The selection of optimum process parameters on A319 aluminum alloy in friction stir welding MCDM method

Marichamy, M.; Babu, S. S.

doi:10.1016/j.matpr.2020.05.080

Cited by 9 publications

(3 citation statements)

References 10 publications

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“…This technique is currently being discussed. Marichamy et al 26 Using the ARAS approach, we were able to determine the best process parameters for welding A319 aluminium alloy. For joining the component.…”

Section: Resultsmentioning

confidence: 99%

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Marichamy

Chockalingam

2023

Proceedings of the Institution of Mechanical Engineers, Part E:

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The major goal of this study is to look into friction stir welding process parameter optimization with the combined decision model, the tensile strength of the best parameter combinations is higher. The recommended hybrid strategy for order preference by similarity to ideal solution (technique for order of preference by similarity to an ideal solution) and grey relational analysis method are used to discover the optimum process parameters. It is also suitable for welding aluminium alloy A319 is Tool rotational speed (r/min), Feed for welding (mm/min), and diameter of tool pin (mm) are all considered while using the friction stir welding process. This operation is primarily implemented through various experiments using Taguchi L9 orthogonal arrays. To this problem, the (technique for order of preference by similarity to an ideal solution) and (grey relational analysis) models are used. Hence, this technique has demonstrated the technology used to identify multi-criteria decision-making in friction stir welding and process parameter optimization for the best results.

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Section: Resultsmentioning

confidence: 99%

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Marichamy

Chockalingam

2023

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…The TiN-coated tool wear loss should be reduced to improve the FSW tool life, called non-beneficiary elements. Implementation procedure of ARAS method for this research work to obtain the best FSW characteristics [48,49]. The implementation procedure of the ARAS technique for optimizing the FSW process is illustrated in figure 9.…”

Section: Multi-criteria Optimization Using Additive Ratio Assessment ...mentioning

confidence: 99%

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Paul,

Thilagham,

K G

et al. 2024

Eng. Res. Express

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The boron carbide (B4C) reinforced AA5052-H32 aluminium composite has been initially fabricated by stir casting method. Friction stir welding (FSW) is used to join two similar AA5052-H32/B4C plates using a titanium nitride (TiN)-coated square tool. The tool wear loss, microhardness, and tensile strength of FSW joints have been investigated by the Taguchi technique. Welding parameters consist of TiN coating thickness, tool rotational speed, welding speed, and axial thrust. Taguchi analysis is used to determine the influences, contributions, and best values of welding parameters to meet optimal welding attributes. The maximum tensile strength (140.134 MPa) has been obtained by increasing the TiN coating thickness, tool's rotational speed, axial thrust, and welding speed. At the highest tool speed and axial trust, the maximum microhardness (158.3 HV) has been attained. The minimum tool wear loss (9.023 %) has been obtained by welding at a moderate speed with maximum rotational speed, axial thrust, and TiN coating thickness. Fractography and SEM analysis have been used to analyze the microstructural behaviour of welded aluminium composite materials and worn-out tool surfaces. The Additive Ratio Assessment (ARAS) multi-criteria optimization technique has been applied to predict the best welding parameters to attain the optimal welding characteristics. The 40 µm TiN coating thickness, 1200 rpm tool rotation, 20 mm/min welding speed, and 6000N axial force are predicted to achieve 108.6 MPa tensile strength, 110 HV microhardness, and 9.37% tool wear loss.

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“…According to their findings, land-based wind energy systems are rated highest in terms of sustainability pointers and sub-points, followed by solid oxide and then phosphoric acid fuel cells, with polycrystalline solar energy systems rated last. Marichamy et al [21] found the optimal process parameters and appropriate for the welding operation of A319 Aluminum alloy using the ARAS method. The optimum arrangement of joining consideration welding feed is 40 mm/min, the rotation speed is 700 rpm, and tool pin diameter is 6 mm for joining the component.…”

Section: Several Researchers Have Implemented the Multi-criteria Deci...mentioning

confidence: 99%

Optimization of atomized spray cutting fluid eco-friendly turning of Inconel 718 alloy using ARAS and CODAS methods

Sivalingam

Poogavanam

Natarajan

et al. 2022

Int J Adv Manuf Technol

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Atomized spray cutting fluid (ASCF) is a sophisticated machining technique that achieves higher productivity, enhanced surface quality, extended tool life, and cost benefits.This research aims to analyze the influence of cutting process parameters on Inconel 718 alloy turning in dry and ASCF cutting environments. The critical machining indices such as surface roughness, machining cost, power consumption, and tool life were analyzed concerning these two cooling environments. The cutting parameters were optimized using desirability functional analysis and two types of multicriteria decision making (MCDM) method, such as additive ratio assessment method (ARAS) and combinative distance-based assessment (CODAS) method, were investigated. The composite desirability index (CD) of optimum parameter setting(A2B1C2D2) is improved by 6.34 % compared to the initial parameter setting (A2B1C2D1). The optimum parameters from the MCDM technique are obtained as a cutting speed of 200 m/min, feed rate of 0.08 mm/rev, and depth of cut of 0.2 mm under ASCF environment. ASCF machining significantly minimize the surface roughness, machining cost and power consumption , maximize the tool life by about 16% , 51%, 17% and 48% respectively as compared with dry machining

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The selection of optimum process parameters on A319 aluminum alloy in friction stir welding MCDM method

Cited by 9 publications

References 10 publications

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool

Optimization of atomized spray cutting fluid eco-friendly turning of Inconel 718 alloy using ARAS and CODAS methods

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The selection of optimum process parameters on A319 aluminum alloy in friction stir welding MCDM method

Cited by 9 publications

References 10 publications

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Process parameters for friction stir welding on A319 aluminium alloy using hybrid technique for order of preference by similarity to an ideal solution and grey relational analysis multi-criteria decision-making method

Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B4C) using titanium nitride coated tool

Optimization of atomized spray cutting fluid eco-friendly turning of Inconel 718 alloy using ARAS and CODAS methods

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Product

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Multi-criteria optimization on friction stir welding of aluminum composite (AA5052-H32/B₄C) using titanium nitride coated tool