Analyzing the Effect of Process Parameters on the Weld Bead Geometry in Robotic GMAW using Taguchi Techniques

Thamilarasi, P.; Kumar, E. Mohan; Ragunathan, S.; Kumar, Pardeep

doi:10.5958/2249-7315.2016.00377.4

Cited by 1 publication

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“…Benyounis et al (2005a, b) applied RSM to optimize the effect of laser welding parameters. Thamilarasi et al (2014) predicted and also optimized the selected parameters of robotic GMAW using Taguchi techniques. Many Researchers have been contributing for the development of new welding processes and gain greater understanding of weld quality and mechanical properties (Weisman, 1976).…”

Section: Introductionmentioning

confidence: 99%

Robotics GMAW-weld Bead Geometry Modeling Using MATLAB Script Approach

Thamilarasi¹,

Ragunathan²,

Mohankumar³

2015

RJASET

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This study is aimed at obtaining a relationship between the values of dependent and independent variables of robotic gas metal arc welding, using linear regression techniques. The welding parameters such as the arc current, stick out, arc voltage and welding speed are taken as independent variables and bead geometry namely bead width, bead penetration and bead reinforcement were dependent variables. In this study, the important factors on bead geometry are considered and the other parameters are held as constant. An extension of this model, namely multiple linear regressions, is used to represent the relationship between a dependent variable and several independent variables. Taguchi's L 27 , 3 level 4 parameter orthogonal array design of experiments, twenty seven samples were analyzed and the bead geometry values of the weld bead have been measured. Then, the relationship between the welding parameters is modeled and expressed in multiple linear regression models by a script approach with MATLAB. Each model is checked for its adequacy by using ANOVA. The proposed model is compared with the experiment values and it has positive correlation with maximum of 3.67% error. The results were confirmed by further experiments.

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Section: Introductionmentioning

confidence: 99%