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The criteria importance through intercriteria correlation (CRITIC) and range of value (ROV) combined methods were used to determine a single index for all multiple responses.

This paper used cold metal transfer (CMT) and pulse metal-inert gas (MIG) welding processes to study the weld-on-bead geometry of AA2099-T86 alloy. This study used Taguchi's approach to find the optimal setting of the input welding parameters. The welding current, welding speed and contact-tip-to workpiece distance were the input welding parameters for finding the output responses, i.e. weld penetration, dilution and heat input. The L9 orthogonal array of Taguchi's approach was used to find out the optimal setting of the input parameters.

The optimal input welding parameters were determined with combined output responses. The predicted optimum welding input parameters were validated through confirmation tests. Analysis of variance showed that welding speed is the most influential factor in determining the weld bead geometry of the CMT and pulse MIG welding techniques.

The heat input and weld bead geometry are compared in both welding processes. The CMT welding samples show superior defect-free weld beads than pulse MIG welding due to lesser heat input and lesser dilution.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.

The purpose of this study is to examine the effects of sensitization on the metallurgical characteristics of weld joints made up of austenitic stainless steel (AISI 316L) and ferritic stainless steel (AISI 430), using the gas tungsten arc welding (GTAW) process with ER316L filler wires.

A non-consumable tungsten electrode with a diameter of 1.6 mm was used during the GTAW procedure. The filler wire, ER316L, was selected based on the recommendation provided in literature. To explore the interconnections among the structure and properties of these weldments, the techniques including scanning electron microscopy and optical analysis have been used. In addition, the sensitization behaviour of the weldments was investigated using the double loop electrochemical potentio-kinetic reactivation (DLEPR) test.

Microstructural analyses revealed the occurrences of coarsened grains with equiaxed columnar grains and migrating grain boundaries in the weld zone. The results of the DLEPR test demonstrated that heat affected zone (HAZ) of AISI 430 was more susceptible to sensitization than HAZ of AISI 316L. Microstructure analysis also revealed the precipitation of large amounts of chromium carbide at the grain boundaries region of AISI 430 welded steel, causing more sensitization and, as a result, more failure or breaking at the side of AISI 430 weld in the dissimilar weldment of AISI 316L–AISI 430.

The present work has been carried out to determine the appropriate welding conditions for joining AISI 316L and AISI 430, as well as the metallurgical properties of the dissimilar weldment formed between AISI 316L and AISI 430. Owing to the difficulties in measuring the performance of these types of dissimilar joints given their unique mechanical and microstructural characteristics, research on the subject is limited.

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

This study aims to identify the primary research areas of modern methods of construction (MMC) along with its current trends and developments.

A combination of bibliometric and qualitative analysis is adopted to examine 1,957 MMC articles in the Scopus database. With the support of CiteSpace 6.1.R6, the clusters, leading authors, journals, institutions and countries in the field of MMC are examined.

Offsite construction, inter-modular connections, augmenting output, prefabricated concrete beams and earthquake-resilient prefabricated beam–column steel joints are the top five research areas in MMC. Among them, offsite construction and inter-modular connections are significantly focused, with many research articles. The potential for collaboration, among prominent authors such as Wang, J., Liu, Y. and Wang, Y., explains the recent rapid growth of the MMC field of research. With a total of 225 articles, Engineering Structures is the journal that has published the most articles on MMC. China is the leading country in this field, and the Ministry of Education China is the top institution in MMC.

The findings of this study bear significant implications for stakeholders in academia and industry alike. In academia, these insights allow researchers to identify research gaps and foster collaboration, steering efforts toward innovative and impactful outcomes. For industries using MMC practices, the clarity provided on MMC techniques facilitates the efficient adoption of best practices, thereby promoting collaboration, innovation and global problem-solving within the construction field.

The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

Material extrusion (MEX) 3D printers suffer from an intrinsic limitation of small size of the prints due to its restricted bed dimension. On the other hand, friction stir spot welding (FSSW) is gaining wide interest from automobile, airplane, off-road equipment manufacturers and even consumer electronics. This paper aims to explore the possibility of FSSW on Acrylonitrile Butadiene Styrene/Polylactic acid 3D-printed components to overcome the bed size limitation of MEX 3D printers.

Four different tool geometries (tapered cylindrical pin with/without concavity, pinless with/without concavity) were used to produce the joints. Three critical process parameters related to FSSW (tool rotational speed, plunge depth and dwell time) and two related to 3D printing (material combination and infill percentages) were investigated and optimized using the Taguchi L27 design of experiments. The influence of each welding parameter on the shear strength was evaluated by analysis of variance.

Results revealed that the infill percentage, a 3D printing parameter, had the maximum effect on the joint strength. The joints displayed pull nugget, cross nugget and substrate failure morphologies. The outcome resulted in the joint efficiency reaching up to 100.3%, better than that obtained by other competitive processes for 3D-printed thermoplastics. The results, when applied to weld a UAV wing, showed good strength and integrity. Further, grafting the joints with nylon micro-particles was also investigated, resulting in a detrimental effect on the strength.

To the best of the authors’ knowledge, this is the first study to demonstrate that the welding of dissimilar 3D-printed thermoplastics with/without microparticles is possible by FSSW, whilst the process parameters have a considerable consequence on the bond strength.

This study aims to determine the effect of different friction stir welding (FSW) parameters on mechanical and metallurgical characteristics of aviation-grade AA8090 alloy joints.

Response surface methodology with central composite design is used to design experiments. The mechanical and microstructure characteristics of the weld joints have been studied through a standardized method, and the influence of threaded pins on the joint microstructure has also been assessed.

From a desirability strategy, the optimum parameters setting of the friction stir welding was the tool rotational speed (TRS) of 800, 1,100 and 1,400 rpm; tool traverse speed (TTS) of 20, 30 and 40 mm/min; and tilt angle 1°, 2° and 3° with different tool pin profiles, i.e. cylindrical threaded (CT), square threaded and triangular threaded (TT), for achieving the maximum tensile strength, yield strength (YTS) and % elongation as an output parameter. The TRS speed was the highest weld joint characteristics influencing parameter. Peak tensile strength (378 MPa), percentage elongation (10.1) and YTS (308 MPa) were observed for the optimized parametric value of TRS-1,400, TTS-40 mm/min and TA (3°) along with CT pin profile. Microstructure study of the welded surface was achieved by using scanning electron microscope of output parameters. When the tool rotation speed, tool transverse speed, tilt angle and tool profile are set to moderately optimal levels, a mixed mode of ductile and brittle fracture has been seen during the microstructure analysis of the welded joint. This has been aided by the material’s plastic deformation and the small cracks surrounding the weld zone.

From the reported literature, it has been observed that limited work has been reported on aviation-grade AA8090 alloys. Further thermal behavior of welded joints has also been observed in this experimental work.

This paper aims to develop a specific type of mobile nonrigid support friction stir welding (FSW) robot, which can adapt to aluminum alloy trucks for rapid online repair.

The friction stir welding robot is designed to complete online repair according to the surface damage of large aluminum alloy trucks. A rotatable telescopic arm unit and a structure for a cutting board in the shape of a petal that was optimized by finite element analysis are designed to give enough top forging force for welding to address the issues of inadequate support and significant deformation in the repair process.

The experimental results indicate that the welding robot is capable of performing online surface repairs for large aluminum alloy trucks without rigid support on the backside, and the welding joint exhibits satisfactory performance.

Compared with other heavy-duty robotic arms and gantry-type friction stir welding robots, this robot can achieve online welding without disassembling the vehicle body, and it requires less axial force. This lays the foundation for the future promotion of lightweight equipment.

The designed friction stir welding robot is capable of performing online repairs without dismantling the aluminum alloy truck body, even in situations where sufficient upset force is unavailable. It ensures welding quality and exhibits high efficiency. This approach is considered novel in the field of lightweight online welding repairs, both domestically and internationally.