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Optimization of TIG Welding Input Variables for AISI 1020 Low Carbon Steel Plate Using Response Surface Methodology

Year 2018, Volume: 2 Issue: 3, 113 - 122, 27.09.2018

Abstract

Based on the Design of experiment (DOE), an experimental design matrix
having thirteen (13) center points, six (6) axial points and eight (8)
factorial points resulting in twenty (20) experimental runs was generated which
included temperature ranging from
96.13-213.86 A, voltage ranging from 16.95-27.04
V and gas flow rate ranging from 11.29-19.70 L/min.
The aforementioned
twenty runs were used as input parameters for TIG welding experimental
procedure as well as prediction and optimization using Response Surface
Methodology (RSM), with the output responses being temperature distribution,
Induced Stress Distribution and bead penetration depth.
 The optimization result revealed that an input
current of 120 A, voltage of 23.95 V and gas flow rate of 15.63 L/min will
produce a weld material with temperature of 326.530C, ISD of 231.746
N/m2 and bead penetration depth of 6.47911 mm.
To
validate the results, regression plot between the experimental values and RSM
predicted values showed proximity in the coefficient of determination (R2)
for the output responses, indicating that RSM can be used as alternative tool
to the prediction and optimization of weld parameters.

References

  • [1] K. S. Arun and S. Paulraj, “Multi-response optimization of process parameters for TIG welding of Incoloy 800HT by Taguchi grey relational analysis”, Engineering Science and Technology, an International Journal, Vol. 19, Issue 2, pp. 811-817, 2016.[2] A. E. Ikpe, I. Owunna and I. Ememobong, “Effects of Arc Voltage and Welding Current on the Arc Length of Tungsten Inert Gas Welding (TIG)”, International Journal of Engineering Technologies-IJET, Vol. 3, Issue 4, pp. 213-221, 2017.[3] K. Y. Benyounis and A. G. Olabi, “Optimization of Different Welding Processes Using Statistical and Numerical Approaches”, Advances in Engineering Software, Volume 39, Issue 6, pp. 483-496, 2008.[4] R. A. Kumar and M. Vijay, “Parametric Optimization of TIG Welding on Joint of Stainless Steel (316) and Mild Steel Using Taguchi Technique”, International Research Journal of Engineering and Technology, Vol. 4, Issue 5, pp. 366-370, 2017.[5] I. S. Kim, K. J. Son, Y. S. Yang and P. K. D. Yaragada, “Sensitivity analysis for process parameters in GMA welding processes using a factorial design method”, International Journal of Machine Tools Manufacturing, Vol. 43, Issue 8, pp. 763-769, 2003.[6] K. Sanjay, K. S. Pravin, P. Dharmendra and S. B. Prasad, “Optimization of TIG Welding Process Parameters Using Taguchi’s Analysis and Response Surface Methodology”, International Journal of Mechanical Engineering and Technology (IJMET), Vol. 8, Issue 11, pp. 932-941, 2017.[7] D. Katherasan, J. V. Elias, P. Sathiya and A. N. Haq, “Simulation and parameter optimization of flux cored arc welding using artificial neural network and particle swarm optimization algorithm”, Journal of Intelligent Manufacturing, Vol. 25, Issue 1, pp. 67-76, 2014.[8] J. Shih, Y. Tzeng, and J. Yang, “Principal component analysis for multiple quality characteristics optimization of metal inert gas welding aluminium foam plate”, Materials Design, Vol. 32, Issue 3, pp. 1253-1261, 2011.[9] K. Ajit, K. Pawan and K. Manish, “Optimization of Process Parameter in TIG Welding Using Taguchi of Stainless Steel-304”, International Journal of Research in Mechanical Engineering and Technology, Vol. 4, Issue 1, pp. 31-36, 2013. [10] P. R. Abhishek, B. Kumar and S. R. Siva, “Parametric Optimization of Tungsten Inert Gas (TIG) welding by using Taguchi Approach”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 5, Issue 3, pp. 3630-3638, 2016.[11] M. P. Krishnan, and A. N. Sait, “Parametric Optimization and Interaction Effect of TIG Welding Parameters for Stainless Steel (SS 301) Sheets”, Mechanics and Mechanical Engineering, Vol. 19, Issue 2, pp. 91-101, 2015.[12] G. Magudeeswaran, S. R. Nair, L. Sundar and N. Harikannan, “Optimization of process parameters of the activated tungsten inert gas welding for aspect ratio of UNS S32205 duplex stainless steel welds” Defence Technology, Vol. 10, Issue 3, pp. 251-260, 2014.[13] K. Siva, N. Murugan and V. P. Raghupathy, “Modelling, analysis and optimization of weld bead parameters of nickel based overlay deposited by plasma transferred arc surfacing”, Computational Material Science and Surface Engineering, Vol. 1, Issue 3, 174-182. 2009.
Year 2018, Volume: 2 Issue: 3, 113 - 122, 27.09.2018

Abstract

References

  • [1] K. S. Arun and S. Paulraj, “Multi-response optimization of process parameters for TIG welding of Incoloy 800HT by Taguchi grey relational analysis”, Engineering Science and Technology, an International Journal, Vol. 19, Issue 2, pp. 811-817, 2016.[2] A. E. Ikpe, I. Owunna and I. Ememobong, “Effects of Arc Voltage and Welding Current on the Arc Length of Tungsten Inert Gas Welding (TIG)”, International Journal of Engineering Technologies-IJET, Vol. 3, Issue 4, pp. 213-221, 2017.[3] K. Y. Benyounis and A. G. Olabi, “Optimization of Different Welding Processes Using Statistical and Numerical Approaches”, Advances in Engineering Software, Volume 39, Issue 6, pp. 483-496, 2008.[4] R. A. Kumar and M. Vijay, “Parametric Optimization of TIG Welding on Joint of Stainless Steel (316) and Mild Steel Using Taguchi Technique”, International Research Journal of Engineering and Technology, Vol. 4, Issue 5, pp. 366-370, 2017.[5] I. S. Kim, K. J. Son, Y. S. Yang and P. K. D. Yaragada, “Sensitivity analysis for process parameters in GMA welding processes using a factorial design method”, International Journal of Machine Tools Manufacturing, Vol. 43, Issue 8, pp. 763-769, 2003.[6] K. Sanjay, K. S. Pravin, P. Dharmendra and S. B. Prasad, “Optimization of TIG Welding Process Parameters Using Taguchi’s Analysis and Response Surface Methodology”, International Journal of Mechanical Engineering and Technology (IJMET), Vol. 8, Issue 11, pp. 932-941, 2017.[7] D. Katherasan, J. V. Elias, P. Sathiya and A. N. Haq, “Simulation and parameter optimization of flux cored arc welding using artificial neural network and particle swarm optimization algorithm”, Journal of Intelligent Manufacturing, Vol. 25, Issue 1, pp. 67-76, 2014.[8] J. Shih, Y. Tzeng, and J. Yang, “Principal component analysis for multiple quality characteristics optimization of metal inert gas welding aluminium foam plate”, Materials Design, Vol. 32, Issue 3, pp. 1253-1261, 2011.[9] K. Ajit, K. Pawan and K. Manish, “Optimization of Process Parameter in TIG Welding Using Taguchi of Stainless Steel-304”, International Journal of Research in Mechanical Engineering and Technology, Vol. 4, Issue 1, pp. 31-36, 2013. [10] P. R. Abhishek, B. Kumar and S. R. Siva, “Parametric Optimization of Tungsten Inert Gas (TIG) welding by using Taguchi Approach”, International Journal of Innovative Research in Science, Engineering and Technology, Vol. 5, Issue 3, pp. 3630-3638, 2016.[11] M. P. Krishnan, and A. N. Sait, “Parametric Optimization and Interaction Effect of TIG Welding Parameters for Stainless Steel (SS 301) Sheets”, Mechanics and Mechanical Engineering, Vol. 19, Issue 2, pp. 91-101, 2015.[12] G. Magudeeswaran, S. R. Nair, L. Sundar and N. Harikannan, “Optimization of process parameters of the activated tungsten inert gas welding for aspect ratio of UNS S32205 duplex stainless steel welds” Defence Technology, Vol. 10, Issue 3, pp. 251-260, 2014.[13] K. Siva, N. Murugan and V. P. Raghupathy, “Modelling, analysis and optimization of weld bead parameters of nickel based overlay deposited by plasma transferred arc surfacing”, Computational Material Science and Surface Engineering, Vol. 1, Issue 3, 174-182. 2009.
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Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Aniekan Ikpe

İkechukwu Owunna

Publication Date September 27, 2018
Published in Issue Year 2018 Volume: 2 Issue: 3

Cite

IEEE A. Ikpe and İ. Owunna, “Optimization of TIG Welding Input Variables for AISI 1020 Low Carbon Steel Plate Using Response Surface Methodology”, IJESA, vol. 2, no. 3, pp. 113–122, 2018.

ISSN 2548-1185
e-ISSN 2587-2176
Period: Quarterly
Founded: 2016
Publisher: Nisantasi University
e-mail:ilhcol@gmail.com