1. J. Yawar and H. Lal, Effect of Various Parameters on Flux Consumption, Carbon and Silicon in Submerged Arc Welding (Saw), Int. J. Emerg. Technol. 6(2) (2015) 176–180.
2. R.P. Singh, R.K. Garg, and D.K. Shukla, Mathematical modeling of effect of polarity on weld bead geometry in submerged arc welding,
J. Manuf. Process. (2016) 21 14–22. https://doi.org/10.1016/j.jmapro.2015.11.003
[CROSSREF]
3. L.H. Barbosa, P.J. Modenesi, L.B. Godefroid, and A.R. Arias, Fatigue crack growth rates on the weld metal of high heat input submerged arc welding,
Int. J. Fatigue. (2019) 119 43–51. https://doi.org/10.1016/j.ijfatigue.2018.09.020
[CROSSREF]
4. T. Tsuyama, K. Nakai, and T. Tsuji, Development of submerged arc welding method using hot wire,
Weld. World. 58(5) (2014) 713–8. https://doi.org/10.1007/s40194-014-0153-8
[CROSSREF] [PDF]
5. L.S. Derevyagina, A.I. Gordienko, A.G. А.М. Orishich Malikov, N.S. Surikova, and M. N. Volochaev, Micro- structure of intercritical heat affected zone and toughness of microalloyed steel laser welds,
Mater. Sci. Eng. A. 770 (2020) https://doi.org/10.1016/j.msea.2019.138522
[CROSSREF]
6. J. Luo, Y. Dong, L. Li, X. and, and . Wang, Microstructure of 2205 duplex stainless steel joint in submerged arc welding by post weld heat treatment,
J. Manuf. Process. 16(1) (2014) 144–148. https://doi.org/10.1016/j.jmapro.2013.06.013
[CROSSREF]
7. B. Singh, Correlation of Flux Ingredients with Width HAZ,
J. Weld. Join. 36(1) (2018) 76–81. https://doi.org/10.5781/JWJ.2018.36.1.9
[CROSSREF] [PDF]
8. C. S. Lee, R. S. Chandel, and H. P. Seow, Effect of Welding Parameters on the Size of Heat Affected Zone of Submerged Arc Welding,
Mater. Manuf. Process. 15(5) (2000) 649–666. https://doi.org/10.1080/10426910008913011
[CROSSREF]
9. V. Gunaraj and N. Murugan, Rediction of heat affected zone characteristics in submerged arc welding of structural steel pipes, Weld. Res. 81(3) (2002) 94–98.
10. S. Choudhary, R. Shandley, and A. Kumar, Optimization of agglomerated fluxes in submerged arc welding, Materials Today, Proc. 5(2) (2018) 5049–5057. https://doi.org/10.1016/j.matpr.2017.12.083
11. V. Gunaraja and N. Murugan, Application of Response surface methodology for predicting weld bead quality in submerged are welding of pipes,
J. Mater. Process. Technol. 88(1-3) (1997) 266–275. https://doi.org/10.1016/S0924-0136(98)00405-1
[CROSSREF]
12. M. Sailender, G. Ch, andraMohan. Reddy, and S. Venkatesh, Influences of process parameters on weld strength of low carbon alloy steel in purged SAW,
Mater. Today Proc. 5(1) (2018) 2928–2937. https://doi.org/10.1016/j.matpr.2018.01.088
[CROSSREF]
13. A. Kumara, S. Maheshwarib, and S. Kumar, Sharma Fuzzy Logic Optimization of Weld Properties for SAW Using Silica Based Agglomerated Flux,
Proc. Comput. Sci. (2015) 57 1140–1148. https://doi.org/10.1016/j.procs.2015.07.403
[CROSSREF]
14. S. Jindal. Krishankant and S. Kant, Shekhar Determination of Flux Consumption in Submerged arc Welding by the Effect of Welding Parameters by Using R .S.M Techniques, Global J. Res. Eng. Mech. Mech. Eng. 12(2) (2012) 21–24.
15. M. Muthu, J. Krishnan Maniraj, R. Deepak, and K. Anganan, Prediction of optimum welding parameters for FSW of aluminium AA6063 alloys and A319 using RSM and ANN,
Mater. Today:Proc. 5(1) (2018) 716–723. https://doi.org/10.1016/j.matpr.2017.11.138
[CROSSREF]
16. N. Singh, B.C. Routara, and D. Das, Study of machining characteristics of Inconel 601in EDM using RSM,
Mater. Today:Proc. 5(2) (2018) 3438–3449. https://doi.org/10.1016/j.matpr.2017.11.590
[CROSSREF]
17. H. Myers and D. C. Montgomery. Response surface me- thodology, process and product optimization using design experiments. NJ: John Wiley &Sons Inc Hoboken, USA; (2009), p. 349–362
18. S. Reddy, K. Vempati, Brahma. Raju, and K. Venkata, Subbaiah Optimization of Welding Parameters of Ti 6al 4v Cruciform shape Weld joint to Improve Weld Strength Based on Taguchi Method,
Mater. Today:Proc. 5(2) (2018) 4948–4957. https://doi.org/10.1016/j.matpr.2017.12.072
[CROSSREF]
19. T. H. Hou, C. H. Su, and W. L. Liu, Parameters optimization of a nano-particle wet milling process using the Taguchi method, response surface method and genetic algorithm,
Powder Technol. 173(3) (2007) 153–62. https://doi.org/10.1016/j.powtec.2006.11.019
[CROSSREF]
20. A. Alafaghani and A. Qattawi, Investigating the effect of fused deposition modeling processing parameters using Taguchi design of experiment method,
J. Manuf. Proc. (2018) 36 164–174. https://doi.org/10.1016/j.jmapro.2018.09.025
[CROSSREF]
21. A. B. Naik and A. C. Reddy, Optimization of Tensile Strength in TIG Welding Using Method Taguchi and Analysis of Variance (ANOVA),
Therm. Sci. Eng. Prog. 8 (2018) 327–339. https://doi.org/10.1016/j.tsep.2018.08.005
[CROSSREF]