Advances in artificial intelligence (AI) techniques that can be used for different purposes have enabled it to be used in many different industrial applications. These are mainly used for modeling, identification, optimization, prediction and control of complex systems under the influence of more than one parameter in industrial applications. With the increasing accuracy of AI techniques, it has also obtained a wide application area on friction stir welding (FSW), one of the production methods developed in recent years. In this study, commonly used AI techniques for FSW, results, accuracy and superiority of AI techniques are reviewed and evaluated. In addition, an overview of AI techniques for FSW in different material combinations is provided. Considering the articles examined; It is seen that welding speed, rotational speed, the plunge depth, spindle torque, shoulder design, base material, pin design/profile, tool type are used as input parameters and tensile strength, yield strength, elongation, hardness, wear rate, welding quality, residual stress, fatigue strength are used as output parameters. As can be seen from the studies, it made important contributions in deciding what input parameters should be in order to have the output parameter at the desired value. The most common used materials for FSW are Al, Ti, Mg, Brass, Cu and so on. When FSW studies using artificial intelligence techniques were examined, it was seen that 81% of the most used materials were AL alloys and 23% of them were made with dissimilar materials. The most commonly utilized AI techniques were said to be artificial neural networks (ANN), fuzzy logic, machine learning, meta-heuristic methods and hybrid systems. As a result of the examination, ANN was the most widely used method among these methods. However, in recent years, with the exploration of new hybrid methods it was seen that hybrid systems used with ANN have higher accuracy.

Artificial Intelligence Applications for Friction Stir Welding: A Review

Bobbin tool friction stir welding (BT-FSW) is a promising solid-state welding process for fabricating closed or hollow profiles due to its self-supporting nature, which is achieved using a combined tool consisting of two shoulders and a penetrating pin, releasing the backing plate. The joint reliability is mainly affected by its macro-/micro-features including geometric defects and non-uniform grains. However, the underlying thermo-physical process has not been fully understood to clarify how the defects form and grains evolve during welding and how to control them. In this paper, a 3D thermo-mechanically coupled Eulerian-Lagrangian model was developed to analyze the material flow behavior and help understand the defect forming mechanism and recrystallization behavior during BT-FSW of aluminum alloy, wherein tracing particles were specially embedded. The calculated results revealed a complex material migration in the domain driven by the rotating tool. The flow behavior in horizontal/vertical directions at local regions was asynchronous, and eventually converged on the advancing side (AS) to normally form a sound joint, where the combined effects of shearing and squeezing of the material flow throughout thickness affected the morphology of S-line defect. In addition, the non-uniform thermo-mechanical cycling caused an abrupt change in grain structure near the TMAZ/SZ-AS transition region due to the combined continuous and discontinuous dynamic recrystallization, and geometrical effect of strain. The final joint failure was the result of competition between the two softening regions, S-line defect and TMAZ/SZ-AS. These can be applied for further fundamental investigation of parameter optimization or welding structure design, and promote the exploration of post-processing methods to improve the joint performance.

In-depth understanding of material flow behavior and refinement mechanism during bobbin tool friction stir welding

A novel material processing approach using the bobbin tool technique called bobbin tool friction stir processing (BTFSP) was developed to simultaneously fabricate two-side composites. The feasibility of simultaneous fabrication of composites on the top and bottom sides of the workpiece using B4C reinforcement particles into Al 6061 alloy was successfully studied in the present paper. Excellent dispersion of the B4C particles obtained at the bottom side of the workpiece by this technique. The metallurgical investigation of Al 6061/B4C double side composites was carried out using optical and scanning electron microscopy. The mechanical properties include sliding wear behavior, and microhardness of the fabricated composites was studied in detail. The results indicated a more uniform distribution of B4C particles with 3 passes. The grain refinement and homogeneous distribution of the B4C significantly improved microhardness and wear properties of the fabricated composites compared to as-received Al.

Dual sided composite formation in Al 6061/B4C using novel bobbin tool friction stir processing

Flow-coupled thermo-mechanical analysis of frictional behaviors at the tool-workpiece interface during friction stir welding

Welding dissimilar alloys of aluminium are quite cumbersome due to their lower melting temperatures and difficulty in welding. To resolve this, solid-state procedure friction stir welding (FSW) is utilized largely in industries. In this present research, dissimilar aluminium alloys AA2014 and AA6063 is joined using the FSW procedure to achieve higher yield strength, ultimate tensile strength and microhardness. Experiments were planned as per response surface methodology (RSM) based central composite design (CCD), for four input parameters (tool pin profile, rotational speed, axial force and traverse speed). Micrographs of the weld show grain refinement and proper fusion of materials which increases the mechanical strength and bonding. Outcomes from the experiment show that the considered input parameters significantly influence all the outputs. The optimum condition was evolved from multiobjective optimization procedure using desirability approach (DA) which are 1010 rpm rotating tool speed, 25 mm min−1 as tool traverse speed, 7 kN of axial force with triangular pin profile. The second-order regression model predicts the output responses with lower residuals and the confirmation experiment outputs produces a maximum deviation of 7.94% with investigational outcomes with optimum condition. Micrographs shows that the heat affected zone (HAZ) region is free from voids, oxides, and cracks. The nugget zone has the flow of materials from both the base metals and the flow track is clearly visible.

Influence of process parameters on the microstructure and mechanical properties of friction stir welds of AA2014 and AA6063 aluminium alloys using response surface methodology

The microstructure and mechanical properties of bobbin tool friction stir welded joints for 2219-T87 aluminum alloy using different welding speeds were investigated based on the experimental results together with a thermo-mechanical model developed. The stir zone created in the joint shows a dumbbell shape. As welding speed increases, both the width and grain size of stir zone decrease. The symmetrical hardness distribution forms across the joint thickness, while the asymmetric hardness is measured along the width of the stir zone. The hardness of the stir zone on the retreating side is lower than that on the advancing side. The hardness profile presents a W-shape, with the minimum values measured increasing with welding speed. The tensile residual stresses increase gradually towards the center of the joint from the outer surface, presenting a symmetrical feature as well. As welding speed increases, both the tensile strength and elongation show a maximum value 70% of joint efficiency. Tensile fracture occurs in the stir zone and shows a symmetrical surface with three different layer fracture modes identified. In layers I and III, the fracture surface presents 45° direction, while fracture propagates along the S-line in layer II.

Investigation on the Effects of Welding Speed on Bobbin Tool Friction Stir Welding of 2219 Aluminum Alloy

Effect of material configuration and welding parameter on weld formability and mechanical properties of bobbin tool friction stir welded Al-Cu and Al-Mg aluminum alloys

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Investigation on the Effects of Welding Speed on Bobbin Tool Friction Stir Welding of 2219 Aluminum Alloy

Effect of material configuration and welding parameter on weld formability and mechanical properties of bobbin tool friction stir welded Al-Cu and Al-Mg aluminum alloys