Friction welding of similar and dissimilar materials: A review

Sathishkumar, G.B.; Sethuraman, P.; Chanakyan, C.; Sundaraselvan, S.; Arockiam, A. Joseph; Alagarsamy, S.V.; Elmariung, A.; Meignanamoorthy, M.; Ravichandran, M.; Jayasathyakawin, S.

doi:10.1016/j.matpr.2021.03.089

Cited by 10 publications

(3 citation statements)

References 30 publications

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“…Various researchers reported that the rotational speed and forge pressure extensively influence mechanical and microstructure characteristics. At the same time, strengthened particle variations on the base alloy were not findings; therefore, this investigation concentrates on one more addition to enhance the properties with the addition of nanoceramic particle (SiC) [18]. Based on the casting process, all the samples were made with SiC reinforcements with maintained parameters of stirring and time duration.…”

Section: Methodsmentioning

confidence: 99%

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Pushparaj¹,

Jeremiah²,

Solomon³

et al. 2023

Journal of Nanomaterials

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Nowadays, the aluminum metal matrix composites (AMCs) play an empirical role to improve the mechanical performance by various applications. Therefore, the secondary processes need to enhance the surface morphology of intermetallic phases with the appropriate reinforcing particles. In this research, Al7075- and ceramic-based nanosilicon carbide (SiC) were utilized to compose the metal matrix composites. These composites were subjected to friction welding for intermetallic surface modification with the various forging pressure and rotating speed. Initially, the AMCs were prepared with three (8–12) kinds of SiC weight proportions by the design of Taguchi L9 orthogonal array. As per the weight proportions, nine samples were prepared and then conducted the friction welding with 10–20 MPa of forge pressure and 1,650–2,050 rpm of rotational speed of spindle. Then, the entire nine specimens were allowed to conduct the tensile and microhardness test. During the mechanical test, the overall welded zone had higher mechanical properties than the base metal. Then, the artificial neural network was utilized to predict the output responses as per the designed concept of trial and error method. The overall predicted responses are nearly closed to the experimental values.

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Section: Methodsmentioning

confidence: 99%

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Pushparaj¹,

Jeremiah²,

Solomon³

et al. 2023

Journal of Nanomaterials

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“…However, weld defects observation and joint strength have not been reported. Since these earlier works, very few researches were published in the past three decades on dissimilar welding of Ni-Ti alloys as indicated in recent reviews [19][20][21]. There has recently been a resurgence of interest in welding Ni-Ti alloys due in particular, to the requirements for light weighting of high temperature structures in aerospace industry.…”

Section: State Of the Art Of Joining Ti-ni Based Alloysmentioning

confidence: 99%

Microstructure and chemical characterization of Linear Friction Welded aerospace materials with focus on dissimilar joints

Boyat

Ballat-Durand

Marteau

et al. 2022

IOP Conf. Ser.: Mater. Sci. Eng.

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This study is focused on a through characterization of the microstructure and chemical composition of dissimilar linear friction welded joints. First, Ti-6Al-2Sn-4Cr-2Mo (Ti6242) and Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti17) joints are described to identify the mechanisms behind the successful cohesion of the material surfaces. It was found that continuous dynamic recrystallization and cohesion took place through grain-boundary migration in a shared single phase β-domain obtained through high temperature and high strain conditions. Then, the possibility of assembling Ti6242 and Inconel 718 is examined. Chemical results combined with microstructure and crystal orientation analyses showed that the intermixing zone formed between the materials was particularly heterogeneous, with the development of an intermediate bimodal microstructure, mainly composed of Ti-β phase and Ti2Ni intermetallic phase.

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“…The use of dissimilar materials results in enhanced system performance and cost reduction, making it a top-notch engineering solution in multi-material processing. Dissimilar welding techniques have succeeded across various sectors, including automotive, electronics, aerospace, and numerous engineering domains [8][9][10]. Notably, the electrical industry has begun embracing this approach, and this is particularly evident in applications within generation, storage, and transmission systems.…”

Section: Introductionmentioning

confidence: 99%

Assessing Tensile Strength and Electrical Conductivity of Friction Stir-Welded Joints of Copper and Aluminum Alloys

Hoyos,

Serna,

Montoya

et al. 2024

Metals

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Dissimilar aluminum joints have widespread applications across various industries, including the electronics and automotive sectors, owing to their unique combination of advantages, including reduced density and enhanced mechanical properties. These characteristics make them an innovative solution for multi-material processing challenges presented in the engineering industry. This article focuses on Friction Stir-Welded butt joints made using a weld–flip–weld approach between aluminum AA6061-T6 and pure copper C11000, exploring the effects of varying rotational speeds (1000, 1200, and 1400 RPM), offsets (0 and 1 mm) in the joint soundness, mechanical strength, and electrical conductivity. The welds were evaluated using non-destructive testing with phased-array ultrasound and tensile testing. Additionally, the electrical conductivity was measured to assess their response to electrical currents. The findings reveal a significant correlation between joint efficiency and electrical conductivity, with the highest values corresponding to a weld executed with a rotational speed of 1400 rpm, traverse speed of 40 mm/min, and 1 mm offset towards the aluminum, achieving the highest joint efficiency, reaching a joint efficiency of approximately 75% and 82.42% of the IACS for electrical conductivity.

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Friction welding of similar and dissimilar materials: A review

Cited by 10 publications

References 30 publications

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Taguchi-Based Artificial Neural Network Modeling of Friction Process on Aluminum Alloy Reinforced with SiC Nanoparticles

Microstructure and chemical characterization of Linear Friction Welded aerospace materials with focus on dissimilar joints

Assessing Tensile Strength and Electrical Conductivity of Friction Stir-Welded Joints of Copper and Aluminum Alloys

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