3D Parts Research Articles

Using 3D Density-Gradient Vectors in Evolutionary Topology Optimization to Find the Build Direction for Additive Manufacturing

Given its layer-based nature, additive manufacturing is known as a family of highly capable processes for fabricating complex 3D geometries designed by means of evolutionary topology optimization. However, the required support structures for the overhanging features of these complex geometries can be concerningly wasteful. This article presents an approach for studying the manufacturability of the topology-optimized complex 3D parts required for additive manufacturing and finding the optimum corresponding build direction for the fabrication process. The developed methodology uses the density gradient of the design matrix created during the evolutionary topology optimization of the 3D domains to determine the optimal build orientation for additive manufacturing with the objective of minimizing the need for support structures. Highly satisfactory results are obtained by implementing the developed methodology in analytical and experimental studies, which demonstrate potential additive manufacturing mass savings of 170% of the structure’s weight. The developed methodology can be readily used in a variety of evolutionary topology optimization algorithms to design complex 3D geometries for additive manufacturing technologies with a minimized level of waste due to reducing the need for support structures.

Large Biaxial Recovered Strains in Self‐Shrinking 3D Shape‐Memory Polymer Parts Programmed via Printing with Application to Improve Cell Seeding

AbstractTrapping of strain in layers deposited during extrusion‐based (fused filament fabrication) 3D printing has previously been documented. If fiber‐level strain trapping can be understood sufficiently and controlled, 3D shape‐memory polymer parts could be simultaneously fabricated and programmed via printing (programming via printing; PvP), thereby achieving precisely controlled 3D‐to‐3D transformations of complex part geometries. Yet, because previous studies have only examined strain trapping in solid printed parts—such as layers or 3D objects with 100% infill—fundamental aspects of the PvP process and the potential for PvP to be applied to printing of porous 3D parts remain poorly understood. This work examines the extent to which strain can be trapped in individual fibers and in fibers that span negative space and the extent to which infill geometry affects the magnitude and recovery of strain trapped in porous PvP‐fabricated 3D parts. Additionally, multiaxial shape change of porous PvP‐fabricated 3D parts are for the first time studied, modeled, and applied in a proof‐of‐concept application. This work demonstrates the feasibility of strain trapping in individual fibers in 1D, 2D, and 3D PvP‐fabricated parts and illustrates the potential for PvP to provide new strategies to address unmet needs in biomedical and other fields.

Atomic layer deposition of TiO2 on porous polysulfone hollow fibers membranes for water treatment

Numerous membranes devoted to water treatment are made of Polysulfone (PSF) and can suffer from performance deterioration because of the intrinsic hydrophobicity of this material. Modifying membrane surface allows the engineering of its physicochemical properties and can achieve improved permeability and anti-fouling efficiency by tuning the membrane hydrophilicity or porosity. Atomic layer deposition (ALD) is a unique technology that provides highly conformal and uniform coatings layers such as oxides over surfaces of three-dimensional (3D) parts, porous materials and particles. In this work, titanium dioxide (TiO2) was deposited on polysulfone hollow fibers (HF) membranes via ALD using TiCl4 and H2O as precursors. Membranes obtained with increasing number of deposition ALD cycles were tested until the pores were totally blocked. The morphology, structure and mechanical properties of membranes were not altered. The deposition was confirmed by scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDX) and X-ray Photoelectron Spectroscopy (XPS) analyses. The deposition of TiO2 enhanced by 50% the water permeability and by 20% the fouling resistance of the PSF HF membranes until only 20 ALD cycles. This is accompanied by an increase of hydrophilicity and a pores size reduction.

Influence of process parameters on the microstructure of laser printed NdFeB alloys

In this study, a methodology, based on the realization of single-track beads to the elaboration of 3D parts, was implemented in order to understand the microstructure of the laser printed NdFeB permanent magnets. An homemade powder was used, and the microstructures of the elaborated samples were characterized. For 3D parts measurement of the magnetic properties with various heat treatments were also carried out. The results demonstrate the effect of the laser parameters on the microstructure, especially on iron nucleation and on the transition from columnar to equiaxed growth. After an optimized heat treatment, the printed magnets exhibit a coercivity HcJ = 551 kA/m, a remanence Br = 0.55 T and an energy product (BH)max = 38 kJ.m−3.

Three-dimensional vortex dipole solitons in self-gravitating systems.

We derive the nonlinear equationsgoverning the dynamics of three-dimensional (3D) disturbances in a nonuniform rotating self-gravitating fluid under the assumption that the characteristic frequencies of disturbances are small compared to the rotation frequency. Analytical solutions of these equations are found in the form of the 3D vortex dipole solitons. The method for obtaining these solutions is based on the well-known Larichev-Reznik procedure for finding two-dimensional nonlinear dipole vortex solutions in the physics of atmospheres of rotating planets. In addition to the basic 3D x-antisymmetric part (carrier), the solution may also contain radially symmetric (monopole) or/and antisymmetric along the rotation axis (z-axis) parts with arbitrary amplitudes, but these superimposed parts cannot exist without the basic part. The 3D vortex soliton without the superimposed parts is extremely stable. It moves without distortion and retains its shape even in the presence of an initial noise disturbance. The solitons with parts that are radially symmetric or/and z antisymmetric turn out to be unstable, although, at sufficiently small amplitudes of these superimposed parts, the soliton retains its shape for a very long time.

Photothermal bleaching of nickel dithiolene for bright multi-colored 3D printed parts

HP’s Multi Jet Fusion is a powder bed fusion 3D printing technology that utilizes a carbon-based radiation absorber in combination with a near infrared (NIR) light source to facilitate the fusion of polymer powder in a layer-by-layer fashion to generate 3D parts. Most available carbon-based and NIR radiation absorbers have an intrinsic dark color, which as a result will only produce black/gray and dark colored parts. However, there are many applications that require variable color, including prosthetics, medical models, and indicators, among others. To create white, bright colored, and translucent parts with MJF, a visibly transparent and colorless radiation absorber is required. In this paper, we designed an activating fusing agent (AFA) that contains a red, strong NIR absorbing dye that turns colorless after harvesting irradiation energy during the MJF 3D printing process and provide a bright colored part when working with other color agents.

Multi-scale modeling of process-induced pressure distribution inside 3D woven composites manufactured using Resin Transfer Molding

This paper presents a novel computationally efficient multi-scale thermo-chemo-mechanical procedure combining up-scale and resolved-scale simulations to predict pressure evolution inside a 3D woven composite part during the Resin Transfer Molding (RTM) process. The developed procedure benefits from the linearity of a previously developed anisotropic temperature- and degree of cure-dependent thermo-chemo-viscoelastic constitutive law which allows for a relatively fast predictions at different length-scales. The RTM process parameters were measured during an actual 3D woven composite manufacturing, and used as a boundary conditions to the developed procedure. The predicted pressure evolution was used to compute the volume fraction of the polymer matrix where the pressure was lower than the threshold below which, as shown in previous works, the formation of porosities may occur.

PointGLR: Unsupervised Structural Representation Learning of 3D Point Clouds.

This work explores the use of global and local structures of 3D point clouds as a free and powerful supervision signal for representation learning. Local and global patterns of a 3D object are closely related. Although each part of an object is incomplete, the underlying attributes about the object are shared among all parts, which makes reasoning about the whole object from a single part possible. We hypothesize that a powerful representation of a 3D object should model the attributes that are shared between parts and the whole object, and distinguishable from other objects. Based on this hypothesis, we propose a new framework to learn point cloud representations by bidirectional reasoning between the local structures at different abstraction hierarchies and the global shape. Moreover, we extend the unsupervised structural representation learning method to more complex 3D scenes. By introducing structural proxies as the intermediate-level representations between local and global ones, we propose a hierarchical reasoning scheme among local parts, structural proxies, and the overall point cloud to learn powerful 3D representations in an unsupervised manner. Extensive experimental results demonstrate that the unsupervised representations can be very competitive alternatives of supervised representations in discriminative power, and exhibit better performance in generalization ability and robustness. Our method establishes the new state-of-the-art of unsupervised/few-shot 3D object classification and part segmentation. We also show our method can serve as a simple yet effective regime for model pre-training on 3D scene segmentation and detection tasks. We expect our observations to offer a new perspective on learning better representations from data structures instead of human annotations for point cloud understanding.

Introducing electric field fabrication: A method of additive manufacturing via liquid dielectrophoresis

Biomedical devices with millimeter and micron-scaled features have been a promising approach to single-cell analysis, diagnostics, and fundamental biological and chemical studies. These devices, however, have not been able to fully embrace the advantages of additive manufacturing (AM) that offers quick prototypes and complexities not achievable via traditional 2D fabrication techniques (e.g., soft lithography). This slow adoption of AM can be attributed in part to limited material selection, resolution, and inability to easily integrate components mid-print. Here, we present the feasibility of using liquid dielectrophoresis to manipulate and shape a droplet of build material, paired with subsequent curing and stacking, to generate 3D parts. This Electric Field Fabrication (EFF) technique is an additive manufacturing method that offers advantages such as new printable materials and mixed-media parts without post-assembly for biomedical applications.

Interfacial adhesion strength between FDM-printed PLA parts and surface-treated cellulosic-woven fabrics

PurposeThe purpose of this study is to investigate surface treatments and fiber types on adhesion properties polylactic acid (PLA) three-dimensional (3D) parts printed on woven fabrics.Design/methodology/approachThe cotton, flax and jute fabrics were exposed to alkali, hydrogen peroxide, stearic acid and ionic liquid treatments to modify surface characteristics before PLA 3D printing. The modification efficiency was assessed with Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) analyses. Then, fused deposition modeling (FDM) printer and PLA filament were used for 3D printing onto the untreated and treated fabrics. The adhesion strength between the fabrics and PLA 3D parts were tested according to DIN 53530 via universal tensile tester.FindingsThe fabric structure is effective on adhesion force and greater values were observed for plain weave fabrics. Maximum separation forces were obtained for alkali pretreated fabrics among jute and cotton. Hydrogen peroxide treatment also increased adhesion forces for jute and cotton fabrics while decreasing for flax fabrics. Stearic acid and ionic liquid treatments reduced adhesion forces compared to untreated fabrics. Treatments are effective to alter adhesion via changing surface chemistry, surface morphology and fabric physical properties but display different effects related to fabric material.Originality/valueThis study provides experimental information about effects of different fiber types and surface treatments on adhesion strength of PLA 3D parts. There is limited research about comprehensive observation on 3D printing on cellulosic-woven fabrics.

The mechanical behavior of the Ti6Al4V/Ti/Ti6Al4V composite produced by directed energy deposition under impact loading

Additive manufacturing (AM) technologies allow to produce the 3D parts of complex geometry using strong materials such as Ti6Al4V alloys. Moreover, the functionally graded materials can be easily created by AM. By combining the material with opposite mechanical characteristics, such as the ductile Ti metal and the strong Ti6Al4V alloy, it is possible to increase the total strength-ductility of the composite material which extends its application area. In the present work, the effect of the Ti layer in the Ti6Al4V/Ti/Ti6Al4V composite on the mechanical behavior of the material is considered. The value of the Ti part plays a key role in the impact strength of the composite material for as-built and annealed states. The heat treatment significantly increases the impact strength by removing the brittle martensite phase. For the tensile properties, the benefits of the combination ductile-strength properties are achieved only after the heat treatment of the composite due to a dominance of the brittleness from the Ti6Al4V part.

Investigation of the Effect of Laser Fluence on Microstructure and Martensitic Transformation for Realizing Functionally Graded NiTi Shape Memory Alloy via Laser Powder Bed Fusion

Nowadays, additive manufacturing (AM) of NiTi shape memory alloy is a challenging topic for the realization of 3D functional parts. Particularly, Laser Powder Bed Fusion (LPBF) of NiTi powder is one of the most challenging processes belonging to AM, thanks to its best performances in terms of productivity and precision of geometrical complexity. The control of the functional performances in NiTi components requires a strong interaction between technological and metallurgical approaches. In fact, a strong correlation among the process conditions, the microstructure, and the final functional performances, beyond the defects associated with the process are needed to be understood and analyzed. In the present work, the correlation between the feasibility map of processability and the obtained microstructure, which can be tailored according to the use of different energy density values, of Ni-rich NiTi powder processed with LPBF is investigated. In detail, discrete energy density values, in the range 60–300 J/mm3, were correlated to microstructure, Ni:Ti ratio, and transformation temperatures of the martensitic transformation, analyzed with SEM, EBSD, EDX, and DSC characterizations, respectively. An increase in laser energy density was found to promote Ni evaporation, which induced a change of the microstructure from austenite to martensite at room temperature. A consequent shift of the transformation temperatures to higher values and a change in microstructural texture was achieved. These achievements can support the identification of the feasibility range for manufacturing functionally graded NiTi SMA, requiring tailored functional properties located in selected positions in the 3D parts.

A Low-Cost Process for Fabricating Reinforced 3D Printing Thermoplastic Filaments.

Low-cost desktop-sized fused deposition modeling (FDM) printers have been widely embraced by small to large-scale institutions and individuals. To further enhance their utility and increase the range of materials that they can process, this work proposes a low-cost solution that adapts to low-cost desktop-sized extruders and enables them to fabricate filaments comprising a wide range of nonorganic reinforcing particles. This solution will fill a gap in the field, as low-cost fabrication techniques for reinforced filaments have been lacking. In the proposed solution, particles are heated and deposited on thermoplastic pellets to form a coating. Coated pellets are subsequently extruded using a low-cost desktop single-screw extruder. The effectiveness of the process is demonstrated by fabricating polylactic acid (PLA) filaments reinforced with two types of reinforcements, namely, dune sand and silicon carbide. Filaments' stiffness and strength were measured, and their microstructure along their lateral and longitudinal directions were investigated. Improvements in tensile strength (up to 8%) and stiffness (up to 4.5%) were observed, but at low reinforcement levels (less than 2 wt%). Results showed that the proposed process could be used to fabricate filaments with multiple types of particles. The produced filaments were successfully used to fabricate 3D parts using a commercial desktop FDM printer.

RI-Fusion: 3D Object Detection Using Enhanced Point Features With Range-Image Fusion for Autonomous Driving

The 3D object detection is becoming indispensable for environmental perception in autonomous driving. Light detection and ranging (LiDAR) point clouds often fail to distinguish objects with similar structures and are quite sparse for distant or small objects, thereby introducing false and missed detections. To address these issues, LiDAR is often fused with cameras due to the rich textural information provided by images. However, current fusion methods suffer the inefficient data representation and inaccurate alignment of heterogeneous features, leading to poor precision and low efficiency. To this end, we propose a plug-and-play module termed range-image fusion (RI-Fusion) to achieve an effective fusion of LiDAR and camera data, designed to be easily accessible by existing mainstream LiDAR-based algorithms. In this process, we design an image and point cloud alignment method by converting a point cloud into a compact range-view representation through a spherical coordinate transformation. The range image is then integrated with a corresponding camera image utilizing an attention mechanism. The original range image is then concatenated with fusion features to retain point cloud information, and the results are projected onto a spatial point cloud. Finally, the feature-enhanced point cloud can be input into a LiDAR-based 3D object detector. The results of validation experiments involving the KITTI 3D object detection benchmark showed that our proposed fusion method significantly enhanced multiple mainstream LiDAR-based 3D object detectors, PointPillars, SECOND, and Part <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{A}{^{2}}$ </tex-math></inline-formula> , improving the 3D mAP (mean Average Precision) by 3.61%, 2.98%, and 1.27%, respectively, particularly for small objects such as pedestrians and cyclists.

Improvement of the Quality of 3D Printing in the Mass Production of Parts

The article highlights the experience of using 3D printing at automotive enterprises manufacturing automotive wiring. The primary attention was paid to optimizing technologies and modernizing equipment in 3D printing in production conditions. This helped to improve the printing quality at the enterprise and reduce energy consumption during mass printing of parts. The article aims at improving quality and reducing energy consumption during 3D printing in serial production conditions. The technique’s novelty consists of a complex of production optimizations combined into a production rack to improve 3D printing. During the research, negative factors affecting print quality and their elimination were analyzed. An experimental setup for 9 printers was created. As a result, ways to increase energy efficiency according to environmental standards were implemented under the mass production of 3D parts. Overall, the applied technology allowed for reducing the time for the development of new prototypes. This made it possible to reduce the produced parts cost and allowed for implementing urgent changes in manufacturing enterprises.

A Machine Learning Approach to Find Density Percentage Error Resulting by Infill Patterns in Additive Manufacturing

This paper presents employing Machine Learning in predicting the error involved in the output density of the additive manufactured parts. Due to the fact that the density of a 3D part is related to the filled volume inside the body, the characteristics of infill lines become important. The existence of density percentage error is proven in previous studies, and it shows the deviation of actual infill density from the desired input density requested by the user. Since the amount of density error is different for various setups of infill parameters, being able to predict the density percentage error without going through the full calculation provides the base for infill setup optimization with the objective to minimize this error. A procedure is shown on how to work on the density error, by selecting a 2D infill pattern, recognizing the corresponding input parameters, and set up the error estimating. This study represents density percentage error prediction for a generic cubic model using a neural network. The developed results demonstrate the accuracy of the implemented neural network in predicting the density percentage error while the infill input parameters are changed.

Constitutive model for corrosion fatigue crack growth in 3D parts

Constitutive model for corrosion fatigue crack growth in 3D parts

PELATIHAN SOLIDWORKS 3D CAD BAGI SISWA SEKOLAH MENENGAH KEJURUAN DI DESA CIANTRA

The aim of this program is to develop the potential of students in the field of design before entering the industrial world. As time goes by, technology advances rapidly, the manufacturing industry continues to attract jobs along with increasing investment. In this case, it requires competent human resources. This activity can increase students' understanding and skills before entering the world of work later. The program that has been implemented is Solidworks 3D CAD training through zoom meetings. This training was given to Vocational High School students in the Ciantra village environment for three meetings on 20, 26 and 27 February 2022. The method used is a demonstration, participants follow the tutorial material from the teacher step by step. Prior to the implementation of the activity, participants were given an introduction to Solidworks module to make it easier for students to understand. The training materials include an explanation of the Solidworks toolbar, the creation of two-dimensional (2D) drawings and the creation of three-dimensional (3D) parts. The results of the training can increase students' knowledge in drawing techniques using Solidworks software. In addition, it can improve students' skills in designing workpieces. It is hoped that by improving the skills of these students it will become capital before entering the industrial world.

Self-activating metal-polymer composites for the straightforward selective metallization of 3D printed parts by stereolithography

The integration of multifunctional elements directly embedded in three-dimensional (3D) printed parts is the cutting-edge of additive manufacturing (AM) and it is crucial for enlarging as well as for strengthening AM role in industrial applications. Here, a straightforward and low-cost method that synergically combines stereolithography (SLA) and selective electroless metallization (EM) is presented for the fabrication of 3D parts characterized by complex shapes and end-use multifunctionalities (conductive, magnetic, mechanical properties). To this end, a novel photocurable composite based on acrylate resin loaded with nickel (Ni) particles is developed for high-resolution SLA-printing of features with self-catalytic properties for EM. Ni particles are loaded in the resin to trigger metal deposition avoiding time consuming and expensive laser-based surface activation. The effect of Ni content on SLA behavior as well as on the efficiency of EM process is studied. Metallized SLA cured samples show good electrical and magnetic properties as well as improved robustness with respect to their non-loaded counterparts. Then, selective metallization of 3D printed parts is successfully achieved by implementing a multi-material SLA-printing where loaded and non-loaded resins are properly interchanged with strong adhesion at the interface, thus offering a cost-effective approach for rapid prototyping of functional free-form features on 3D structures.

The Reuse method of the Part CNC process based on 3D feature matching

Aiming at the problem of efficient reuse of existing parts CNC process, this paper presents a reuse method of the part CNC process based on 3D feature matching. It’s assumed the part which is the most similar to the 3D features of the new part has been found in the CNC history library. To reuse the CNC process of the existing part, the CNC programs and machining parameters of the existing part are imported into the new part as the machining template firstly, then the improved 3D polar radius surface moments are used to extract the 3D shape and position vectors of the machining area of each CNC program of the existed part and each face of the new part, finally the weighted Euclidean distance is used as a metric to find the most similar matching of each machining area in the new part, and the matching result is optimized by the greedy algorithm based fragmented surface matching algorithm and the overall optimization algorithm. Hundreds of sets of 3D feature similar parts were verified in the prototype system based on this method. The results show that this method can effectively reuse the existing CNC parts, and significantly improve the efficiency of CNC programming.