Document Type : Research Paper





This study investigated the optimization of three welding parameters (wire feed speed, arc voltage, and shielding gas flow rate) for SS 304H by using Taguchi based Grey relational analysis. In this research work, pure argon was used as shielding gas. Numbers of trials were performed as per L16 (4xx3) orthogonal array design and the mechanical quality such ultimate tensile strength, microhardness, Toughness, and microstructure of SS304H optimized by Grey-based Taguchi analysis and result shows that the optimal parameters combination were as A4B4C3 i.e. flow rate at 23L/min, voltage at 25 V and welding speed at 350IPM and it was observed that wire feed speed had the most significant effect followed by voltage and gas flow rate. An optimal combined parameter of the welding operation was obtained via Grey relational analysis. By analyzing Grey relational grade matrix, the degree of influence for each controllable process factor onto individual quality targets can be found. 

Graphical Abstract

Optimization of gas metal arcwelding parameters of SS304 austenitic steel by Taguchi –Grey relational analysis


Main Subjects

[1]     Saadat Ali Rizvi, SP Tewari and Wajahat Ali, Advanced Welding Technology ,Katson  publishers, New Delhi, INDIA, pp. 8-9,(2007).
[2]     Lippold, J. C., and Koteki, D. J., Welding metallurgy and weldability of Stainless steels,2nd ed. john wiley & sons, New Jersey, pp. 40-41(2005).
[3] Baddoo N. R., ”Stainless steel in construction-A review of research, applications, challenges and opportunities’ of constructional steel research,Vol. 64, pp. 1199-06, (2008).
[4]     Tusek J., and Suban M., “Dependence of melting rate in MIG/MAG welding on the type of shielding gas used”, Journal of Material Process Technology, Vol. 119 ,pp. 185-192,(2001).
[5]     S. M. Joo, H. S. Bang, and S. Y. Kwak, “Optimization of hybrid CO2 laser-GMA welding parameters on dissimilar materials AH32/STS304L using Grey-based Taguchi analysis”, International Journal of Precision Engineering and Manufacturing, Vol. 15, No. 3 pp.447-454, (2014).
[6]     A. K Srirangan, 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, pp.811-817, (2016).
[7]     R. Sathish, B., Naveen, P., Nijanthan, K., Arun Vasantha, Geethan, R., and Vaddi Seshagiri, “Weldability and process parameter optimization of dissimilar pipe joints using GTAW”, International Journal of  Engineering  Research and Applications. Vol. 2, No. 3, pp. 2525-2530, (2012).
[8]     A. Hakan, A. Bayram, E. Ugur, Y. Kazancoglu, G. Onur, “Application of Grey relational analysis and Taguchi method for the parametric optimization of friction stir welding process”, Materials and Technology. Vol. 44, No. 4, pp. 205-211, (2010).
[9]     S. K Sharma, Saadat Ali Rizvi, and R. P, Kori, “Optimization of Process Parameters in Turning of AISI 8620 Steel Using Taguchi and Grey Taguchi Analysis”, International Journal of Engineering Research and Applications, Vol. 4, No. 3, Version 6, pp. 51-57,(2014).
[10]   Nabendu Ghosh, Pradip Kumar Pal, Goutam Nandi, “Parametric Optimization of MIG Welding on 316L Austenitic Stainless Steel by Grey-Based Taguchi Method”, Procedia Technology, Vol. 25, pp. 1038-1048, (2016).
[11]   S. Datta, A. Bandyopadhyay, P. K. Pal, “Grey-based Taguchi method for optimization of bead geometry in submerged arc bead on-plate welding”. International Journal of Advanced Manufacturing Technology, Vol. 39, No. 11-12, pp. 1136-1143, (2008).
[12]   P. Sathiya, S. Aravindan, R. Jeyapaul P.M. Ajith, and A. Noorul Haq, “Optimizing the weld bead characteristics of super austenitic stainless steel (904L) through grey-based Taguchi method”, Multidiscipline Modeling in Materials and Structures, Vol. 6, No. 2, pp. 206 - 213, (2010).
[13]   Saadat Ali Rizvi, SP Tewari, Wajahat Ali, Application of Taguchi Technique to Optimize the process parameters of MIG wedging on IS 2062 steel, International Journal on Emerging Trends in Mechanical & Production Engineering, Vol. 2, No. 2,pp. 1-11, ( 2016).
[14]     S. Khalilpourazary, P. M. Kashtiban and N. Payam, Optimizing turning operation of St37 steel using grey relational Analysis,Journal of Computational and Applied Research in Mechanical Engineering, Vol. 3, No. 2, pp. 134-144, (2014).
[15]   ASTM E8/E8M − 11. Standard Test Methods for Tension Testing of Metallic Materials. ASM International; (2013).
[16]   R. Ramanujam, N. Muthukrishnan and R. Raju, ”Optimization of cutting parameters for turning Al–SiC(10p) MMC using ANOVA and Grey relational analysis” International Journal of Precision Engineering and Manufacturing, Vol. 12, No. 4, pp. 651-656, (2011).
 [17] S. Ranganathan and T. Senthilvelan, “Multi-response optimization of machining parameters in hot turning using Grey analysis”. International Journal of Advanced Manufacturing Technology, Vol. 56, No. 5, pp. 455-462, (2011).
[18]   R. Vinayagamoorthy and A. M. Xavior, “Parametric optimization on multi-objective precision turning using Grey relational analysis”. Procedia Engineering. Vol. 97, pp. 299-307, (2014).
 [19] B. M. Gopalsamy, B. Mondal, and S. Ghosh, “Optimization of machining parameters for hard machining: Grey relational theory approach and ANOVA” International. Journal of Advanced Manufacturing Technology, Vol. 45, pp. 1068-1086, (2009).
[20]   A. H. Suhail, N. Ismail, S. V.  Wong and N. A. A. Jalil, “Surface roughness identification using the grey relational analysis with multiple performance characteristics in turning operations” Arabian Journal of  Science and Engineering Vol. 37,  No.  4, pp. 1111-1117, (2012).
[21]   K. R. Sivaraos, Milkey, A. R. Samsudin, A. K. Dubey, P. Kidd, “Comparison between Taguchi Method and Response Surface Methodology (RSM) in Modeling CO2 Laser Machining” Jordan Journal of Mechanical and Industrial Engineering, Vol. 8, No. 1, pp. 35-42, (2014).
 [22] J. Deng, The essential methods of grey systems, (Huazhong University Press, Wuhan) (1992).
 [23]  Saadat  Ali  Rizvi,  SP  Tewari,  “Multi Objective Optimization by Application of Taguchi Based Grey Relational Analysis for GMA Welding of IS2062 Structural Steel”, Mechanics and Mechanical Engineering, Vol. 21, No. 3, pp. 717–729,(2017).