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This paper aims to anticipate the possible development direction of WAAM. For large-scale and complex components, the material loss and cycle time of wire arc additive manufacturing (WAAM) are lower than those of conventional manufacturing. However, the high-precision WAAM currently requires longer cycle times for correcting dimensional errors. Therefore, new technologies need to be developed to achieve high-precision and high-efficiency WAAM.

This paper analyses the innovations in high-precision WAAM in the past five years from a mechanistic point of view.

Controlling heat to improve precision is an effective method. Methods of heat control include reducing the amount of heat entering the deposited interlayer or transferring the accumulated heat out of the interlayer in time. Based on this, an effective and highly precise WAAM is achievable in combination with multi-scale sensors and a complete expert system.

Therefore, a development direction for intelligent WAAM is proposed. Using the optimised process parameters based on machine learning, adjusting the parameters according to the sensors’ in-process feedback, achieving heat control and high precision manufacturing.

Wire + arc additive manufacturing (WAAM) uses existing welding technology to make a part from metal deposited in an almost net shape. WAAM is flexible in that it can use multiple materials successively or simultaneously during the manufacturing of a single component.

In this work, a gas metal arc welding (GMAW) based wire + arc additive manufacturing (WAAM) system has been developed to use two material successively and fabricate bimetallic additively manufactured structure (BAMS) of low carbon steel and AISI 316L stainless steel (SS).

The interface shows two distinctive zones of LCS and SS deposits without any weld defects. The hardness profile shows a sudden increase of hardness at the interface, which is attributed to the migration of chromium from the SS. The tensile test results show that the bimetallic specimens failed at the LCS side, as LCS has lower strength of the materials used.

The microstructural features and mechanical properties are studied in-depth with special emphasis on the bimetallic interface.

The purpose of this paper is to improve the productivity and quality of the wire arc additive manufacturing process by benchmarking the strategies from the selected six strategies, namely, heat treatment process, inter pass cooling process, inter pass cold rolling process, peening process, friction stir processing and oscillation process.

To overcome the lack of certainty associated with correlations and relationships in quality functional deployment, fuzzy numbers have been integrated with the quality functional deployment framework. Twenty performance measures have been identified from the literature under five groups, namely, mechanical properties, physical properties, geometrical properties, cost and material properties. Using house of quality weights are allocated to performance measures and groups, relationships are established between performance measures and strategies, and correlations are assigned between strategies. Finally, for each strategy, relative importance, score and crisp values are calculated.

Inter pass cold rolling process strategy is computed with the highest crisp value of 15.80 which is followed by peening process, heat treatment process, friction stir processing, inter pass cooling process,] and oscillation process strategy.

To the best of the authors’ knowledge, there has been no research in the literature that analyzes the strategies to improve the quality and productivity of the wire arc additive manufacturing process.

Additive manufacturing (AM) can achieve significant weight savings with only minor compromises in strength if high-performance wrought aluminum alloys are used as feedstock. Despite the advantages in strength that aluminum alloys (AA) 6061 offer, they cannot be manufactured via printing because of hot cracking and other solidification problems. The purpose of this study is to achieve high-quality printing of AA6061 with nanotreated wires.

Nanotreating was used to modify the AA6061 alloy composition by adding a small fraction of nanoparticles to enhance the alloy’s manufacturability and resultant properties. Wire arc additive manufacturing (WAAM) was used to print the nanotreated AA6061 wire feedstock. The microstructure of the printed AA6061 was characterized by X-ray crystallography, optical microscopy, scanning electron microscopy and energy dispersive spectroscopy mapping. The microhardness profile, tensile behavior and fracture surface were analyzed.

This work successfully used WAAM to print nanotreated AA 6061 components. The resulting AA6061 parts were crack-free, with exceptional grain morphology and superior mechanical properties. Owing to the excellent size control capabilities of nanoparticles, a homogeneous distribution of small grains was maintained in all deposited layers, even during repeated thermal cycles.

Previous studies have not successfully printed AA6061 using WAAM. Conventional WAAM products exhibit anisotropic mechanical properties. The nanotreated AA6061 was successfully printed to achieve homogeneous microhardness and isotropic tensile properties. The promising results of this study reflect the great potential of nanotech metallurgy as applied to the WAAM process.

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.

The purpose of this research is to show the characteristics of a Cu–Ti dissimilar interface produced by a wire arc-based additive manufacturing process. The purpose of this research was to determine the viability of the Cu–Ti interface for the fabrication of functionally graded structures (FGS) using the wire arc additive manufacturing (WAAM) process.

This paper used the WAAM process with variable current vis-à-vis heat input to demonstrate multiple Ti-6Al-4V (Ti64) and C11000 dissimilar fabrications. The hardness and microstructure of the dissimilar interfaces were investigated thoroughly. The formation of Cu–Ti intermetallic at the Ti64/Cu fusion interface is been revealed by scanning electron microscopy and energy dispersive X-ray analysis, while X-ray diffraction was used to identify various Cu–Ti intermetallic phases. The effect of microstructure on interfacial sensitivity and hardness are also investigated.

The formation of CuTi intermetallic and the β-phase transformation in Ti-6Al-4V are found to be heat input dependent. The Cu diffusion length increases as the heat input for Ti64 deposition increases, resulting in a greater Cu–Ti intermetallic thickness. The Cu–Ti interface properties improve when the heat input is less than approximately 250 J/mm or the deposition current is less than 90 A. The microhardness ranges from 55 to 650 HV from the Cu-side to the interface and from 650 to 350 HV from the interface to the Ti-side. Higher current increases interface hardness, which increases brittleness and makes the interface more prone to interfacial cracking.

Nonlinear components are needed for a variety of extreme engineering applications, which can be met by FGS with varying microstructure, composition and properties. FGS produced using the WAAM process is a novel concept that requires further investigation. Despite numerous studies on Ti-clad Cu, information on Cu–Ti interface characteristics is lacking. Furthermore, the suitability of the WAAM process for the development of Cu–Ti FGS is unknown. As a result, the goal of this research article is to fill these gaps by providing preliminary information on the feasibility of developing Cu–Ti FGS via the WAAM process.

This paper aims to numerical and experimental analysis on substrate deformation and plastic strain induced by wire arc additive manufacturing.

The component has the form of a hollow, rectangular thin wall consisting of 25 deposition layers of SS316L on an SS304 substrate plate. Thermo-mechanical finite element analysis was applied with Goldak’s double-ellipsoidal heat-source model and a non-linear isotropic hardening rule based on von Mises’ yield criterion. The layer deposition was modelled using simplified geometry to minimize overall pre-processing work and computational time.

A new material modelling of SS316L was obtained from the chemical composition of the evolved component characterized by scanning electron microscope/energy dispersive X-ray and further generated by an advanced material-modelling software JMatPro. In defining heat-transfer coefficients, transient thermometric analysis was first performed in the bead and on the substrate, which was followed by an adjustment of the heat-transfer coefficients to reflect the actual temperature distribution. Based on the adjusted model and boundary conditions, sensitivity analysis was conducted prior to the ultimate simulation of substrate deformation and equivalent plastic strain. Furthermore, this simulation was verified by conducting a series of automated wire + arc additive manufacturing tests using robotic gas Metal arc welding with distortion measured by coordinate-measurement machine and equivalent plastic strain measured by optical three-dimensional-metrology measurements (Gesellschaft für Optische Messtechnik).

It can be concluded that a proper numerical computation using the adjusted model and property-evolved material exhibits a similar trend with acceptable agreement compared to the experiment by yielding an error percentage up to 30% for deformation and up to 21% for equivalent plastic strain at each individual measurement point.

The purpose of this paper is to find a theoretical reference to adjust the unsymmetrical arc shape and plasma flow of overlapping deposition in wire arc additive manufacturing (WAAM) and ensure the effect of the gas shielding and stable heat and mass transfer in deposition process. The multiphysical numerical simulation and physical experiment are used for validation.

In this study, welding torch tilt deposition and external parallel magnetic field–assisted deposition are presented to adjust the unsymmetrical arc shape and plasma flow of overlapping deposition, and a three-dimensional numerical model is developed to simulate the arc of torch tilt overlapping deposition and external parallel magnetic field–assisted overlapping deposition.

The comparison of simulated results indicate that the angle of welding torch tilt equal to 20° and the magnetic flux density of external transverse magnetic field equal to 0.001 Tesla are capable of balancing the electric arc and shielding gas effectively, respectively. The arc profiles captured by a high-speed camera match well with simulated results.

These studies of this paper can provide a theoretical basis and reference for the calibration and optimization of WAAM process parameters.

A new wire arc additive manufacturing (WAAM) process combined with gravity-driven powder feeding was developed to fabricate components of tungsten carbide (WC)-reinforced iron matrix composites. The purpose of this study was to investigate the particle transportation mechanism during deposition and determine the effects of WC particle size on the microstructure and properties of the so-fabricated component.

Thin-walled samples were deposited by the new WAAM using two WC particles of different sizes. A series of in-depth investigations were conducted to reveal the differences in the macro morphology, microstructure, tensile performance and wear properties.

The results showed that inward convection and gravity were the main factors affecting WC transportation in the molten pool. Large WC particles have higher ability than small particles to penetrate into the molten pool and survive severe dissolution. Small WC particles were more likely to be completely dissolved around the top surface, forming a thicker region of reticulate (Fe, W)₆C. Large WC particles can slow down the inward convection more, thereby leading to an increase in width and a decrease in the layer height of the weld bead. The mechanical properties and wear resistance significantly increased owing to reinforcement. Comparatively, samples with large WC particles showed inferior tensile properties owing to their higher susceptibility to cracks.

Fabricating metal matrix composites through the WAAM process is a novel concept that still requires further investigation. Apart from the self-designed gravity-driven powder feeding, the unique aspects of this study also include the revelation of the particle transportation mechanism of WC particles during deposition.

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.