Recent Development in Friction Stir Welding Process: A Review

Soori, Mohsen; Asmael, Mohammed; Solyalı, Davut

doi:10.4271/05-14-01-0006

Cited by 31 publications

(26 citation statements)

References 107 publications

(254 reference statements)

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“…Although much research has been conducted to illustrate the phenomenon of temperature and material flow gradients in thick plate welds and to investigate the variation in microstructure and properties, it is crucial to study the effects of temperature and material flow gradients on the welding efficiency for thick plate FSW. Heat input, material flow, and mechanical properties are under the influence of the tool design [ 20 , 21 , 22 , 23 ]. However, there are some differences in the role of pins in thick and thin plates.…”

Section: Introductionmentioning

confidence: 99%

Effect of Temperature and Material Flow Gradients on Mechanical Performances of Friction Stir Welded AA6082-T6 Joints

Wang

et al. 2022

Materials

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The temperature and material flow gradients along the thick section of the weld seriously affect the welding efficiency of friction stir welding in medium-thick plates. Here, the effects of different gradients obtained by the two pins on the weld formation, microstructure, and mechanical properties were compared. The results indicated that the large-tip pin increases heat input and material flow at the bottom, reducing the gradient along the thickness. The large-tip pin increases the welding speed of defect-free joints from 100 mm/min to 500 mm/min compared to the small-tip pin. The ultimate tensile strength and elongation of the joint reached 247 MPa and 8.7%, equal to 80% and 65% of the base metal, respectively. Therefore, reducing the temperature and material flow gradients along the thickness by designing the pin structure is proved to be the key to improving the welding efficiency for thick plates.

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Section: Introductionmentioning

confidence: 99%

Effect of Temperature and Material Flow Gradients on Mechanical Performances of Friction Stir Welded AA6082-T6 Joints

Wang

et al. 2022

Materials

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“…Soori et al provide assessment and improvement of CNC machining in digital settings using virtual machining methods and processes [17][18][19][20]. Soori et al provide a review of current developments in friction stir welding operations in order to examine and improve efficiency in the process of component manufacturing employing welding techniques [21]. Soori and Asamel investigated applications of simulated milling systems to reduce residual stress and deflection error throughout five-axis end milling of turbine blades [22].…”

Section: -Introductionmentioning

confidence: 99%

NURBS Interpolation Algorithm to Minimize Chord Error in 5-Axis CNC Milling Operations of Turbine Blades

Soori

Arezoo

2022

Preprint

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5-Axis CNC machining operations are added to create complicated items with free form surfaces, such as turbine blades. Virtual machining systems are used in machining processes to improve the precision of manufactured products. Chord errors can be caused by cutting tool paths with a set feed rate in 5-Axis machining processes of turbine blades with free form surfaces. As a consequence, chord errors should be studied and eliminated in order to obtain the appropriate precision in machined products with free form surfaces. The research work proposed a virtual machining system to reduce chord error in 5-Axis milling of free form surfaces. To obtain the NURBS (Non-Uniform Rational B-Splines) profiles of cutting tool paths with abilities of control points modification along machining operations, the curved surface interpolation algorithm during turbine blade five axes milling processes is implemented. Then, a NURBS interpolation algorithm with restricted chord error and control of acceleration is developed in the study to minimize chord error in machined parts with free form surfaces. Finally, the sample turbine blade is machined by using the 5-Axis CNC milling and the chord error along machining paths are measured by using the CMM machine. As a consequence,, the proposed virtual machining system can provide an efficient device for boosting the machined components accuracy with free form surfaces by employing 5-Axis CNC milling machines.

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“…To obtain the joint with higher strength, more and more experimental design methods have been introduced into the parameter optimization of FSW process, such as response surface methodology (Kim et al, 2010) and Taguchi method (Chanakyan and Sivasankar, 2020). Compared with these experimental design methods, the combination of artificial neural network (ANN) and population-based intelligence algorithm has greater advantages in parameter prediction and hybrid multi-objective optimization, which can find out the better process parameters combination to improve the strength of welding joint (Soori et al, 2021;Asmael et al, 2022). Song et al (2020) used radial basis function (RBF)-grey wolf optimizer (GWO) system to optimize the welding process parameters of Al/Mg dissimilar alloys FSW.…”

Section: Introductionmentioning

confidence: 99%

Improving the tensile strength of non-keyhole friction stir lap welding joint of 2024-T4 Al alloy by radial basis function neural network and improved particle swarm optimization algorithm

Sun

et al. 2022

Front. Mater.

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The non-keyhole friction stir lap welding (N-KFSLW) technology assisted by the outer stationary shoulder and the inner upper half-thread rotating pin was proposed to obtain the welding joint without keyhole through one-time process. Choosing 2024 aluminum alloys as the research object, the formation, microhardness and tensile strength of N-KFSLW joint were investigated. The improved particle swarm optimization (IPSO) algorithm was newly developed and had the advantages of large convergence speed and strong search ability, by which the radial basis function (RBF) neural network was optimized to enhance its prediction accuracy. After that, the RBF and IPSO (IPSO-RBF) system was used to predict the joint strength and optimize the process parameters combination. The results showed that the lap joint had not only the SZ with the thickness almost equal to the thickness of upper sheet but also the cold lap with a very small height, thereby leading to the high tensile strength of joint. The optimized parameters of welding speed, rotating speed and pin type by the IPSO-RBF system were respectively 612 rpm, 80 mm/min, and upper half-thread pin, and the tensile strength of lap joint reached 11.88 kN/mm. The N-KFSLW technology assisted by upper half-thread pin provides an effective way to obtain the lap joint with high performance, and the IPSO-RBF system can be used to maximize the strength of welding joint.

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Recent Development in Friction Stir Welding Process: A Review

Cited by 31 publications

References 107 publications

Effect of Temperature and Material Flow Gradients on Mechanical Performances of Friction Stir Welded AA6082-T6 Joints

Effect of Temperature and Material Flow Gradients on Mechanical Performances of Friction Stir Welded AA6082-T6 Joints

NURBS Interpolation Algorithm to Minimize Chord Error in 5-Axis CNC Milling Operations of Turbine Blades

Improving the tensile strength of non-keyhole friction stir lap welding joint of 2024-T4 Al alloy by radial basis function neural network and improved particle swarm optimization algorithm

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