welds microstructure while micro-indentation hardness tests enabled to establish hardness profiles along weld nuggets. Tensile-shear tests have been carried out in order to quantify the mechanical strength of welds. Analysis of variance showed that welding current is the most significant parameter and contributes for about 70% to welds mechanical strength. The ratio of hardness in the fusion zone to nugget surface area was found to be correlated with the failure mode of welded specimens. On that basis, a multi-objective optimization of the process parameters, through the non-dominated sorting genetic algorithm was performed. This optimization resulted in a reduction of current, electrode pressing force and welding time of 10.58%, 13.59% and 32.61% respectively. Optimized parameters were then assessed trough tensile-shear testing of welded specimens, all specimens passed the validation tests by experiencing failure in the base metal.

Graphic Abstract



中文翻译:

非支配排序遗传算法对A36低碳钢和热镀锌钢板电阻点焊工艺参数的多目标优化

工业正在不断提高生产速度,同时最大限度地降低生产成本。本文提出了一种通过优化电阻点焊 (RSW) 的工艺参数来最小化生产时间和能源的有效方法。本研究中使用了两种钢种,ASTM A36 钢和 A653 热浸镀锌钢。焊接是在重叠配置中完成的,一个等级一个等级,同时遵循完整的因子计划。显微分析揭示了焊缝的微观结构,而显微压痕硬度测试能够建立沿焊缝熔核的硬度分布。为了量化焊缝的机械强度,已经进行了拉伸剪切试验。方差分析表明,焊接电流是最重要的参数,对焊缝机械强度的贡献率约为 70%。发现熔合区的硬度与熔核表面积的比率与焊接试样的失效模式相关。在此基础上,通过非支配排序遗传算法对工艺参数进行多目标优化。这种优化导致电流、电极压紧力和焊接时间分别减少了 10.58%、13.59% 和 32.61%。然后通过焊接试样的拉伸剪切测试评估优化的参数,所有试样都通过了母材失效的验证测试。这种优化导致电流、电极压紧力和焊接时间分别减少了 10.58%、13.59% 和 32.61%。然后通过焊接试样的拉伸剪切测试评估优化的参数,所有试样都通过了母材失效的验证测试。这种优化导致电流、电极压紧力和焊接时间分别减少了 10.58%、13.59% 和 32.61%。然后通过焊接试样的拉伸剪切测试评估优化的参数,所有试样都通过了母材失效的验证测试。

图形摘要

更新日期:2021-07-04
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