Wire arc additive manufacturing (WAAM) enables high-rate fabrication of large metallic components, but spatial variations in thermal history can lead to microstructural heterogeneity that requires efficient process models to evaluate. This study evaluates whether cooling rates extracted from a graph theory model (GTM)-based thermal simulation are consistent with the microstructural evolution observed in an ER70S-6 WAAM wall. Thermal histories from the model were analyzed at selected build heights, and cooling rates were extracted from the final thermal excursion through the austenite phase field. Microstructures at corresponding locations were characterized using electron backscatter diffraction (EBSD) to quantify grain size distributions, and pearlite interlamellar spacing was used as an additional indicator of cooling behavior. The modeled cooling rates were highest near the substrate and generally decreased with build height, consistent with the observed reduction in the fine grain fraction and the progressive shift in the grain size distribution as build height increased. Pearlite spacing trends also supported the modeled cooling rate variation. These results indicate that GTM-derived thermal histories can be post-processed into metallurgically meaningful cooling rate estimates for WAAM steel builds and linked to dataset specific empirical grain size distribution relationships for process–thermal history–microstructure assessment.

Understanding build-scale microstructural variation in wire arc additive manufacturing (WAAM) of low-carbon steels is essential for ensuring consistent structure-property relationships throughout large components. Conventional destructive characterization techniques, such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), are time-intensive and limited to localized regions, making comprehensive evaluation of large WAAM structures challenging. In this study, a nondestructive ultrasonic approach was employed to characterize a 252 mm tall ER70S-6 S-curved WAAM wall produced using a triple-bead deposition strategy. Optical and SEM analysis revealed a repeating dual-region microstructure consisting of uniform polygonal ferrite at melt pool centers and heterogeneous ferrite with coarse and fine grains near melt pool boundaries, attributed to cyclic thermal conditions. Longitudinal ultrasonic backscatter imaging was used to evaluate the continuity of this periodicity along the full build height. The ultrasonic response exhibited a consistent repeating pattern that correlated with the observed layer-wise microstructural variation. X-ray computed tomography confirmed the absence of detectable porosity, indicating that ultrasonic contrast is primarily governed by grain morphology. Overall, the results indicate that longitudinal backscatter ultrasound is a promising nondestructive characterization technique for validating microstructural variations along the s-curved WAAM wall, with significant potential for microstructure optimization and process control.

This work presents, verifies, and experimentally validates an extended Graph Theory (GT) approach for thermal simulation in metal big area additive manufacturing (mBAAM). The extended approach features a modeling domain enhanced by variable node density for fast computation, whereby node density is low away from the build plane where thermal gradients are low. Scalability and flexibility of the model are enhanced by decoupling the toolpath from mesh generation. Verification is carried out by comparison with simulations from a commercial Finite Element software (Simufact Welding). Experimental validation is carried out with an S-shaped and C-shaped wall, each with three weld tracks per layer and built to 252 mm tall on a mild steel EN-8 substrate. The wall material is mild steel (ER70s-6 feedstock) and a shielding gas with composition 82/18 % Ar/CO2 is used. Thermal data is collected from shielded thermocouples embedded in each substrate as well as bare thermocouples spot-welded to the wall throughout the deposition. The GT-predicted three-dimensional thermal history agrees with experimental data within 4.5 % and 16 degrees C. Compared to previously published works, the present approach reduces computation time and enables freedom in toolpath selection, scaling up the GT approach with potential for process optimization and thermal modeling of large parts.

In this work, IN718 superalloy has been additively manufactured through Laser-based Powder Bed Fusion (PBF) process. The present investigation aims to study the effect of post printing heat treatments on the metallurgical aspects, such as phases, crystallographic texture, microstructure evolutions and the mechanical properties. Heat treatment optimization has been pursued to achieve a better combination of strength and ductility. PBF fabricated material was further subjected to different heat treatments, comprising of homogenizing, solutionizing and ageing. Material was characterized with respect to the building direction (BD). As-printed specimen exhibits face centered cubic (FCC) gamma matrix along with minor amounts of other phases. The melt pool boundaries were found to be rich in Niobium and Molybdenum, indicating segregation during fabrication. Upon post-heat treatments these segregations dissolved considerably. Heat treated microstructure exhibited homogeneously dispersed gamma ' and gamma '' phases, and relatively small fractions of carbides, acicular and plate shaped delta phases. Heat treatments led to a significant increase in hardness (by about 54 %) and tensile strength (by about 45 %) while retaining considerable ductility.

Hybrid manufacturing is the combination of two or more different processes to overcome their individual limitations and take advantage of their combined strengths to produce components more efficiently and eco-friendly than existing processes. Double-sided incremental forming (DSIF) and metal additive manufacturing (MAM) using direct energy deposition are the most flexible processes that do not require geometry-specific tooling to produce customized and complex metal parts. However, there is no absolute geometrical freedom, and each process and machine has certain limitations (MAM process has gravity and torch accessibility constraints due to lower surface inclinations and intricate shapes, respectively). Hence, the main objective of the present work is to demonstrate the feasibility thereof from the judicious hybridization of DSIF and MAM processes ( termed as HyDAM, Hybrid Deformation aided Additive Manufacturing) in terms of product complexity by exploiting the geometrical freedom offered from both processes. Non-planar substrates are formed using DSIF and deposition is carried out using wire-based direct energy deposition (W-DED). In the present work, two complex geometries which are difficult to fabricate by conventional AM process due to torch accessibility and gravity constraints are considered to demonstrate their feasibility through proposed hybrid process. An appropriate build orientation of the component is chosen, and the corresponding substrate is formed using DSIF. The material deposited on the formed substrate with a suitable deposition path. The feasibility of proposed HyDAM is successfully demonstrated by fabricating complex components using a three-axis machine during deposition. Future work includes the automatic feature recognition for HyDAM, role of process parameters on bead asymmetry, path planning, exploring complex geometries (for example: deposition of non-planar cellular/perforated structures), performing thermo-mechanical analysis, and achieving the good accuracy.

FDM-fused deposition modeling is an extrusion-based 3D printing technique, has been extensively researched and proven to be a fundamental tool with diverse applications in engineering fields for creating 3D objects. The popularity of thermoplastic materials like PLA, ABS, PETG, Nylon, and TPU in FDM 3D printing is due to their properties and affordability. However, the introduction of new high-grade polymers (HGPs) creates compatibility challenges with existing machines and processes, limiting their full-scale adoption. The adoption of new materials in 3D printing can necessitate modifications to hardware, software, and settings, which can be costly and time-consuming. Ensuring quality control and consistency becomes challenging as each material requires unique parameters and processing conditions, resulting in variability and difficulties in achieving consistent part quality. Optimizing FDM parameters for high-grade polymers (HGPs) like PEEK is challenging due to their unique properties. The high thermal gradient and heat distribution during printing can result in residual stresses and deformations, impacting the quality and mechanical properties such as tensile, compressive, and impact strength. There is a limited research focus on investigating the impact resistance or strength of materials compared to tensile and compressive properties, resulting in fewer studies available on this aspect of mechanical properties. Therefore, this article utilized a multi-criteria decision-making (MCDM) method to determine the best combination of process parameters for 3D printing PEEK and resulting in improved impact strength − 230.4 kJ/m2 while considering factors such as build orientation—XZ, print density—100

Purpose This study aims to improve the mechanical properties of an object produced by fused deposition modelling with high-grade polymer. Design/methodology/approach The study uses an ensembled surrogate-assisted evolutionary algorithm (SAEA) to optimize the process parameters for example, layer height, print speed, print direction and nozzle temperature for enhancing the mechanical properties of temperature-sensitive high-grade polymer poly-ether-ether-ketone (PEEK) in fused deposition modelling (FDM) 3D printing while considering print time as one of the important parameter. These models are integrated with an evolutionary algorithm to efficiently explore parameter space. The optimized parameters from the SAEA approach are compared with those obtained using the Gray Relational Analysis (GRA) Taguchi method serving as a benchmark. Later, the study also highlights the significant role of print direction in optimizing the mechanical properties of FDM 3D printed PEEK. Findings With the use of ensemble learning-based SAEA, one can successfully maximize the ultimate stress and percentage elongation with minimum print time. SAEA-based solution has 28.86% higher ultimate stress, 66.95% lower percentage of elongation and 7.14% lower print time in comparison to the benchmark result (GRA Taguchi method). Also, the results from the experimental investigation indicate that the print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3D printed high-grade thermoplastic PEEK polymer. Research limitations/implications This study is valid for the parameter ranges, which are defined to conduct the experimentation. Practical implications This study has been conducted on the basis of taking only a few important process parameters as per the literatures and available scope of the study; however, there are many other parameters, e.g. wall thickness, road width, print orientation, fill pattern, roller speed, retraction, etc. which can be included to make a more comprehensive investigation and accuracy of the results for practical implementation. Originality/value This study deploys a novel meta-model-based optimization approach for enhancing the mechanical properties of high-grade thermoplastic polymers, which is rarely available in the published literature in the research domain.

The objective of this paper is to develop, verify, and experimentally validate a mesh-free spectral graph theory-based approach for rapid prediction of thermal history in metal parts made using the wire arc additive manufacturing (WAAM) process. Accurate and rapid prediction of the thermal history is a critical prerequisite for functional quality assurance of WAAM parts. In the spectral graph method, the WAAM part is represented as a set of discrete nodes encompassed by a network graph. The thermal history is obtained by solving the heat equation on the network graph. The spectral graph theory approach thus bypasses the cumbersome computational burden associated with mesh generation in the finite element method. To validate the spectral graph theory approach, experimental temperature data is acquired for multi-layer mild steel WAAM parts processed under six different combinations of shape and inter-layer dwell time conditions. Further, each experiment was replicated resulting in a total of 12 parts. The accuracy of the thermal trends predicted by the spectral graph theory approach was quantified in terms of the symmetric mean absolute percent error (SMAPE) and root mean squared error (RMSE, °C). The thermal history trends were predicted with SMAPE < 5

Among the AM processes Laser based Powder Bed Fusion (LPBF) technique offers precise and complex geometric fabrication. However, the microstructural and mechanical properties obtained from LPBF process requires further investigation, especially for IN718 superalloys. In this study, various heat treatments were applied to LPBFed Inconel 718 specimens to examine their effects on microstructure, microhardness and wear behavior. Three different heat treatments, each involving varied solutionizing and ageing steps were incorporated. Asprinted specimens exhibited distinct fish scale structures with columnar dendrites. Heat treatments effectively dissolved the Laves phase and precipitated strengthening phases like gamma '' and gamma '. Microhardness increased significantly after heat treatments, correlating with the formation of strengthening precipitates. Friction and wear tests showed as-printed specimens exhibited higher wear loss (922 f 13 mu m) and coefficient of friction (COF) (0.511 f 0.07) due to the presence of Laves phase and softer matrix. Heat-treated specimens demonstrated significantly reduced wear loss (262 f 5 mu m) and COF (0.368 f 0.01), with HT2 showing the best wear resistance attributed to a homogeneous microstructure. SEM analysis of worn surfaces confirmed abrasive and adhesive wear mechanisms in as-printed specimens, while heat-treated specimens exhibited reduced wear with smoother surfaces.

Wire arc additive manufacturing (WAAM) is a proven technology in metal additive manufacturing (AM), which can produce large-scale components at a faster production rate. Since WAAM adopts a welding heat source for metal deposition over the substrate, severe thermal gradients develop around the deposition resulting in residual stresses in the substrate, thereby distorting the substrate. In the case of area filling in metal AM processes, heat accumulation is progressive and a large amount of heat is accumulated at the end of the deposition. This leads to thermal imbalance over the substrate and an increase in the shrinkage forces during cooling, thereby causing higher distortion. This paper mainly deals with the mitigation of distortion in the substrate for area filling caused by the thermal imbalance over the substrate. This thermal imbalance is addressed in two ways; a) by selectively insulating and b) by selectively conducting the heat from the substrate. Simulations are conducted to study the thermal evolution during area filling and counterbalance the heat by insulating and conducting the substrate selectively during experimental deposition. A comparative assessment of distortions of the full conduction, full insulation, selective conduction and selective insulation cases is detailed. The selective thermal management strategy showed lower thermal imbalance over the substrate resulting in lower distortion.

The present study combines the Wire-based DED (W-DED) and Powder-based DED (P-DED) to achieve a high deposition rate and higher feature resolution, respectively, within the single component. The research puts forward a novel Wire-Power (WP) Hybrid DED process, which is realized by sequential deposition of feedstock in Wire and then in Powder form. Based on the deposition-extraction combination, three sample configurations, C1 (Y-X), C2 (X-X) and C3 (Y-Z), were fabricated and characterized for the mechanical properties and microstructural aspects. OM images revealed defect-free P-DED and W-DED interface, while the EBSD analysis showed grain size variations owing to differences in the cooling rates. The Ultimate Tensile Strength (UTS) values of C1 and C2 configurations are about 132.2 and 139.7 % higher in comparison to C3. Low cycle fatigue results showed that the C2 sustained a higher number of completely reversed cycles to failure in comparison to the other configurations. The impact energy absorbed by C3 is the highest, affirming the strong W-P interface.

Energy consumption is an important metric used to evaluate the sustainability potential of manufacturing processes. Due to the low volume and mass customization potential, additive manufacturing (AM) processes have experienced exponential growth in recent years, resulting in heightened ecological consciousness surrounding energy usage. Gaining insight into the energy-intensive sub-systems and sub-processes and identifying strategies for their minimization enables manufacturers to save on energy costs and also aids in reducing their carbon footprint. This study delves into the energy consumption characteristics of the powder bed fusion (PBF) process, particularly selective laser melting (SLM). Through experimental investigation, we investigate how certain factors impact energy usage, namely capacity utilization, layer thickness, and part orientation. We present a novel formulation for estimating primary and total energy consumption in PBF processes, offering a comprehensive energy consumption model. Our results demonstrate significant energy savings with increased capacity utilization—up to a 32.68% reduction in total energy consumption (TEC) per part. Layer thickness variations show the lowest TEC at 25 μm, which can be attributed to the SLM machine's reduced operational time and energy usage of auxiliary components. Furthermore, altering part orientation for the given case study yielded a 50% reduction in TEC, highlighting orientation as a critical factor in energy efficiency. Our formulation, benchmarked against experimental data and specific energy consumption (SEC) values from the literature, effectively captures these parameters' influence on energy usage. The insights from this research advance our understanding of energy dynamics in SLM processes and pave the way for more energy-efficient practices in AM.

Additive manufacturing (AM) is a rapidly evolving technology that has potential to revolutionize the way products are designed, manufactured, and delivered and having a wide variety of applications including artistry, medical, bio-printing, aerospace, automobile, defence, nuclear, marine, food, electronics and for open-source hobbyist printing etc. Fused deposition modelling (FDM) is relatively simple and affordable 3D printing technique, where filament or wire form of feedstock materials are used. However, over the years full-scale implementation of this technology has become slower due to the development of new materials periodically e.g., HGPs (high-grade polymers), and thus compatibility with the existing 3D printing machines is a major challenge. The adjustment of process parameters during any manufacturing system can always be value-added, thus it is felt that investigating them and their effects will always be beneficial to improve the quality and final product. Indeed, it is difficult to consider specific FDM printing process parameters to obtain optimum mechanical behaviour in case of HGPs e.g. PEEK (poly-ether-ether-ketone). Therefore, in this paper with the help of Taguchi DOE (design of experiments), effect of four most relevant FDM printing process parameters (nozzle temp., print speed, layer height and print direction) and their percentage contribution on mechanical properties (ultimate tensile strength) were analysed for PEEK -a high-grade polymer.

Laser based Powder Bed Fusion (LPBF) stands out among Additive Manufacturing (AM) techniques for its ability to fabricate intricate geometries with high precision. However, LPBF produced parts, particularly Inconel 718 (IN718) superalloys, demand further exploration in microstructural and mechanical properties aspect. This study explores the effect of heat treatments on LPBF fabricated Inconel 718. Three distinct heat treatments involving diverse solutionizing temperatures and ageing steps were applied to the LPBFed IN718 alloy. As-printed samples showed columnar dendritic microstructure. The heat treatments led to precipitation of strengthening gamma '' and gamma ' phases. A substantial increase in microhardness was observed after heat treatments. Wear tests revealed asprinted specimens suffered higher wear loss (similar to 889 mu m) and coefficient of friction (COF) (similar to 0.627) attributed to Laves phase and low hardness of the matrix. However, heat-treated specimens exhibited substantially lower wear loss (similar to 217 mu m) and COF (similar to 0.342), with HT2 condition demonstrating superior wear resistance attributed to a homogeneous microstructure.

Laser-directed energy deposition is a powerful and promising metal-based additive manufacturing technique. This is becoming a prominent approach for the freeform production of thin-wall structures. However, its diffusion into the industry is still limited due to the challenges in controlling the geometry. One of the main causes for this is heat accumulation during multi-layer deposition. Therefore, the present study focuses on the real-time monitoring of molten pool thermal cycles using an IR pyrometer for a deep understanding of the spatiotemporal variations of it with layer number. From the experimental observations, the monitored molten pool cycles were found to clearly identify/indicate the heat accumulation with layer number. Based on this, the variation in laser scanning speed and interpass delay was systematically introduced during the deposition process to control the heat accumulation, which is once again monitored through the recorded thermal cycles. Further, a method to mitigate the existing waviness through adjusting the relative position between the powder focusing point, peak, and valley was demonstrated. Waviness was found to mitigate by carrying out the depositions keeping the powder focusing point aligned with the valleys of the undulated surface.

Components fabricated in metal additive manufacturing, including wire arc additive manufacturing, undergo complex thermal cycles, resulting in residual stresses and thermal distortions. The present work investigates the effect of applying in-situ electric pulses to the component after the deposition of every layer to reduce residual stresses. The experimental results revealed that electropulsing resulted in dislocation rearrangement/annihilation, thereby decreasing dislocation density. A significant reduction in the fraction of low angle grain boundaries was observed for electropulse-treated samples, indicating a decrease in residual stress. Further, X-ray diffraction results also confirm a reduction in residual stress (24.0–29.4% reduction compared to untreated samples). The method can effectively be used to address specific regions selectively in addition to in-situ reduction of residual stresses in deposited components.Abbreviations: EBSD: electron backscattered diffraction; EPT: electropulsing treatment; EWF: electron wind force; GND: geometrically necessary dislocations; KAM: Kernel average misorientation; LAGBs: low angle grain boundaries; WAAM: wire arc additive manufacturing; XRD: X-ray diffraction

In the material extrusion based 3D printing-fused deposition modelling (FDM), each material may require its own unique set of processing parameters and these parameters can be difficult to optimise and control. This can lead to variability in the final product and can make it challenging to produce parts with consistent quality. Indeed, it is difficult to consider specific FDM parameters to obtain optimum mechanical properties mainly in case of high grade polymers (HGPs) e.g. PEEK, PEK, PPS etc. With the high thermal gradient and heat distribution during their printing, possibilities of residual stresses and deformations are unavoidable, which directly affects its quality and mechanical properties. In this article, an ensembled Surrogate Assisted Evolutionary Algorithm (SAEA) based method is used to optimise the process parameters (layer height, print speed, print direction and nozzle temperature) to enhance the mechanical properties, considered as print quality, of PEEK considering print time into account. The solution obtained through the SAEA approach is further compared with the solution computed through Gray Relational Analysis (GRA) Taguchi, which is used as the benchmark method, to establish the superiority of the proposed one. The comparison indicates the SAEA based solution has 28.86% of higher Ultimate stress value, 66.95% of lower percentage of elongation and 7.14% of lower print time in comparison to the benchmark result. It has also been found that print direction has a greater role in deciding the optimum value of mechanical properties for FDM 3d-printed PEEK material.

This article presents innovative approaches for managing residual stresses and distortion in additive manufacturing (AM) of metal components (baseplate material: EN8; filler wire material: ER70S-6). The experiments are conducted with two approaches for thermal management—passive and active. The passive approach of experiments is performed by varying the selected process parameters to study their effect on residual stresses and distortion. The chosen parameters are current, torch speed, geometry, continuous or a delay in the deposition, and cooling arrangement. Based on the understanding gained from the passive approach, the active approach of thermal management was implemented by insulating the substrate with and without adaptive current and heating the substrate. The experimental results were corroborated with the simulation to understand the process better. A comparative study for hardness was made based on the T8/5 extracted from the simulation. These experiments and simulations endorse passive and active thermal management as effective tools that can alter the distortion and residual stress pattern and the mechanical properties of an AM component. The investigation concludes that the process parameters that lead to higher heat input vis-à-vis an increase in current or a decrease in speed increase the distortion. On the other hand, the parameters that affect the rate of heat distribution vis-à-vis torch speed and geometry affect the residual stresses. When current, traverse speed and a/b ratio were kept the same, active thermal management with a heated base reduced distortion from 1.226 mm to 0.431 mm, a 65% reduction compared to passive thermal management. Additionally, the maximum residual stress was reduced from 492.31 MPa to 250.68 MPa, with residual stresses decreasing from 418.57 MPa to 372 MPa. Overall, active thermal management resulted in a 63% reduction in distortion, lowering it from 1.35 mm to 0.50 mm using external heating. The components that are difficult to complete because of the in-process distortion are expected to be manufactured with thermal management, e.g., heating the substrate is an effective measure to manage the in-process distortion. Thermal management techniques depend on geometry; for instance, a concave surface, because of self-heating, reduces the cooling rate and has relatively less variation in hardness.

Thermoplastic materials such as Polylactic acid, Acrylonitrile Butadiene Styrene, Polyethylene terephthalate glycol, Nylon, and Thermoplastic polyurethane are favoured in Fused deposition modeling 3D printing due to their cost-effectiveness and versatile properties. However, with the introduction of high grade thermoplastic material poses compatibility challenges with existing machines and processes, impeding widespread adoption in FDM 3D printing. Incorporating new materials into 3D printing requires adjustments to hardware, software, and settings, leading to potential expenses and time investments. Maintaining quality control and consistency becomes complex as each material demands specific parameters and processing conditions. This variability hinders achieving consistent part quality in 3D printing. Moreover, achieving optimal FDM parameters for high-grade polymers (HGPs) like Polyether ether ketone (PEEK) is a challenge due to the distinctive nature of the property, requiring specialized careful considerations during its optimization process. The considerable thermal gradient and heat distribution during printing can lead to residual stresses and deformations, significantly affecting the quality and, in particular, its impact strength. This article optimizes an industry grade 3D printing PEEK based on the limited number of process parameters, namely, build orientation, in-fill density and chamber temperature. Further, the research tries to derive a predictive model for Impact Strength (IS), which is an important consideration for the 3D printed object. In this article, along with the Impact Strength, Printing Time and Material Usage are also studied to find empirical evidence of association between these output variables or response variables. The result indicates that there is a positive significant correlation or association between them. When utilizing a specific parameter setup, the resulting IS of 86.5 kJ/m², a print time of 89 minutes, and a material usage of 3.26 grams are achieved. Notably, there is a measurable reduction of 9.18% in printing time and a 11.66% decrease in material usage when the print density is set to 100% to optimize impact strength. This optimization approach proves the use of composite desirability is a better approach where multiple objectives need to be achieved. The proposed regression model predicts the impact strength with coefficient of determination value more than 50%.

Purpose Amongst various additive manufacturing (AM) techniques for realizing the complex metallic objects, weld-deposition (arc)-based directed energy AM technique is attaining more focus over commercially available powder bed fusion techniques. This is because of the capability of high deposition rates, high power and material utilization, simpler setup and less initial investment of arc-based AM. Nevertheless, realization of sudden overhanging features through arc-based weld-deposition techniques is still a challenging task because of the necessity of support structures. This paper aims to describe a novel methodology for producing complex metallic objects with sudden overhangs without using supports. Design/methodology/approach The realization of complex metallic objects with sudden overhangs (without using supports) is possible by reorienting the workpiece and/or deposition head at every instance using higher order kinematics (5-axis setup) to make sure the overhanging feature is in line to the deposition direction. Findings In the absence of universally applicable support mechanism, deposition of overhanging features remains one of the main challenges in AM. A separate support structure is often necessary for depositing the overhanging features. Small overhang features are usually possible by a little overextension from the previous layer. Nevertheless, deposition of large gradually varying overhangs and sudden overhangs with complex features without support structures is a challenging task in any AM process. This demands higher order kinematics which calls for inclined and/or orthogonal slicing and area filling. Originality/value The unique aspect of this paper is the identification of sudden overhang feature from a tessellated computer-aided design (.stl) file and generates an orthogonal tool path for deposition for sudden overhangs. An in-house MATLAB routine has been developed and presented for performing the same. This methodology helps in realization of sudden overhangs without use of supports. To validate proposed technique, various illustrative case studies have been taken up for deposition.