Process parameter optimization of hot-wire TIG welding of 10 mm thick type 316LN stainless steel plates

焊接 响应面法 材料科学 钨极气体保护焊 冶金 中心组合设计 实验设计 工艺优化 过程变量 热影响区 惰性气体 复合材料 过程(计算) 机械工程 电弧焊 工程类 计算机科学 数学 环境工程 统计 操作系统 机器学习
作者
Chandrasekhar Neelamegam,R. Meenakshisundaram,Vasudevan Muthukumaran
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science [SAGE]
卷期号:238 (3): 849-862 被引量:2
标识
DOI:10.1177/09544062231175779
摘要

This study aims to reduce the number of weld passes and total heat input to 316LN stainless steel during hot-wire tungsten inert gas (HW-TIG) welding process by optimizing process parameters. Therefore, the response surface methodology (RSM) of design of experiments (DOE) approach has been adopted to optimize HW-TIG welding parameters and study the interaction between the parameters and responses. In order to minimize the total number of experimental runs, a design matrix was generated with 30 sets of process parameters. The bead-on plate welding experiments were carried out based on the above generated process parameters. Using the RSM, a quadratic model was developed based on a central composite design to establish the regression equations between input variables (welding current, wire feed current, welding speed, and wire feed rate) and responses (bead width, depth of penetration, and weld cross sectional area). The input process parameters and their responses were correlated with the regression model. Further, parameter values were optimized using the desirability approach and the optimized solutions were generated. Using the optimized process parameters, 316LN stainless steel weld joints were fabricated. Tensile testing and metallography samples were extracted from the fabricated weld joints. The results reveal that the optimization of process parameters by RSM based approach reduced the number of weld passes and improved the weld quality with lower heat input to 316LN stainless steel. In addition, the fabricated weld joint of 316LN stainless steel using the optimized process parameters exhibited better microstructure and strength properties.

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