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Optimization of MIG Welding Parameters to Control Quality of Welding

Author(s):

Ankur Malviya , New Horizon College of Engineering , Bengaluru ; Shiena Shekhar, BIT DURG

Keywords:

Metal Inert Gas (MIG), Optimization, Weld Input Parameters, Artificial Neural Network (ANN)

Abstract

In the manufacturing industries welding plays a significant role and such industries require experienced manpower. Since to join metals and to have joints such that it can bear mechanical stresses with respect to the norms of industry standards and to have such welding joints industries requires greater control during the process. The welders play an important role and it again a problem to have sufficient qualitative manpower to obtain the desired process from them. Since MIG welding is popular in automotive and structural sectors so it is required to have to control the process of welding. In MIG welding there are number of input parameters used to control the welding process and so it is required to check and control its input parameters to get weld of desired qualities. In this paper we have discussed the optimization process for input parameters with respect to the quality of welding so that it can be greater help for welders to have control on the output quality of welding.

Other Details

Paper ID: IJSRDV7I10675
Published in: Volume : 7, Issue : 1
Publication Date: 01/04/2019
Page(s): 1499-1502

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