Optimization of Friction Stir Spot Welding Process using Artificial Neural Network
Author(s):
Anup Narsing Chavan , Government College of Engineering Amravati – 444 604 [M.S.] India; Prof. M. T. Shete, Assistant Professor, Mechanical Department Government College of Engineering, Amravati – 444 604 [M.S.] India,
Keywords:
Artificial Neural Networks, FSSW, HDPE-Sheet, Welding Parameters
Abstract:
Friction stir spot welding (FSW) is a relatively novel welding technology, which has caught the interest of automobile, ships and aeronautic industrial sectors due to its many advantages and saving large industrial potential. This paper presents the prediction of welding strength at variable welding parameter used a friction stir spot weld joints obtain through Artificial Neural Networks (ANN). Experiments were conducted by varying the input variable welding parameters such as rotational speed, plunge depth, plunge rate and dwell time, which create a key role in deciding the weld quality. A full design (trials) was used through the experimental design. ANN is solving obtained by two kinds such as M coding and nftool in Mat-lab.
Other Details:
| Manuscript Id | : | IJSTEV1I10114
|
| Published in | : | Volume : 1, Issue : 10
|
| Publication Date | : | 01/05/2015
|
| Page(s) | : | 353-358
|
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