An Integrated Approach for optimization of Pulsed ND: YAG Laser Beam Welding process

被引:4
作者
Nagaraju, U. [1 ]
Gowd, G. Harinath [1 ]
Vardan, T. Vishnu [1 ]
机构
[1] Madanapalle Inst Technol & Sci, Madanapalle 517325, India
关键词
RSM; ANN; ND:YAG Laser; DOE and Inconel 625;
D O I
10.1016/j.matpr.2017.11.483
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Laser beam welding is a non-traditional, advanced technique used for similar & dissimilar materials and is widely used in various industries like automobile, aerospace, nuclear reactors, etc. at a faster pace. As it is a complex process, it is very difficult to find the optimal process parameters. The primary point of welding is to acquire a high quality joints and requiring little to no effort. However, without optimization, it is impractical to accomplish minimal effort welding. The principle work of this exploration is to display, break down and improve weld bead geometry in the powerful ND: YAG laser butt welding of Inconel 625. However, in view of the literature review, the responses are continuous and have impact on the welding geometry. In this way the feasible varieties of the judgment factors are started by coordinating trial tests. The Design of Experiment (DOE) system is used to generating the experimental plan and then conducting the experiments according to the plan. After recording the responses Reaction Surface Methodology (RSM) is received for precise expectation numerical models to evaluate the response variables and are created from the experimental information. Artificial Neural Networks (ANNs) have adopted from the MATLAB software for analysing the output response regression and provide the best curve fitting among the input and output variables. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7991 / 8000
页数:10
相关论文
共 8 条
[1]   Effect of laser welding parameters on the heat input and weld-bead profile [J].
Benyounis, KY ;
Olabi, AG ;
Hashmi, MSJ .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2005, 164 :978-985
[2]  
Bhuvana Saharan G., 2007, INT J MANUFACTURING, V32, P1125
[3]  
Casalino G., 2008, INT J ADV MANUFACTUR
[4]  
Gowd G. Harinath, 2011, INT J ENG RES IN AUG
[5]  
Howard B. C., 1989, MODERN WELDING TECHN
[6]   Prediction of weld bead geometry and penetration in shielded metal-are welding using artificial neural networks [J].
Nagesh, DS ;
Datta, GL .
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 2002, 123 (02) :303-312
[7]   Optimization of Nd:YAG laser welding onto magnesium alloy via Taguchi analysis [J].
Pan, LK ;
Wang, CC ;
Hsiao, YC ;
Ho, KC .
OPTICS AND LASER TECHNOLOGY, 2005, 37 (01) :33-42
[8]  
Steen W.M., 1991, LASER MAT PROCESSING