Process Parameter Optimization of A-TIG Welding on P22 Steel

Pavan, A. R.; Arivazhagan, B.; Vasudevan, M.

doi:10.1007/978-981-13-8767-8_8

Cited by 11 publications

(4 citation statements)

References 8 publications

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“…After fitting models using BBD design [20,21], response surfaces were generated using Design-Expert software, which are visual representations of 3d curves. They provide insights into the effects of welding parameters as well as their interactions on the response parameters of ΔH P11, ΔH 316LN and σmax.…”

Section: Response Surface Analysismentioning

confidence: 99%

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

Benlamnouar,

Bensaid,

Saadi

et al. 2024

Mater. Res. Express

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In this study, response surface methodology (RSM) was employed to optimize the welding parameters' effects on mechanical properties of dissimilar welds between Cr-Mo steel grade (P11) and austenitic stainless steel (AISI 316LN). To determine the best welding parameters, variance analysis (ANOVA), desirability function, and perturbation analysis were used to create regression models and identify the significant parameters influencing tensile strength and hardness gaps in the weld joints. The results indicated that welding speed is the most significant parameter affecting both the austenitic hardness gap and tensile strength, while gas flow has the most significant impact on the hardness gap of Cr-Mo steel. Furthermore, welding speed positively influences the mechanical properties of dissimilar weld, whereas welding current has a slight negative effect on tensile strength. The optimum welding parameters were found to be 130 A for welding current, 70 mm/min for welding speed, and 13 l/min for welding gas flow, resulting in hardness gap values of 18.10 HV (Stainless steel side), 27.38 HV (Cr-Mo steel side), and a tensile strength of 453.90 MPa. The optimum parameter effect is concentrated at the weld interfaces between the fusion zone and the heat-affected zone. This effect led to limitations in grain coarsening, a reduction in the martensite and delta ferrite phase percentages, a slight increase in the bainite ratio, and a decrease in carbide precipitations. As a result, a homogenization of strain distribution in the optimum weld was achieved, leading to ductile fracture in Cr-Mo steel.

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Section: Response Surface Analysismentioning

confidence: 99%

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

Benlamnouar,

Bensaid,

Saadi

et al. 2024

Mater. Res. Express

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show abstract

“…In the design of experiments (DOE), RSM is one of the main methods used to estimate unknown mechanisms by applying an empirical model. 13 Vasantharaja and Vasudevan 14 used RSM to optimize input variables by integrating model solutions and experimental data. During activated-TIG (A-TIG) welding, they determined the parameters required to achieve full penetration with a thickness of 10 mm depth in RAFM steel.…”

Section: Introductionmentioning

confidence: 99%

Process parameter optimization of hot-wire TIG welding of 10 mm thick type 316LN stainless steel plates

Neelamegam

Meenakshisundaram

Muthukumaran

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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This study aims to reduce the number of weld passes and total heat input to 316LN stainless steel during hot-wire tungsten inert gas (HW-TIG) welding process by optimizing process parameters. Therefore, the response surface methodology (RSM) of design of experiments (DOE) approach has been adopted to optimize HW-TIG welding parameters and study the interaction between the parameters and responses. In order to minimize the total number of experimental runs, a design matrix was generated with 30 sets of process parameters. The bead-on plate welding experiments were carried out based on the above generated process parameters. Using the RSM, a quadratic model was developed based on a central composite design to establish the regression equations between input variables (welding current, wire feed current, welding speed, and wire feed rate) and responses (bead width, depth of penetration, and weld cross sectional area). The input process parameters and their responses were correlated with the regression model. Further, parameter values were optimized using the desirability approach and the optimized solutions were generated. Using the optimized process parameters, 316LN stainless steel weld joints were fabricated. Tensile testing and metallography samples were extracted from the fabricated weld joints. The results reveal that the optimization of process parameters by RSM based approach reduced the number of weld passes and improved the weld quality with lower heat input to 316LN stainless steel. In addition, the fabricated weld joint of 316LN stainless steel using the optimized process parameters exhibited better microstructure and strength properties.

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“…30 A-TIG welding trials on 10 mm thick P22 steel confirmed that RSM precisely optimized process parameters for a high depth of weld penetration and low weld bead width. 31 RSM tool was effective for the successful optimization of input parameters to achieve maximum DOP in the A-TIG welding of 304L grade SASS. Research also indicated that using activating flux SiO 2 doubled weld penetration depth.…”

Section: Introductionmentioning

confidence: 99%

“…30 A-TIG welding trials on 10 mm thick P22 steel confirmed that RSM precisely optimized process parameters for a high depth of weld penetration and low weld bead width. 31…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization and experimental validation of A-TIG welding of super austenitic stainless steel AISI 904L using response surface methodology

Sunny

Korra

Vasudevan

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part E:

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Super austenitic stainless steel (SASS) is a premium stainless steel (SS) variant which finds applications in challenging environments. One of the premium grades of SS that falls under the said category is AISI 904L. Autogenous activated flux tungsten inert gas (A-TIG) welding is an established technique for fabricating sound steel joints which offers various advantages. In this context, this research aims to identify an optimum set of input process parameters to effectively employ A-TIG welding to fabricate 10 mm thick joints of SASS AISI 904L plates by employing bead on plate welding trials. The input parameters varied for the trials are welding current, torch travel speed, and percentage of Argon gas present in a mixture of Argon and Helium – which is the shielding gas used, while the responses were the depth of weld penetration (DOP) and weld bead width (BW). For finalizing the combinations of input parameters and the run order of the welding trials, the design of experiments (DOE) was performed using central composite design (CCD) of response surface methodology (RSM). After performing the trials, the DOP and BW attained were measured and the data thus generated were analyzed to study the influence of varying input parameters on the two responses. Analysis of variance (ANOVA) was then performed to check the input parameter's level of significance. RSM's desirability approach was used for numerical optimization to attain maximum DOP and a moderate BW. A linear regression equation generated can be used to precisely predict DOP and BW for any random values of input parameters. The bead on plate trial's validation study displayed root mean squared error (RMSE) values of 0.328 and 0.653 for DOP and BW respectively, The RMSE values of DOP and BW of the joint fabricated with optimized parameters was 0 and 0.311 respectively.

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Process Parameter Optimization of A-TIG Welding on P22 Steel

Cited by 11 publications

References 8 publications

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

Process parameter optimization of hot-wire TIG welding of 10 mm thick type 316LN stainless steel plates

Parameter optimization and experimental validation of A-TIG welding of super austenitic stainless steel AISI 904L using response surface methodology

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