High Geometric Accuracy Research Articles

Integration of the Velodyne LiDAR Sensor and Pixhawk for Indoor 3D Mapping

Abstract The importance of indoor mapping has surged across various applications, encompassing human navigation, indoor exploration, and hazardous site mapping. With satellite positioning systems ineffective indoors, alternative navigational sensors and methods, such as inertial measurement units (IMU) and simultaneous localization and mapping algorithms (SLAM), have been harnessed to furnish precise indoor positioning for mapping endeavors. Leveraging LiDAR-based SLAM, which is sensitive to environmental textures and various pose configurations, addresses these challenges. In order to accomplish reliable and precise indoor 3D mapping, this study combines the Velodyne VLP-16 3D-LiDAR sensor with the Pixhawk Cube Orange, which has a 9 Degrees of Freedom (DOF) IMU sensor. The study uses the LIO-SAM (LiDAR Inertial Odometry and Simultaneous Localization and Mapping) technique, which integrates data from LiDAR and IMU to increase mapping precision. It is carried out at the BAAK Dr. Angka Building, Institut Teknologi Sepuluh Nopember, Surabaya. The experimental results reveal that the 3D indoor mapping exhibits commendable visualization and high geometric accuracy, meeting the LoD 3 criteria. Validation using a roll meter yielded a root mean square error (RMSE) of 0.3552 meters, indicating considerable accuracy. The accuracy was further validated by showing LiDAR point cloud errors ranging from 7.92% to 15.75%. Linear regression analysis confirmed a high correlation (R2 0.9954) between LiDAR point cloud measurements and manual measurements, substantiating the method’s reliability. In order to accomplish reliable and precise indoor 3D mapping, this study combines the Velodyne VLP-16 3D-LiDAR sensor with the Pixhawk Cube Orange, which has a 9 Degrees of Freedom (DOF) IMU sensor. The study uses the LIO-SAM (LiDAR Inertial Odometry and Simultaneous Localization and Mapping) technique, which integrates data from LiDAR and IMU to increase mapping precision. It is carried out at the BAAK Dr. Angka Building, Institut Teknologi Sepuluh Nopember, Surabaya.

Single-Scene SAR Image Data Augmentation Based on SBR and GAN for Target Recognition

High-performance neural networks for synthetic aperture radar (SAR) automatic target recognition (ATR) often encounter the challenge of data scarcity. The lack of sufficient labeled SAR image datasets leads to the consideration of using simulated data to supplement the dataset. On the one hand, electromagnetic computation simulations provide high amplitude accuracy but are inefficient for large-scale datasets due to their complex computations and physical models. On the other hand, ray tracing simulations offer high geometric accuracy and computational efficiency but struggle with low amplitude correctness, hindering accurate numerical feature extraction. Furthermore, the emergence of generative adversarial networks (GANs) provides a way to generate simulated datasets, trying to balance computational efficiency with image quality. Nevertheless, the simulated SAR images generated based on random noise lack constraints, and it is also difficult to generate images that exceed the parameter conditions of the real image’s training set. Hence, it is essential to integrate physics-based simulation techniques into GANs to enhance the generalization ability of the imaging parameters. In this paper, we present the SingleScene-SAR Simulator, an efficient framework for SAR image simulation that operates under limited real SAR data. This simulator integrates rasterized shooting and bouncing rays (SBR) with cycle GAN, effectively achieving both amplitude correctness and geometric accuracy. The simulated images are appropriate for augmenting datasets in target recognition networks. Firstly, the SingleScene-SAR Simulator employs a rasterized SBR algorithm to generate radar cross section (RCS) images of target models. Secondly, a specific training pattern for cycle GAN is established to translate noisy RCS images into simulated SAR images that closely resemble real ones. Finally, these simulated images are utilized for data augmentation. Experimental results based on the constructed dataset show that with only one scene SAR image containing 30 target chips, the SingleScene-SAR Simulator can efficiently produce simulated SAR images that exhibit high similarity in both spatial and statistical distributions compared with real images. By employing simulated SAR images for data augmentation, the accuracy of target recognition networks can be consistently and significantly enhanced.

Role of oxide layer on corrosion resistance and surface conductivity of titanium bipolar plates for proton exchange membrane fuel cell

Heat-assisted forming (either hot stamping or multi-step forming with intermediate annealing) has been demonstrated as an effective novel forming process of titanium bipolar plate (Ti-BPP) with fine flow channels and high geometrical accuracy, where an oxide layer can be introduced to Ti-BPPs due to thermal oxidation. Although low-cost coating (e.g., amorphous carbon coating) is normally applied to Ti-BPPs in order to increase their corrosion resistance and surface conductivity, the impact and mechanism of oxide layer on the corrosion resistance and surface conductivity of coated Ti-BPPs remain unclear. This work finds that the oxide layer introduced by thermal oxidation enhances the corrosion resistance of coated Ti-BPPs (cathodic corrosion current density decreased from 1.54 to 0.54 μA/cm2) without reducing surface conductivity. The oxide layer thickens from <10 to 100–150 nm, with its primary composition changing from TiO2 to Ti3O during thermal oxidation and coating process. The presence of Ti3O enhances the resistance of the charge transfer and point defect migration of Ti-BPPs while moderating the capacitive behavior of amorphous carbon coating. Maintaining surface conductivity relies on two key mechanisms: the reduction of concentrated and film resistance by amorphous carbon coating, and the transformation of oxide layer's composition.

Tool wear prediction in broaching based on tool geometry

Abstract The aircraft engine is a safety-critical part of an aircraft. Constructive modifications resulting in ecological and economic improvements of the engine lead to necessary changes in manufacturing processes. The turbine discs in the low-pressure section are made of temperature resistant nickel-based superalloys. For the connection of the turbine blades with the disc, fir-tree slots are machined by broaching. The broaching process achieves high geometrical accuracy as well as process reliable rim zone properties. Alternative manufacturing processes such as milling or wire electrical discharge machining are still the subject of research in many applications and do not yet achieve the required process reliability. Especially in finishing operations, tool geometry is complex. In previous research work, the local rake angle and, as a result, the acting cutting force were determined analytically and empirically. Based on these results, the relationship between tool geometry, cutting force, and tool wear will be investigated in this work to enable a cutting length dependent prediction of tool wear. The aim of this work is a model-based prediction of tool wear for a given cutting length and a previously unknown tool geometry. For this purpose, a method was developed to predict tool wear using empirical test data as well as internal machine data. With the results of this work, it is not only possible to identify critical points on newly developed broaching tools by maxima of the cutting force, but also to predict wear locally, depending on the cutting length.

Generation of Customized Bone Implants from CT Scans Using FEA and AM.

Additive manufacturing (AM) allows the creation of customized designs for various medical devices, such as implants, casts, and splints. Amongst other AM technologies, fused filament fabrication (FFF) facilitates the production of intricate geometries that are often unattainable through conventional methods like subtractive manufacturing. This study aimed to develop a methodology for substituting a pathological talus bone with a personalized one created using additive manufacturing. The process involved generating a numerical parametric solid model of the specific anatomical region using computed tomography (CT) scans of the corresponding healthy organ from the patient. The healthy talus served as a mirrored template to replace the defective one. Structural simulation of the model through finite element analysis (FEA) helped compare and select different materials to identify the most suitable one for the replacement bone. The implant was then produced using FFF technology. The developed procedure yielded commendable results. The models maintained high geometric accuracy, while significantly reducing the computational time. PEEK emerged as the optimal material for bone replacement among the considered options and several specimens of talus were successfully printed.

Charged Gold Nanoparticles for Target Identification-Alignment and Automatic Segmentation of CT Image-Guided Adaptive Radiotherapy in Small Hepatocellular Carcinoma.

Because of the challenges posed by anatomical uncertainties and the low resolution of plain computed tomography (CT) scans, implementing adaptive radiotherapy (ART) for small hepatocellular carcinoma (sHCC) using artificial intelligence (AI) faces obstacles in tumor identification-alignment and automatic segmentation. The current study aims to improve sHCC imaging for ART using a gold nanoparticle (Au NP)-based CT contrast agent to enhance AI-driven automated image processing. The synthesized charged Au NPs demonstrated notable in vitro aggregation, low cytotoxicity, and minimal organ toxicity. Over time, an in situ sHCC mouse model was established for in vivo CT imaging at multiple time points. The enhanced CT images processed using 3D U-Net and 3D Trans U-Net AI models demonstrated high geometric and dosimetric accuracy. Therefore, charged Au NPs enable accurate and automatic sHCC segmentation in CT images using classical AI models, potentially addressing the technical challenges related to tumor identification, alignment, and automatic segmentation in CT-guided online ART.

Influences of curing depth and layer thickness on forming accuracy and mechanical properties of biphasic calcium phosphate bioceramics fabricated by vat photopolymerization

Vat photopolymerization (VPP) is a high potential and efficient method for fabricating advanced ceramics. However, the selection of printing strategy importantly determines the geometrical accuracy and mechanical strength of ceramic parts prepared by VPP. In this study, the effects of the curing depth (Cd) to layer thickness (Lt) ratio and Lt on forming accuracy, microstructures, mechanical properties, surface roughness of biphasic calcium phosphate (BCP) bioceramic green bodies and sintered bodies were investigated. When the Cd/Lt ratio was smaller than 4.0, and the Lt was not over 50 μm, the green bodies presented high forming accuracy (the dimension errors ˂ 3.50 %). Inappropriate Cd/Lt and Lt caused lots of defects including different types of cracks and delamination on green bodies and sintered bodies, and impaired their mechanical strength. The optimal Cd/Lt ratio and Lt were obtained to be 4.0 and 50 μm, in which parameters there were few cracks and delamination on the sintered BCP bioceramics. The flexural strength and the fracture toughness of sintered BCP increased when the Cd/Lt ratio increased from 3.0 to 4.0. However, the flexural strength and the fracture toughness decreased when the Cd/Lt ratio further increased to 5.0. The flexural strength of sintered BCP increased at first and then decreased when the Lt increased from 25 μm to 50 μm, and the fracture toughness and hardness of BCP decreased continually. The flexural strength of sintered BCP showed a maximum value of 113.21 MPa, and the maximum fracture toughness was 0.71 MPa∙m1/2. The elastic modulus and hardness of sintered BCP also reached 24.16 GPa and 3.04 GPa, respectively. The printing surface roughness of BCP bioceramics decreased when the Cd/Lt ratio or Lt increased. The lateral surface roughness decreased with the increase of Cd/Lt ratio, and increased with the increase of Lt. This new result provides a clear printing strategy for fabricating ceramics with high geometrical accuracy and mechanical properties by VPP technique.

Improving and Predicting the Surface Roughness and the Machining Accuracy in Ultrasonic Vibration-Assisted Milling

The present research work amis to develop a controlled vibratory system for improving the performance of slotting process based on the vibration-assisted milling technique. In addition, the establishment of a statistical model for predicting the process efficiency was a key aim target.In the current investigation, an ultrasonic vibratory device was designed to provide vibration oscillations in the cutting feed direction to the 7075 aluminum alloy workpiece side at 34.7 kHz frequency and 10 μm amplitude. A LabView code has been developed to control the input vibration parameters. A full factorial design of experiments with 4 factors and 2 levels was conducted. An in-depth statistical analysis is then implemented to study the effect of machining and vibration parameters on the process performance. Then, a statistical model for predicting the process response in terms of cutting force, surface roughness, and machining accuracy has been established.Some experiments showed a significant reduction in cutting force up to 50% in the feed direction. Additionally, an improvement in workpiece surface roughness was recorded. Regarding the machined surface accuracy, introducing ultrasonic vibrations significantly reduces the produced slot width error compared to Conventional Milling (CM).The developed statistical model shows a very well agreement with the experimental results. Therefore, the developed VAM technique is suitable for manufacturing parts that require high geometrical and dimensional accuracy.

Development of Multi-Strip Image Mosaicking for KOMPSAT-3A Images

Abstract. High-resolution satellite imagery has a limitation in terms of coverage area. This limitation presents challenges for extensive-scale analysis at regional or national levels. To maximize the utility of high-resolution satellite imagery, the implementation of image mosaicking techniques is essential. In this paper, we have developed seamline extraction techniques and relative geometric correction optimized for high-resolution satellite imagery. Ultimately, we proposed a multi-strip image mosaicking method for KOMPSAT-3A (Korea Multi-Purpose Satellite-3A) images. We applied the Dijkstra's shortest path algorithm to efficiently extract seamlines. we also performed image registration based on feature matching and homography transformation to correct the relative geometric errors between input images. We conducted experiments with our methods using 29 scenes from KOMPSAT-3A L1G data. The results indicated high relative geometric accuracy, with an average error of 1.63 pixels. Furthermore, we were able to obtain high-quality seamless mosaic images. Our proposed method is expected to enhance the utility of KOMPSAT-3A imagery for large-scale environmental and urban analysis and to provide more accurate and comprehensive data.

Direct-ink-write 3D printing of highly-stretchable polyaniline gel with hierarchical conducting network for customized wearable strain sensors

The development of direct-ink-write (DIW) 3D printing conducting polymer gels with remarkable mechanical properties, satisfactory conductivity, and customized three-dimensional structures is in high demand for next-generation wearable strain sensors, yet challenging due to the difficulty of preparing conducting polymer solutions with high concentrations. Herein, a novel cellulose nanocrystal (CNC)-regulated polyaniline (PANI) composite ink for DIW 3D printing customized wearable strain sensors with high stretchability and hierarchical conducting networks is fabricated. With the employment of CNC as a stabilizer to regulate the intermolecular interactions, the in-situ polymerized composite ink achieves well-dispersed PANI and abundant reversible intermolecular interactions, which is favorable for DIW 3D printing PANI composite gel with tailored planar patterns of high geometric accuracy. Benefiting from the hierarchical gel frameworks and abundant non-covalent interactions within the PANI-based composite ink, the PANI composite gel exhibits remarkable stretchability, promising low-temperature tolerance and excellent strain sensing performance. Due to its unique wavy mesh structure, the DIW-printed PANI composite gel-based wearable strain sensor is more sensitive and can accurately detect changes in the human body. This work aims to expedite the advancement of DIW printing conducting polymer gel for the development of personalized wearable strain sensors and advanced flexible electronics.

Effect of depositional strategy on surface roughness of Al-5%Mg wall fabricated via Cold Metal Transfer based Wire Arc Additive Manufacturing

Cold Metal Transfer (CMT) based Wire Arc Additive Manufacturing (WAAM) is the future-driven novel technology for fabricating complex metal components, having advantages like high deposition rates, increased material efficiency, lesser lead time, low heat input, and low cost. Despite of above advantages, the CMT-WAAM process possesses few limitations in terms of producing metal components with high geometrical accuracy. Al-Mg alloys are particularly appealing for their lightweight and exceptional mechanical properties, making them attractive for various industrial applications such as marine, automobile, aerospace, etc. In this study, an Al-5%Mg alloy single wall has been built through CMT-WAAM using Current at 110A, Travel Speed (TS) of 7 mm/sec, and Gas Flow Rate (GFR) of 15L /min. The effect of unidirectional and bidirectional deposition direction on the surface quality of the fabricated sample has been investigated. Surface roughness (Ra) tests were conducted at three different zones (upper, middle, and bottom) of the specimen wall before the machining operation using a taylor hobson surtronic tester. It is concluded from the results that the S2 wall (unidirectional) has more Ra value than the S1 wall (bidirectional) in all zones due to the presence of a humping defect which results in more waviness over the S2 wall’s surface. In the bidirectional strategy, the roughness value reduces by 8.567 % (upper zone), 9.95 % (middle zone), and 13.019 % (bottom zone) than the unidirectional strategy. Thereby establishing that the deposition direction tends to build WAAM wall with a better surface finish.

Ortho-NeRF: generating a true digital orthophoto map using the neural radiance field from unmanned aerial vehicle images

ABSTRACT True Digital Orthophoto Maps (TDOMs) have high geometric accuracy and rich image characteristics, making them essential geographic data for national economic and social development. Complex terrain and artificial structures, automatic distortion elimination and occluded area recovery in TDOM generation pose significant challenges. Hence, the need for further improvements in both mapping accuracy and automation is highlighted. In this paper, we present an approach for generating a TDOM based on a Neural Radiance Field (NeRF) without utilizing prior three-dimensional geometry information called an Ortho Neural Radiance Field (Ortho-NeRF). The Ortho-NeRF divides a large-scale scene into small tiles, implicitly reconstructing each tile by selecting pixels on posed images, and individually generate TDOMs of all tiles using a true-ortho-volume rendering before mosaicking. Additionally, the Ortho-NeRF uses a strategy to skip empty spaces and adaptively set the spatial resolution of a voxel grid, improving the generated TDOM quality with fewer computational resources. Many experiments showed that our approach outperforms ContextCapture, Metashape, Pix4DMapper, and Map2DFusion, especially in challenging areas. Owing to its global consistency and continuous nature, Ortho-NeRF was able to effectively reconstruct the geometry information and details, generating TDOMs without distortion or misalignment. Eight ground control points were randomly selected to evaluate the geometric accuracy of the TDOMs, with an average median error of 0.267 m. The length between two points on a plane was also measured for quantitative evaluation, with a mean absolute error of 0.08 m and a mean relative error of 0.14%. Compared with the NeRF efficiency, that of the Ortho-NeRF increased 104 times in training and about 1000 times in rendering.

Design of Sustainable Aluminium-Based Feedstocks for Composite Extrusion Modelling (CEM).

Additive manufacturing (AM) has become one of the most promising manufacturing techniques in recent years due to the geometric design freedom that this technology offers. The main objective of this study is to explore Composite Extrusion Modelling (CEM) with aluminium as an alternative processing route for aluminium alloys. This process allows for working with pellets that are deposited directly, layer by layer. The aim of the technique is to obtain aluminium alloy samples for industrial applications with high precision, without defects, and which are processed in an environmentally friendly manner. For this purpose, an initial and preliminary study using powder injection moulding (PIM), necessary for the production of samples, has been carried out. The first challenge was the design of a sustainable aluminium-based feedstock. The powder injection moulding technique was used as a first approach to optimise the properties of the feedstock through a combination of water-soluble polymer, polyethyleneglycol (PEG), and cellulose acetate butyrate (CAB) wich produces low CO2 emissions. To do this, a microstructural characterisation was carried out and the critical solid loading and rheological properties of the feedstocks were studied. Furthermore, the debinding conditions and sintering parameters were adjusted in order to obtain samples with the required density for the following processes and with high geometrical accuracy. In the same way, the printing parameters were optimised for proper material deposition.

Laser Powder Bed Fusion of Stainless Steel 316L for Rectangular Micropillar Array with High Geometrical Accuracy and Hardness

Laser Powder Bed Fusion of Stainless Steel 316L for Rectangular Micropillar Array with High Geometrical Accuracy and Hardness

Welding between confinements as a new approach for high deposition rate additive manufacturing with laser-assisted double wire welding with nontransferred arc

Laser-assisted double wire welding with nontransferred arc uses an electric arc to melt two welding wires fed toward each other. The molten material drips onto the substrate, where it is joined to the substrate without undercuts by means of oscillated laser radiation. The process offers possibility of creating structures with high deposition rates (8.4 kg/h), but faces challenges in fulfilling the requirements for surface properties and geometric accuracy. One approach to meet the requirements is to confine the final seam geometry by applying the melt into a mold. Such a confinement can be a wall previously applied by a process with higher geometric accuracy. An investigation of this approach was carried out by studying the deposition of mild steel weld beads within two confining structures, in this case, a groove. A particular interest in the evaluation is connection of the weld bead to the base material in the corners, the bottom surface, and the side surface of the groove. In the first step, weld beads are deposited in 12 mm wide grooves in a mild steel substrate with variable laser beam oscillation amplitudes of 10–13 mm. In the second step, several layers are deposited with variable welding speeds. The oscillation amplitude that generates the best connection in the corners is 13 mm. Bonding on the bottom and side surfaces could be achieved with all parameter sets. When applying several layers, the best lateral connection in the groove was produced with a welding speed of 200 mm/min.

Research on hybrid remanufacturing process chain of laser cladding, CNC machining and ultrasonic rolling for aero-engine blades

There are high geometric accuracy and mechanical performance requirements in the repair and remanufacturing process for aero-engine blades. Therefore, a synergy of multiple processes is necessary for blade repair. This paper mainly studies the coupling relationship between multiple processes of aero-engine blade repair and the influence and contribution of each process to the final surface integrity of the blade. Firstly, a hybrid remanufacturing process chain of laser cladding, CNC machining and ultrasonic rolling is proposed for the requirements of blade repair. Then, a numerical model of the geometric feature construction and transient thermal and structural behavior in the hybrid remanufacturing process chain for blades is established. Finally, the interaction law among the three processes of laser cladding, CNC machining and ultrasonic rolling is analyzed. The results show that a larger powder feed rate is allowed in the laser cladding process of the hybrid remanufacturing process chain for blades. Thermal deformation and residual stress caused by high powder feed rate and thin-walled structure can be optimized by CNC machining and ultrasonic rolling. In addition, the influence mechanism of the three processes on the final surface integrity is revealed. It is shown that the effects of the hybrid remanufacturing process parameters on the remanufacturing quality are different from that of the traditional process. The feasibility of the hybrid remanufacturing process chain for blades is illustrated by the verification experiment on the damaged blade.

Enhancing flexographic printing process with laser-induced microstructured printing forms for adjustable material transfer

Polymer optical waveguides are efficiently produced using flexographic printing, enabling fast and cost-effective manufacturing. However, the small print height results in a cross-sectional area too small for effective light coupling. To address this, multiple layers are printed to achieve the required waveguide dimensions. This sequential printing process prolongs processing time as material is repeatedly fed into the machine, potentially leading to issues like dust inclusions and oxygen inhibition. This study demonstrates modifying flexographic printing forms to increase transferred material height by up to 20 % in a single pass. Different microstructure geometries (hexagon, triangle, and square) with varying depths were inserted into the printing form to analyze their effects on material transfer. The use of a UV-nanosecond laser and a mask-based process allowed for precise insertion of the microstructures, resulting in high geometric accuracy and homogeneous ablation.

Influence of SLM block support design on geometrical quality of AISI 316 l cantilever features and its impact on post-processing

In Selective Laser Melting, the design of efficient support structures is the key to enable the production of high-quality functional parts exhibiting complex shapes with improved geometrical accuracy. Nonetheless, from a process point of view, supports are waste material that must be minimized to reduce production costs and post-processing. Despite the recent technological advances, support optimization is based on time- and resource-consuming trial-and-error experimental campaigns, while support removal is primarily a manual operation which requires a consistent human effort and consumable consumption. Nowadays, the industry is demanding a tool capable to optimize support design and placement based on part geometry and building orientation, by ensuring high part geometrical accuracy along with reduced timing for post-processing operations. Specifically, the purpose of this experimental campaign, is to evaluate the influence of support thickness and tooth length on the dimensional accuracy of AISI 316 l cantilever specimens in order to form a solid baseline of knowledge for the future realization of an automated algorithm for optimized support structure generation based on both part and process requirements. The experimental results show that the support thickness strongly affects the final part distortion, reducing the as-built geometrical deviation by 72.6% when wall thickness increases up to 0.7 mm, whereas tooth length has a higher impact on post-processing when decreased from 0.7 mm to 0.3 mm, reducing support time removal and consumables usage respectively up to 40.5% and 72.7%. The achieved results highlight that the implementation of optimized support structures ensuring low geometrical deviation and involving reduced resource consumption in post-processing is feasible. These findings provide the starting design rules for the engineering of an empirical methodology, based on thermomechanical modelling, enabling optimized design and implementation of SLM support structures.

High geometric fidelity through closed-loop control of the weld pool size in gas metal arc welding based direct energy deposition

Arc based direct energy deposition combines the flexibility of additive manufacturing with high build rates and low investment costs. However, high geometric fidelity of manufactured components is not possible with state-of-the-art methods. Highly varying and geometry-dependent boundary conditions, e.g. heat dissipation and the interpass temperature, are quasi-random influences with a strong impact on the geometric fidelity and the manufactured microstructure. Without adjusting for these variations, process stability decreases, geometric deviations become more likely and defects accumulate from layer to layer. A high geometric fidelity of the manufactured components can therefore not be guaranteed with the state of the art. Due to the large number of influencing variables in the arc-based manufacturing process, this problem cannot be solved by the definition of simple setpoints. Closed-loop control, however, offers the opportunity to flexibly counteract any deviations that occur by adjusting the process parameters in real time. Since the manufactured part is created by solidification from the weld pool, a closed-loop control of the weld pool size is being developed. The developed controller uses the weld pool properties and the interpass temperature as feedback variables and takes into account the non-linear system behaviour as well as the process noise and the parameter uncertainties. The subordinate control of the welding power source is further used for improved process stability. To the best of our knowledge, this solution provides a level of robustness, steady-state accuracy and geometric fidelity that has not been achieved by previous approaches reported in the literature. To illustrate the performance of this closed-loop control for components with low heat dissipation, we demonstrate the fabrication of thin-walled components with high geometric accuracy for a fast 3D printing process and investigate the influence of the welding process variables on the microstructure, the evaluation of the geometric fidelity is based on EN ISO 1101.

Machining of additively manufactured alloy 718 in as-built and heat-treated condition: surface integrity and cutting tool wear

AbstractAdditive manufacturing (AM) using powder bed fusion is becoming a mature technology that offers great possibilities and design freedom for manufacturing of near net shape components. However, for many gas turbine and aerospace applications, machining is still required, which motivates further research on the machinability and work piece integrity of additive-manufactured superalloys. In this work, turning tests have been performed on components made with both Powder Bed Fusion for Laser Beam (PBF-LB) and Electron Beam (PBF-EB) in as-built and heat-treated conditions. The two AM processes and the respective heat-treatments have generated different microstructural features that have a great impact on both the tool wear and the work piece surface integrity. The results show that the PBF-EB components have relatively lower geometrical accuracy, a rough surface topography, a coarse microstructure with hard precipitates and low residual stresses after printing. Turning of the PBF-EB material results in high cutting tool wear, which induces moderate tensile surface stresses that are balanced by deep compressive stresses and a superficial deformed surface that is greater for the heat-treated material. In comparison, the PBF-LB components have a higher geometrical accuracy, a relatively smooth topography and a fine microstructure, but with high tensile stresses after printing. Machining of PBF-LB material resulted in higher tool wear for the heat-treated material, increase of 49%, and significantly higher tensile surface stresses followed by shallower compressive stresses below the surface compared to the PBF-EB materials, but with no superficially deformed surface. It is further observed an 87% higher tool wear for PBF-EB in as-built condition and 43% in the heat-treated condition compared to the PBF-LB material. These results show that the selection of cutting tools and cutting settings are critical, which requires the development of suitable machining parameters that are designed for the microstructure of the material.