Multi-objective optimization of friction welding parameters in AISI 304L austenitic stainless steel and copper joints

Shanjeevi, C.; Kumar, Sudhanshu; Sathiya, P.

doi:10.1177/0954405414555590

Cited by 24 publications

(13 citation statements)

References 12 publications

(13 reference statements)

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“…Copper-SS joints have been produced by using various solid state or fusion welding processes. Solid state welding processes like diffusion welding, friction stir welding (FSW), and explosive welding have been extensively used [3][4][5][6][7][8]. In diffusion welding of copper-SS, the interlayer material, applied temperature, and pressure, etc.…”

Section: Introductionmentioning

confidence: 99%

“…Imani et al [7] for FSW of copper-SS joints reported that off-setting of the pin toward copper side by 30% produced defect free welds with better tensile strength. Shanjeevi et al 2016 [8] reported that friction pressure is the most significant process parameter of FSW followed by pin rotational speed affecting the resultant microstructure and tensile properties of copper-SS joints. For fusion welding of copper-SS, different arc welding processes and high energy density Laser Beam Welding (LBW) or Electron Beam Welding (EBW) processes have been used.…”

Section: Introductionmentioning

confidence: 99%

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X-ray tomography study on porosity in electron beam welded dissimilar copper–304SS joints

Kar

Dinda

Roy

et al. 2018

Vacuum

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Dissimilar joining of copper (C10300) to AISI-304 Stainless Steel (SS) sheets was performed using Electron Beam Welding (EBW) process. EBW was performed for two weld conditions such as with beam oscillation and without beam oscillation. X-ray Computed Tomography (XCT) technique was used for three-Dimensional (3D) visualization and quantification of porosity in the weld region. It was observed that the application of beam oscillation resulted in less porosity and the average pore size was found to be smaller as compared to without beam oscillation condition. Also, pores were found to be uniformly distributed in the weld incase of with beam oscillation as compared to without beam osicllaition condition. Further, it was observed that there exists an optimum beam oscillation diameter beyond which there is no positive effect of beam oscillation in controlling the porosity formation in the weld joint.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

X-ray tomography study on porosity in electron beam welded dissimilar copper–304SS joints

Kar

Dinda

Roy

et al. 2018

Vacuum

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“…Analysis of the effectiveness of the models for Hardness, Impact strength and Tensile strength responses performed by the help of R 2 (coefficient of determination, R 2 ) values. R 2 (Coefficient of determination) is used to check the goodness of the model; it determines how close the predicted values with the experimental values [36,[41][42][43][44]. When R 2 approaches to the value of 1, implying the response models have closely resembled the actual (experimental) data.…”

Section: R-testmentioning

confidence: 99%

Investigation on the effect of mechanical vibration in mild steel weld pool

Singh

2019

Manufacturing Rev.

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This study presents a new concept of a vibratory welding setup which can transfer the mechanical vibrations in the weld zone during Shielded Metal Arc welding (SMAW) process and can also produce the resonance frequency of 300 Hz. In the present investigation mild steel plates of 6 mm thickness has been butt welded using both conventional and vibratory welding conditions. Microstructure and the mechanical properties of the butt welded joints were evaluated, and the results were compared. Further, in order to optimize the process parameters of vibratory welding technique Taguchi and analysis of variance (ANOVA) technique have been adopted. The responses considered for analysis are hardness, ultimate tensile strength (UTS) and impact strength. The result of the study indicates that by applying the vibratory treatment during welding process the mechanical properties such as hardness, tensile strength and impact strength have been enhanced. Lastly, the obtained results are correlated from the results in the past researches.

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“…1., shows the uniform distribution of the composite particles in the metal matrix aluminium alloy AA7075 + 10 % vol SiCP-T6. Friction welding on the cast rods of AA7075 + 10 % vol SiCP-T6 had been done on the continues drive friction welding using the Taguchi's L27 orthogonal array framed by taking the four process parameters such SS, FP, UP and BOL with three level in each of them [11] as shown in the Table 2. The samples were then friction welded as per the Taguchi's L27 orthogonal array shown in the Table 3.…”

Section: Materials Preparation and Friction Weldingmentioning

confidence: 99%

Multi-objective Optimization of Friction Welding Process Parameters using Grey Relational Analysis for Joining Aluminium Metal Matrix Composite

Sundararajan

Shanmugam²

2018

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Aluminium metal matrix composites has gained importance in recent time because of its improved mechanical and metallurgical properties. The welding of aluminium metal matrix composites using conventional welding process has got many demerits so in order to overcome them a solid state welding process is to be employed. To achieve a good strength, weld in the aluminium metal matrix composite bars an efficient and most preferred technique is friction welding. In this work the aluminium metal matrix composite AA7075 + 10 % vol SiC-T6 is selected and friction welded. The combination of friction welding process parameters such as spindle speed, friction pressure, upset pressure and burn-off-length for joining the AA7075 + 10 % vol SiCP-T6 metal matrix composite bars are selected by Taguchi's design of experiment. The optimum friction welding parameters were determined for achieving improved ultimate tensile strength and the hardness using grey relational analysis. A combined grey relational grade is found from the determined grey relational coefficient of the output responses and the optimum friction welding process parameters were obtained as spindle speed-1200 rpm, friction pressure-100 MPa, upset pressure-250 MPa, Burn-off-Length-2 mm. Analysis of variance (ANOVA) performed shows that the friction pressure is the most significant friction welding parameter that influences the both the ultimate tensile strength and hardness of friction welded AA7075 + 10 % volSiCP-T6 joints. The fractured surface under microstructure study also revealed good compliance with the grey relational grade result.

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Multi-objective optimization of friction welding parameters in AISI 304L austenitic stainless steel and copper joints

Cited by 24 publications

References 12 publications

X-ray tomography study on porosity in electron beam welded dissimilar copper–304SS joints

X-ray tomography study on porosity in electron beam welded dissimilar copper–304SS joints

Investigation on the effect of mechanical vibration in mild steel weld pool

Multi-objective Optimization of Friction Welding Process Parameters using Grey Relational Analysis for Joining Aluminium Metal Matrix Composite

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