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Additive manufacturing based on robotic welding is used for the manufacture of metal parts by applying an arc as a heat source and wire as feedstock. The process is known as wire arc additive manufacturing (WAAM). However, the current WAAM process has a limitation in fabricating block structure components with high geometry accuracy and consistent...
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... Based on observations, the main factor contributing to the presence of the transition area is the response time of the process, which can be influenced by two factors: machine delay time, and process transition time [21]. The delay time of the wire feeder was measured, and various parameters (including WFS, current, voltage, and others) were recorded during the deposition process. ...
Part quality monitoring and control in wire-based directed energy deposition additive manufacturing (w-DEDAM) processes has been garnering continuous interest from both the academic and industrial sectors. However, maintaining a consistent layer height and ensuring that the wall height aligns closely with the design, as depicted in computer-aided design (CAD) models, pose significant challenges. These challenges arise due to the uncertainties associated with the manufacturing process and the working environment, particularly with extended processing times. To achieve these goals in an industrial scenario, the deposition geometry must be measured with precision and efficiency throughout the part-building process. Moreover, it is essential to comprehend the changes in the interlayer deposition height based on various process parameters. This paper first examines the behaviour of interlayer deposition height when process parameters change within different wall regions, with a particular focus on the transition areas. In addition, this paper explores the potential of geometry monitoring information in implementing interlayer wall height compensation during w-DEDAM part-building. The in-process layer height was monitored using a coherent range-resolved interferometry (RRI) sensor, and the accuracy and efficiency of this measurement were carefully studied. Leveraging this information and understanding of deposition geometry, the control points of the process parameters were identified. Subsequently, appropriate and varied process parameters were applied to each wall region to gradually compensate for wall height. The wall height discrepancies were generally compensated for in two to three layers.
... Currently, few studies have proposed a generic method for selecting manufacturing parameters (Quérard, 2019). Other studies propose a method selecting manufacturing parameters for a particular part geometry (Cui et al., 2021;Zhao et al., 2020). ...
... Concerning the manufacturing parameter selection model proposed by Quérard (2019) (Figure 4), two main steps are included: Studies carried out by Cui et al. (2021); and Zhao et al. (2020) consist in selecting the manufacturing parameters based on the heat input at the start of the arc. Cui et al. (2021) propose a method to manufacture metal block structure parts. ...
... Concerning the manufacturing parameter selection model proposed by Quérard (2019) (Figure 4), two main steps are included: Studies carried out by Cui et al. (2021); and Zhao et al. (2020) consist in selecting the manufacturing parameters based on the heat input at the start of the arc. Cui et al. (2021) propose a method to manufacture metal block structure parts. The principle of this method is to separate depositing paths and apply different heat inputs to these paths. ...
Wire Arc Additive Manufacturing (WAAM) is a metallic additive manufacturing process based on the fusion of metallic wires using an electric arc as a heat source. The challenge associated with WAAM is heat management and understanding bead geometry. All of the process variables, such as travel speed (TS), wire feed speed (WFS), idle time, combine to produce the geometry of the deposited bead that results in the desired component shape. Therefore, determining a method for selecting a good combination of process parameters is critical to obtain a high-quality part. This article presents a study on how to control the WAAM process to produce a thick part of aluminium alloys. An experimental design is determined to study the influence between various process parameters such as WFS, TS, the layer height, or the length of the bead. Different samples are made using a Yaskawa robot, and the classic CMT (Cold Metal Transfer) mode as a manufacturing method. A new manufacturing method is then proposed by adding an important step in the process parameters determination. The results indicate that the length of the bead has a significant impact on the torch speed of the process.
... For the entire WAAM process, the thermal properties of solids and liquids such as the thermal conductivity, density, specific heat, emissivity, and latent heat are used for melting the wire. Similarly, the mechanical properties such as the yield strength, elastic modulus, and thermal expansion coefficient, as well as the elastic and plastic strain of the materials that are functions of temperature are used during the process to predict the expansion and contraction of molten beads, as reported in the literature [33,34]. ...
The wire arc additive manufacturing (WAAM) process is a 3D metal-printing technique that builds components by depositing beads of molten metal wire pool in a layer-by-layer style. Even though manufactured parts commonly suffer from defects, the search to minimize defects in the product is a continuing process, for instance, using modeling techniques. In areas where thermal energy is involved, thermomechanical modeling is one of the methods used to determine the input thermal load and its effect on the products. In the WAAM fabrication process, the thermal load is the most significant cause of residual stress due to the extension and shrinkage of the molten pool. This review article explores the thermomechanical effect and stress existing in WAAM-fabricated parts due to the thermal cycles and other parameters in the process. It focuses on thermomechanical modeling and analysis of residual stress, which has interdependence with the thermal cycle, mechanical response, and residual stress in the process during printing. This review also explores some methods for measuring and minimizing the residual stress during and after the printing process. Residual stress and distortion associated with many input and process parameters that are in complement to thermal cycles in the process are discussed. This review study concludes that the thermal dependency of material characterization and process integration for WAAM to produce structurally sound and defect-free parts remain central issues for future research.
... Wu et al. found that as thermal energy accumulates in the part, the deposited bead height decreases while the width increases due to the increased solidification time of the weld bead [17]. In extreme failure conditions, the liquid metal flows off of the top layer during deposition [14,18]. In the present study, thermal energy can be conducted through the fixturing into the machine tool table; in extreme scenarios, this can thermally damage critical machine components. ...
Wire arc additive manufacturing (WAAM) allows for quick, large component manufacturing with fast deposition rates while leveraging readily available wire feedstock that is significantly cheaper than metal powder. However, the increased deposition rate of this process requires enhanced thermal management as failures can occur due to overheating. A common strategy to mitigate overheating is to dwell, or pause, between individual layers; however, this can significantly increase build times and eliminate the advantage of additive manufacturing being able to manufacture components quickly. To help mitigate this issue, this study explores the use of active cooling to maintain process control and to decrease overall build time. Conductive cooling applied to either the bottom or side of the print substrate was explored. Results from this study showed that bottom build plate active cooling can be used to decrease dwell times by up to 50% and decrease cool-down to room temperature after the building process by up to 75%. Results from this study demonstrate that the use of active cooling strategies for WAAM can be used for better thermal control over the process and should be further investigated.
... Due to this reason, the production cost of the process increases by limiting the use of laser and electron beams in the fabrication of extensive metallic structures on a larger scale [8]. Electric arc as a heat source is a promising technique for the fabrication of large-scale intricate metallic structures owing to their high rate of deposition, reduced cost, and minimal wastage rate [9,10]. A metal wire is employed as feedstock material in the electric arc method, and its cost relative to metal power for equal weight is very low [11]. ...
Appropriate selection of wire–arc additive manufacturing (WAAM) variables imparts bead geometries with characteristics of multi-layer structures. Thus, the present study aimed to optimize the gas metal arc welding (GMAW)-based WAAM variables of travel speed (TS), wire feed speed (WFS), and voltage (V) for the bead geometries of bead width (BW) and bead height (BH) on an SS 316L substrate. Single-layer depositions were made through a metallic wire of SS 316L by following an experimental matrix of the Box–Behnken design (BBD) technique. Multivariable regression equations were generated for design variables and responses, and ANOVA was used to investigate the feasibility of the obtained regression equations. WFS was the highest contributor affecting the BW, followed by V and TS, while WFS was again the highest contributor affecting the BH, followed by TS and V. Heat transfer search (HTS) optimization was used to attain optimal combinations. The single-objective optimization result showed a maximum bead height and minimum bead width of 6.72 mm and 3.72 mm, respectively. A multi-layer structure was then fabricated by considering an optimization case study, and it showed optimized parameters at a WFS of 5.50 m/min, TS of 141 mm/min, and voltage of 19 V with the bead height and bead width of 5.01 mm and 7.81 mm, respectively. The multi-layered structure obtained at the optimized parameter was found to be free from disbonding, and seamless fusion was detected between the obtained layers of the structure. The authors believe that the present study will be beneficial for industrial applications for the fabrication of multi-layer structures.
... Under some circumstances, a deposited bead can be re-melted multiple times, contributing to the larger grain microstructure [119]. If power, traverse speed, and feedstock parameters are kept constant from the beginning of the deposition process, failures due to overheating can occur where weld pool solidification time becomes long enough that the molten material flows from the deposition site increasing material waste and decreasing layer height [120,121]. ...
Hybrid additive manufacturing intertwines both additive and subtractive manufacturing layer by layer to digitally fabricate parts with complex geometries, improved surface finish and tight dimensional accuracies, the sum of which is difficult to obtain with any single process. Computer-Aided Manufacturing (CAM) software is required to orchestrate the machine toolpathing for both the deposition as well as the machining processes and is crucial for the successful fabrication of high quality parts. CAM requires substantial operator input to account for challenging aspects of each fabricated structure. For example, deciding at which layer of deposition will the machining process continue to maintain access to complex cavities for finishing - internal features that would otherwise be unfinishable due to reach limitations or obstructions after fabrication is complete. Moreover, of the many commercially-available hybrid systems, each has a unique kinematic environment which can benefit from specific optimization of toolpath planning and substantial research has directly correlated toolpathing with the microstructure evolution, mechanical properties, porosity and residual stress state of the final fabricated part. This review explores the available strategies for CAM in the context of hybrid direct energy deposition, discusses the advantages and disadvantages of each and considers future CAM trends for this transformational digital manufacturing technology.
... When the heat input is low, the bead grows narrow and tall, but when the heat input is high, it becomes wide and short. [8]. The welding current and torch travel speed has a greater influence on the weld bead geometry at the length of the bead than the arc voltage, torch angle, and contact to work distance. ...
Metal parts are manufactured using various metal additive manufacturing processes. Wire arc additive manufacturing (WAAM) is the process that uses an arc as a heat source and feeding material in the form of wire. The existing WAAM process has limitations in producing metal components with high geometrical accuracy. In this study, ER70S6 wire was used for developing a unique process-planning method based on deposition ratio (DR) to minimize the complexity of the process in achieving high geometrical accuracy. Weld bead geometry is determined by measuring the width and height of the deposited beads. By varying the travel speed (TS) keeping the wire feed speed (WFS) constant the process depends on the deposition ratio is studied. The result justified the direct proportionality between the deposition ratio and the bead height. Hence, this indicates that this procedure is effective in producing a high-quality deposited bead profile just by controlling the deposition rate.
... 7 Printing case with the spiral contour trajectory: a planned in software; b simulated deposition; c a printed single layer an outside-in direction. On the other hand, Cui et al. [27] showed better-performed printing using outside-in, considering that the first external bead deposition serves as a limiting wall to guarantee dimensional accuracy. The spiral contour deposition strategy claims, to some extent, to balance the benefits and setbacks of the deposition direction. ...
To overcome a shortage of flexible and low-cost solutions for wire arc additive manufacturing (WAAM) preprocessing, this work's objective was to develop and validate an in-house computational programme in an open-source environment for WAAM preprocessing planning. Algorithms for reading STL (stereolithography) files and implementing rotation, slicing, trajectory planning, and machine code generation were elaborated and implemented in the Scilab environment (free and open-source). A graphical interface was developed to facilitate user interaction, with 5 options for path planning. The functional-ity of each work step is detailed. For validation of the software, single and multiple-layer prints, with different geometrical complexity and printing challenges, were built in a CNC table geared by the generated machine code. The validation criteria were deposition imperfection, morphological, and dimensional tolerances. The outputs showed that the parts were successfully printed. Therefore, this work demonstrates that Scilab provides the necessary resources for companies and universities to implement and/or develop algorithms for planning and generating trajectories for WAAM. Moreover, emerging ideas can be reasonably easily implemented in such software, not always possible in commercial packages.
... Examples of porosity[26] and voids[27]. ...
Wire Arc Additive Manufacturing (WAAM) is a promising manufacturing technology that has been used to build medium to larger-sized components. The recent progress of Artificial Intelligence (AI) technology has led to Machine Learning (ML) algorithms being widely implemented for modeling, control, monitoring, and simulation processes in WAAM. However, current defect detection systems are limited due to the types of detectable defects, and a real-time micro-defect detection system is yet to be developed. This paper aims to provide an in-depth review of process monitoring approaches suitable for a WAAM system related to defect detections. Particular focus is given to the ML-based monitoring systems, and how they could be implemented into the WAAM process to improve the detecting accuracy, reliability, and efficiency. The paper concludes by discussing the current challenges and future work for developing a real-time monitoring system.KeywordsWAAMAdditive manufacturingDefect detectionProcess monitoringMachine learning
... In order to solve the problem caused by heat input, Honnige used roll pressure to control the residual stress of the manufactured part in the WAAM process, which not only refined the crystal structure, but also reduced the deformation of the part [18]. In addition, Cui proposed a new process planning method, while maintaining high manufacturing efficiency, by applying different heat input at different positions to control the transformation of the crystal structure, so as to minimize defects in the parts [19]. Zhou found through experiments that the surface quality can be improved by optimizing process parameters to reduce heat input [20]. ...
Wire and arc additive manufacturing has unique process characteristics, which make it have great potential in many fields, but the large amount of heat input brought by this feature limits its practical application. The influence of heat input on the performance of parts has been extensively studied, but the quantitative description of the influence of heat input on the surface quality of parts by wire and arc additive manufacturing has not received enough attention. According to different heat input, select the appropriate process parameters for wire and arc additive manufacturing, reversely shape the profile model, select the appropriate function model to establish the ideal profile model according to the principle of minimum error, and compare the two models to analyze the effect of heat input on the surface quality of the parts manufactured by wire and arc additive manufacturing. The results show that, when the heat input is high or low, the standard deviation value and the root mean square value reach 1.908 and 1.963, respectively. The actual profile is larger than the ideal profile. When the heat input is moderate, the standard deviation value and the root mean square value are only 1.634 and 1.713, respectively, and the actual contour is in good agreement with the ideal contour. Combined with the analysis of the transverse and longitudinal sections, it is shown that the heat input has a high degree of influence on the surface quality of the specimen manufactured by wire and arc additive manufacturing, and higher or lower heat input is disadvantageous to it.
