Multi-response optimization of process parameters in friction stir welding of dissimilar aluminum alloys by Grey relation analysis (AA 6061-T6 &amp; AA5083-H111)

Elatharasan, G.; Manikandan, R.; Karthikeyan, G.

doi:10.1016/j.matpr.2020.06.353

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…The GRG is calculated by summing the weighted grey relational coefficients obtained from GRA. The coefficients are determined using optimal weights for each performance characteristic, as depicted in equation (16).…”

Section: Grg Creationmentioning

confidence: 99%

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Process parameters settings of friction stir welding using multi-response optimization for aluminum alloys

Pandav,

Patil,

Pandipati

2024

Eng. Res. Express

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The defense and aerospace industries utilize the AA2050, an aluminum-lithium alloy of the third generation. Principal component analysis (PCA) and Taguchi-grey relational analysis (GRA) are utilized in this study to enhance the process constraints for friction stir welding (FSW). The quality of the weld can be influenced by various process factors such as the speed at which the weld is traversed, the speed at which the tool is rotated, the angle at which the tool is tilted, the diameter of the shoulder, and the shape of the tool pin. The combination of PCA and the well-known Taguchi-GRA approach enables the objective estimation of response weights. Here, a Taguchi L16 orthogonal array was designed, and sixteen tests were carried out using it. These experiments were conducted with various assessments including tensile strength, yield strength, elongation percentage, hardness of the weld zone, bending load, etc. Through the utilization of Taguchi-GRA-PCA analysis, the most suitable process parameters were identified as a traverse speed (TS) of 160 mm/min, a rotating speed (RS) of 900 rpm, a tilt angle (TA) of 2 degrees, a shoulder diameter (SD) of 16 mm, and with a straight square tool pin profile (TPP). ANOVA revealed the relevance of all five characteristics, with rotational speed being the most influential, accounting for 43.56% of the entire result. A confirmation experiment done under ideal conditions revealed a significant improvement in total weld quality of 19.06%.

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Section: Grg Creationmentioning

confidence: 99%

“…The bending load S/N ratio was analyzed using ANOVA, and the findings are presented in table 16. The significant parameters were tool pin profile and rotational speed, with p-values below 0.05.…”

Section: Effect Of Process Parameters On Bending Loadmentioning

confidence: 99%

Process parameters settings of friction stir welding using multi-response optimization for aluminum alloys

Pandav,

Patil,

Pandipati

2024

Eng. Res. Express

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“…The composite Al7075 + 9% SiC + 1% MoS2 exhibited the highest values. The main objective of the study [20,21] is to improve the process parameters in friction stir welding of dissimilar aluminum alloys (AA 6061-T6 & AA5083-H111) by utilizing Grey relation analysis. To examine the microstructure and identify any welding flaws, the scanning electron microscope was utilized.…”

Section: Introductionmentioning

confidence: 99%

Material selection for milling fixture of friction stir welding using simulia

Pandav,

Patil,

Pandipati

2024

Eng. Res. Express

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Friction stir welding is an innovative welding technique that joins two different materialswithout the need for consumables. The process involves a profiled probe and shoulder toolthat is rotated and plunged between the two workpieces at the interface during the friction stirprocess. The weld zone undergoes dynamic recrystallization, resulting in a strong bondbetween the materials. This method offers superior bonding compared to traditional arcwelding. In the context of conventional or non-traditional milling machines, friction stirwelding is performed. It is necessary to use a milling fixture to attach the plates that need tobe butt and lap welded, fixture can be used in underwater FSW. To ensure the workpiece issecurely held in place, a fixture or holder is necessary. In this article, friction-stir welding,and a fixture with a clamping setup are constructed. The fixture is carefully designed toconsider the movement of the instrument and workpiece, and it is manufactured usingCatiaV6 3D experience software. The fixture is then subjected to three different types oftesting using Simulia software. The materials tested include cast iron, die steel, and tool steel.After simulation analysis, the best material for friction-stir welding operations is selected.

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“…The authors have studied the impact of various tool pin diameter, weld speed, and spinning speed during the welding process and found that both welding speed, tool spinning speed were the most significant FSW parameter affecting the output parameters. Elatharasan et al [6] developed the statistical model of FSW process parameters for the materials AA6061 and AA5083 through grey relational analysis. They obtained high quality welds of FSW on the dissimilar alloy by adopting optimum process parameters.…”

Section: Introductionmentioning

confidence: 99%

Microstructure, Mechanical and Corrosion Behavior of Friction Stir Processed AA6082 with Cr3C2 Particles

Bharathikanna¹,

Elatharasan²

2022

Soldag. insp.

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Friction stir processing (FSP) is a novel method of metal surface modification during the process by the addition of strengthening particles. FSP produced refined microstructures with the development of added ceramic particles on surface metal. In this FSP, mechanical characteristics were enhanced by FSP parameters, tool spinning speed, traverse speed and the axial force of high carbon high chromium die steel (non-consumable tool). In this research, FSP technique was employed on the surface of the base metal AA6082 aluminium alloy to modify composites of metal surface utilizing Cr3C2 particles. Mechanical properties like tensile strength, processed surface hardness and microstructure were studied. This research mainly focused on the parametric optimization of FSP on AA6082 with multiple responses (tensile strength and processed surface hardness) based on Taguchi L9 orthogonal array and grey relational analysis (GRA). The significant FSP parameters were obtained by grey relational grade (GRG) with an analysis of variance tool. Axial force and traverse speed were the most significant FSP parameters, which the most influence of performance characteristic of friction stir processed specimens. The predicted values were validated by confirmation test at setting of optimum level exhibits better conformity with investigational values. Field Emission Scanning Electron Microscope (FESEM) was carried out to determine the presence of strengthening particles in the processed Aluminium alloy.

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Multi-response optimization of process parameters in friction stir welding of dissimilar aluminum alloys by Grey relation analysis (AA 6061-T6 & AA5083-H111)

Cited by 11 publications

References 18 publications

Process parameters settings of friction stir welding using multi-response optimization for aluminum alloys

Process parameters settings of friction stir welding using multi-response optimization for aluminum alloys

Material selection for milling fixture of friction stir welding using simulia

Microstructure, Mechanical and Corrosion Behavior of Friction Stir Processed AA6082 with Cr3C2 Particles

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