Optimization of geometric parameters in a welded joint through response surface methodology

被引:40
作者
Martinez-Conesa, Eusebio J. [1 ]
Egea, Jose A. [2 ]
Miguel, Valentin [3 ]
Toledo, Carlos [1 ]
Meseguer-Valdenebro, Jose L. [1 ]
机构
[1] Univ Politecn Cartagena, Dept Bldg Technol, Paseo Alfonso 13,48, Cartagena 30203, Spain
[2] Univ Politecn Cartagena, Dept Appl Math & Stat, Av Dr Fleming S-N, Cartagena 30202, Spain
[3] Univ Castilla La Mancha, Dept Appl Mech & Projects Engn, Campus Univ S-N, Albacete 02071, Spain
关键词
Response surface methodology; Welding process; Multiobjective optimization; Geometric parameters; PENETRATION; CONCRETE; ALLOY;
D O I
10.1016/j.conbuildmat.2017.07.163
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This work makes use of experimental design and response surface methodology to model Gas Metal Arc Welding processes. The correlations among three key geometric parameters, ie., penetration, bead width and overthickness, and four technological variables that define the welding process are quantified. Based on experimental data and using model selection techniques, a mathematical model has been deduced for each of the response variables herein presented. Using these models, a Multiobjective optimization is carried out to find the space of optimal solutions (i.e., the Pareto front). After a preliminary study of the relationships between independent and response variables, regression models are built. These models capture the data variability reasonably well (e.g., around 70% of the variability). These models are the basis to perform the multiobjective optimization using the epsilon-constraint approach. Results reveal that the conditions which favour a good balance between maximum penetration and minimum bead width and overthickness, involve a high value for gas flow rate, low values for electrode feed rate and voltage, and an intermediate value for the electrode position. This permits the authors to define the welding conditions that lead to an optimum joint geometry and then to guarantee its properties. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:105 / 114
页数:10
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