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A Computational approach in optimizing process parameters influencing the heat input and Depth of Penetration of Tungsten Inert Gas welding of Austenitic Stainless Steel(AISI 316L) using Response Surface Methodology

Publication Type : Journal Article

Publisher : International Conference on Advances in Materials and Manufacturing Applications, IConAMMA 2018,

Source : International Conference on Advances in Materials and Manufacturing Applications, IConAMMA 2018, 16th -18th August, 2018, India, Volume 24, p.1199 - 1209 (2020)

Url : https://www.sciencedirect.com/science/article/pii/S221478532033056X

Keywords : AISI 316L stainless steel, Optimization, Response surface methodology (RSM)

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2020

Abstract : Austenitic stainless steel (AISI 316L) possesses high strength, and corrosion resistance finds application as a major base material for the manufacturing of boilers, chemical reactors, etc. Tungsten Inert Gas Welding (TIG) is a common process used for making joints in the fabrication industries like chemical, railway coaches, and automobile parts. In this work, Austenitic Stainless steel plates of Size 200 x 100 x 5 mm undergoes conventional TIG process. The input parameters set for the study was Welding Current, Welding Speed and Gas flow rate and the output response chosen for the study was Depth of Penetration (DOP) and Heat Input. Central Composite design, a common response surface methodology of Design Experimentation was used to conduct the welding trials. ANOVA was conducted to find a relation between the input and the output with a certainty level of 95%. A full quadratic response surface regression model was developed between Depth of Penetration (DOP), Heat Input and welding current, Welding Speed, and gas flow rate. It was found DOP there exists a linear relation for the input parameters. The Heat input model shows a quadratic relation exists between welding current, welding speed, and output response. The model accuracy was 95.29% for DOP and 99.43% for Heat input. The difference between R-sq. and R-sq. (adj) was less than 2% for both the cases which indicates the model accurately resembles the experimental parameters chosen for the study. Desired depth & heat were accomplished at an optimum current of 185 A, welding speed of 50.11 mm/min and gas flow rate of 13.1 l/min.

Cite this Research Publication : M. John Varkey, A. Sumesh, and K Kumar, R., “A Computational approach in optimizing process parameters influencing the heat input and Depth of Penetration of Tungsten Inert Gas welding of Austenitic Stainless Steel(AISI 316L) using Response Surface Methodology”, International Conference on Advances in Materials and Manufacturing Applications, IConAMMA 2018, 16th -18th August, 2018, India, vol. 24, pp. 1199 - 1209, 2020.

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