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Parametric Optimization of MIG Welding on 316L Austenitic Stainless Steel by Taguchi Method

Nabendu Ghosh, Pradip Kumar Pal, and Goutam Nandi
Mechanical Engineering Department, Jadavpur University, Kolkata 700032, W.B, India
Abstract—Weld quality mainly depends on features of bead geometry, mechanical-metallurgical characteristics of the weld as well as on various aspects of weld chemistry and these features are expected to be greatly influenced by various input parameters like current, voltage, electrode stick-out, gas flow rate, edge preparation, position of welding, welding speed and many more in metal inert gas (MIG) welding. Moreover, the cumulative effect of the mentioned quality indices determines the extent of joint strength that should meet the functional aspects of the weld in practical field of application. Therefore, preparation of a satisfactory good quality weld seems to be a challenging job. The welding investigators have always been in search for better quality of weldment. In present work, effect of current, gas flow rate and nozzle to plate distance on quality of weld in metal gas arc welding of Austenitic stainless steel AISI 316L has been studied through experiment and analyses. Butt welded joints have been made by several levels of current, gas flow rate and nozzle to plate distance. A plan of experiments based on Taguchi technique has been used. An Orthogonal array, Signal to Noise (S/N) ratio and analysis of variance (ANOVA) are employed to study the welding characteristics of material & optimize the welding parameters. The result computed is in form of contribution from each parameter, through which optimal parameters are identified for maximum tensile strength and percentage elongation.
 
Index Terms—MIG welding, AISI 316L austenitic stainless steel: X-ray radiographic test, tensile test, taguchi method, ANOVA, Signal to Noise (S/N) ratio, optimization

Cite: Nabendu Ghosh, Pradip Kumar Pal, and Goutam Nandi, "Parametric Optimization of MIG Welding on 316L Austenitic Stainless Steel by Taguchi Method," International Journal of Mechanical Engineering and Robotics Research, Vol. 6, No. 2, pp. 88-95, March 2017. DOI: 10.18178/ijmerr.6.2.88-95
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