3D Parts Research Articles

MULTISENSOR FUSION-BASED DIGITAL TWIN IN ADDITIVE MANUFACTURING FOR IN-SITU QUALITY MONITORING AND DEFECT CORRECTION

AbstractEarly detection and correction of defects are critical in additive manufacturing (AM) to avoid build failures. In this paper, we present a multisensor fusion-based digital twin for in-situ quality monitoring and defect correction in a robotic laser-directed energy deposition process. Multisensor fusion sources consist of an acoustic sensor, an infrared thermal camera, a coaxial vision camera, and a laser line scanner. The key novelty and contribution of this work are to develop a spatiotemporal data fusion method that synchronizes and registers the multisensor features within the part's 3D volume. The fused dataset can be used to predict location-specific quality using machine learning. On-the-fly identification of regions requiring material addition or removal is feasible. Robot toolpath and auto-tuned process parameters are generated for defect correction. In contrast to traditional single-sensor-based monitoring, multisensor fusion allows for a more in-depth understanding of underlying process physics, such as pore formation and laser-material interactions. The proposed methods pave the way for self-adaptation AM with higher efficiency, less waste, and cleaner production.

3D polymer composite filament development from post‐consumer polypropylene and disposable chopstick fillers

AbstractThis study focused on the development of three‐dimensional (3D) polymer composite filament made of disposable chopstick (DC) and post‐consumer polypropylene (PPP). The PPP/DC composite parts were printed via fused filament fabrication (FFF) process. The effect of the printing temperature and different DC fiber content on the properties of the 3D printed parts were investigated. The printing temperature of 200–220°C was suitable for these filaments because the printing temperature did not show any thermal degradation, as proven by thermogravimetric analysis. Furthermore, the thermal stability of the 3D filament increased with DC content. The chemical modification with sodium hydroxide (NaOH) was carried out on DC to remove the unwanted organic components by showing changes in peak intensity in the Fourier transform infrared analysis. Moreover, the melt flow index of the composite filaments decreased with increasing of the DC content and caused the composites' viscosity increased. The results show that the optimum printing temperature of 210°C would reduce the warping and gave better tensile properties to the 3D printed parts. Nevertheless, the tensile strength and elongation at break of the 3D printed PPP/DC parts reduced as the DC content increased because the presence of some air gap and fiber pull out on the fracture surface of 3D printed parts, which are in line with the results observed from scanning electron microscopy. However, the tensile strength and elongation at break percentage of all 3D printed PPP/DC composite parts were higher in comparison with the 3D parts printed by commercial wood plastic composite filament.

Impact of controlled prewetting on part formation in binder jet additive manufacturing

Binder jetting is an additive manufacturing process that bonds powder through selectively depositing binder by inkjet printing. The part is then extracted and densified by sintering and/or infiltration. The process offers low costs and fast build rates, but properties can be poor due to residual porosity after sintering. The inkjet printing process may contribute to this residual porosity by creating large pores. The droplet kinetic energy ejects some powder particles from the bed and rearranges others. Particle ejection and rearrangement are theorized to create porous regions in binder-jetted parts. In this work, small amounts of moisture are added to the spread powder before printing and the impact on part formation, part properties, and printing parameters measured with varied droplet spacing, droplet velocity, and print frequency. Moisture is added by applying an atomized fluid mixture to the powder between layer spreading and binder printing. The fluid mixture partially evaporates but leaves a stable residue to increase cohesion and enhance imbibition. Moisture addition to the powder increases the range of droplet spacings for line formation while reducing particle ejection, powder rearrangement, and balling in layer and multilayer parts. Excessive moisture addition decreases the effective saturation of printed lines, but saturation in 3D parts is less impacted. Increased surface roughness in the first few layers of a print was also mitigated with prewetting. High-speed X-ray imaging verified prewetting reduction in particle ejection and rearrangement.

Communication of Design Data in Manufacturing Democratization

Part design is the principal source of communicating design intent to manufacturing and inspection. Design data are often communicated through computer-aided design (CAD) systems. Modern analytics tools and artificial intelligence integration into manufacturing have significantly advanced machine recognition of design specification and manufacturing constraints. These algorithms require data to be uniformly structured and easily consumable; however, the design data are represented in a graphical structure and contain a nonuniform structure, which limits the use of machine learning algorithms for a variety of tasks. This paper proposes an algorithm for extracting dimensional data from three-dimensional (3D) part designs in a structured manner. The algorithm extracts face dimensions and their relationships with other faces, enabling the recognition of underlying patterns and expanding the applicability of machine learning for various tasks. The extracted part dimensions can be stored in a dimension-based numeric extensible markup language (XML) file, allowing for easy storage and use in machine-readable formats. The resulting XML file provides a dimensional representation of the part data based on their features. The proposed algorithm reads and extracts dimensions with respect to each face of the part design, preserving the dimensional and face relevance. The uniform structure of the design data facilitates the processing of data by machine learning algorithms, enabling the detection of hidden patterns and the development of pattern-based predictive algorithms.

A Mathematical Model for Force Prediction in Single Point Incremental Sheet Forming with Validation by Experiments and Simulation

Incremental sheet forming (ISF) is an emerging technology that has shown great potential in forming customized three-dimensional (3D) parts without the use of product-specific dies. The forming force is reduced in ISF due to the localized nature of deformation and successive forming. Forming force plays an important role in modeling the process accurately, so it needs to be evaluated accurately. Some attempts have been made earlier to calculate the forming force; however, they are mostly limited to empirical formulae for evaluating the average forming force and its different components. The current work presents a mathematical model for force prediction during ISF in a 3D polar coordinate system. The model can be used to predict forces for axis-symmetric cones of different wall angles and also for incremental hole flanging. Axial force component, resultant force in the r-θ plane, and total force have been calculated using the developed mathematical model appearing at different forming depths. The cone with the same geometrical parameters and experimental conditions was modeled and simulated on ABAQUS, and finally, experiments were carried out using a six-axis industrial robot. The mathematical model can be used to calculate forces for any wall angle, but for comparison purposes, a 45° wall angle cone has been used for analytical, numerical, and experimental validation. The total force calculated from the mathematical model had a very high level of accuracy with the force measured experimentally, and the maximum error was 4.25%. The result obtained from the FEA model also had a good level of accuracy for calculating total force, and the maximum error was 4.89%.

Extended concentric arches model for piled beam-supported embankments

Geosynthetic-reinforced embankments founded on piled beams have emerged as a new ground modification technique for supporting earth embankments over deep soft subsoil. This paper presents an analytical model for this technique that combines parts of two existing analytical design models. The soil arching behaviour that divides the vertical embankment load into a part that is transferred to the piled beams directly, and the residual load part that rests on the geosynthetic, is described by the 3D part of the Concentric Arches (CA) soil arching model of van Eekelen et al. (2013 and 2015), which was adopted in CUR226:2016. The paper also compares the difference between adopting the 2D or the 3D part of this CA model. The tensioned geosynthetic effect was described by the membrane action equation of Pham (2020b). This equation calculates the geosynthetic strain and includes load–deflection behaviour, adhesion, and friction along the geogrid/soil interface. Two field studies and fully coupled hydromechanical finite element analyses were used to verify the proposed analytical approach and its assumptions. The paper compares the effect of founding geosynthetic-reinforced embankments on piles or piled beams. Finally, a parametric study showed the impact of beam width, center-to-center pile spacing, and geogrid stiffness on load transfer efficiency.

A comprehensive review of polymer materials and selective laser sintering technology for 3D printing

This review analyses different approaches used to study selective laser sintering (SLS) technology of polymer materials. These main approaches concern: thermal behaviour, fatigue and surface roughness.Regarding the first behaviour, researchers extensively studied the impact of process parameters, including scan speed, laser, power and laser energy density, on the thermal behaviour of 3D printed parts. Numerical and experimental analyses are used to conduct process parameter evaluations.Laser power and scan speed are the most significant parameters of the laser energy density. For the second, according to test protocols and quantitative analysis performed, the authors concluded that the combination of small and large laser energy density particles generates higher sintering and better fatigue resistance. Moreover, tensile analysis in different environments showed that testing in the water decreased the fatigue life of polymer samples. The influence of process parameters on the mechanical properties and surface roughness of 3D parts is also analysed. In addition, the investigators found that the additives increase the surface roughness of 3D printed parts.This review shows that researchers can focus on creating a combination of these approaches to expand the use of this process for industrial part production.All these investigations have made it possible to determine the optimal process conditions to ensure higher quality, optimal surface quality and better fatigue strength.

PRODUCTION OF WASTE JUTE DOPED PLA (POLYLACTIC ACID) FILAMENT FOR FFF: EFFECT OF PULVERIZATION

In recent years, there has been an outbreak of research on natural fiber-reinforced materials to reduce non-recycled material effects and produce environmentally friendly products. In parallel with the increasing popularity of additive manufacturing, the development of new natural fiber-reinforced materials in this field has also increased to improve pure material characteristics and reduce raw materials usage. This study presents the manufacturing process of %5 waste jute-reinforced PLA filaments and the characteristics of 3D printed parts. For the production of jute-reinforced filaments, polylactic acid (PLA) granules were pulverized to increase the material surface for better bonding between materials in the composite matrix structure. The effectiveness of pulverizing PLA granules was exposed by comparing it with the production of the same composite matrix with PLA granules. Both matrices were formed into filaments to produce 3D parts in Fused Filament Fabrication technology. Thermo-gravimetric analysis (TGA) and differential scanning calorimetry (DSC) will be presented in filament form. Besides, the mechanical properties of 3D parts will also be presented. Within the scope of the study, it is aimed to reveal the material size effect for producing natural fiber-reinforced filaments for additive manufacturing.

Surface Functionalization of 4D Printed Substrates Using Polymeric and Metallic Wrinkles.

Wrinkle topographies have been studied as simple, versatile, and in some cases biomimetic surface functionalization strategies. To fabricate surface wrinkles, one material phenomenon employed is the mechanical-instability-driven wrinkling of thin films, which occurs when a deforming substrate produces sufficient compressive strain to buckle a surface thin film. Although thin-film wrinkling has been studied on shape-changing functional materials, including shape-memory polymers (SMPs), work to date has been primarily limited to simple geometries, such as flat, uniaxially-contracting substrates. Thus, there is a need for a strategy that would allow deformation of complex substrates or 3D parts to generate wrinkles on surfaces throughout that complex substrate or part. Here, 4D printing of SMPs is combined with polymeric and metallic thin films to develop and study an approach for fiber-level topographic functionalization suitable for use in printing of arbitrarily complex shape-changing substrates or parts. The effect of nozzle temperature, substrate architecture, and film thickness on wrinkles has been characterized, as well as wrinkle topography on nuclear alignment using scanning electron microscopy, atomic force microscopy, and fluorescent imaging. As nozzle temperature increased, wrinkle wavelength increased while strain trapping and nuclear alignment decreased. Moreover, with increasing film thickness, the wavelength increased as well.

The economics of additive manufacturing ikand topology optimisation – a case analysis of the electric scooter

This article describes the process of topology optimisation (TO) of three components of an electric scooter, namely the neck, platform, and suspension bracket. We use these example parts to investigate the additive manufacturing (AM) workflow, from re-design to nesting and support approach that has an impact on the total costs and time required for product development and manufacturing, with a focus on Direct Metal Laser Sintering (DMLS) technology. Due to the mathematically generated shape, components that are topology optimised and fabricated through AM have improved structural load-to-weight ratio. The article elaborates on the cost of manufacturing these new geometrical structures and re-designing existing components. Recognising topology-optimised design features for the LPBF manufacturing process like creating touch points between parts in 3D nesting orientations and lattice structure integration reduces cost in volume production. Our study shows that it is beneficial for the DMLS process to perform finite element analysis (FEA) and optimise components using TO and lattice structures, as weight reduction also translates to cheaper fabricating parts. Defining and implementing a streamlined workflow for editing the complex automatically generated support structures improves manufacturability. Such approaches encourage companies to adopt wider LPBF processes in mainstream industries. Abbreviations: AM = additive manufacturing; DMLS = direct metal laser sintering; TO = topology optimisation; SLS = selective laser sintering; FEA = finite element analysis; CAD = computer-aided design; CAM = computer-aided manufacturing; 3D = three dimension; CAE = computer-aided engineering

Uncanny Valley Game in Virtual Environments

Nowadays, as VR technology is developing at an incredible rate, related topics such as the virtual environment, mobile equipment for VR, and metaverse are also becoming hot topics. The article will be depicting the process of researching the Uncanny Valley theory's demonstration in the virtual environment. We created a horror virtual reality game that simulates the environment in real life. In the early stage of making the game, we first discussed how to set a proper story background for the game to put in the environment we want for testing the theory. We got our inspiration from "Backroom". Based on our inspiration, we determined the art style of our game, and later, in 3D modeling parts, we designed several monsters. After finishing all the modeling and programming parts, we tested them in our group. Finally, we released it to the public with a questionnaire to test the public's response. After analyzing the collected data, most people will feel a feeling of horror with the environment we create. We can conclude that the Uncanny Valley theory might still be suitable for the virtual environment. It can show that the Uncanny Valley theory might suit more scales than we think. And for VR experiences, we can use this theory to better create a scary scene or experience, which could be used in in-game making or VR filmmaking.

Casting of high surface area electrodes enabled by low-temperature welding of copper nanoporous powders and nanoparticles hybrid feedstocks

Nanoporous metallic powders are proposed as electrodes for hydrogen production, current collectors in batteries, or active material in propellants to overcome limitations in reaction kinetics of their bulk solid counterpart. However, their consolidation into 3D parts via powder metallurgy while maintaining high mechanical performance is limited by their thermodynamic instability during sintering and poor flowability. This paper demonstrates the synthesis of spherical nanoporous copper powders (PCu) via dealloying of Cu-Al gas-atomized precursors with high-throughput (i.e., 0.1 kg/hr), moderate flowability (i.e., Carney flowrate of 32.9 s/50 g), moderate-oxygen content (i.e., < 12 at.%), high-surface area (∼12 m2/g) and free of precipitates. The nanoscale weldability of hybrid feedstocks composed of PCu (65.5 – 91.2 vol.%) and copper nanoparticles (8.8 – 34.5 vol.%) were harvested to sinter them at temperatures as low as a third of its melting point and overcome the metastability of PCu to preserve its high-surface area. Open-die casting in reducing atmospheres was employed at temperatures between 300 – 700 °C resulting in parts with ultimate compression strength of 3.6 – 17.8 MPa while forming electrically conductive solids with preserved nanoporosity (i.e., pore size 24 – 36 nm). Such feedstocks may be integrated with powder-based manufacturing processes such as powder injection molding and additive manufacturing to produce complex architectures.

Process of Pure Copper Fabricated by Selective Laser Melting (SLM) Technology under Moderate Laser Power with Re-Melting Strategy.

Pure copper (Cu) material, because of its high thermal conductivity, can be 3D printed to fabricate effective thermal management components. However, in the selective laser melting (SLM) process, due to copper's high optical reflectivity, Cu-based parts need to be printed using high laser power. In this study, we demonstrated 3D printing with a re-melting strategy is able to fabricate high-density and low-surface-roughness pure copper parts using only a moderate laser (350 W) power. The effect of the re-scan to initial scan speed ratio on the printing quality resulting from the re-melting strategy is discussed. The re-melting strategy is likened to a localized annealing process that promotes the recrystallization of the newly formed copper microstructures on the re-scan path. Given a hatch spacing of 0.06 mm and a powder layer thickness of 0.05 mm, Cu samples with 93.8% density and low surface roughness (Sa~22.9 μm) were produced using an optimized scan speed of 200 mm/s and a re-scanning speed of 400 mm/s, with a laser power of 350 W. Our work provides an approach to optimize the laser power for printing pure copper 3D parts with high relative density (low porosity) and low surface roughness while ensuring the lifetime stability of the part. The re-melting strategies have broad implications in 3D printing and are particularly relevant for metals with high reflectivity, such as pure copper.

Effects of powder properties on the 3D printing of BaTiO3 ceramic resins by stereolithography

Stereolithography is a layer-by-layer building fabrication technique enabling production of advanced ceramic 3D shapes that are not achievable by other methods. Critical parameters of stereolithography are associated with the preparation of a ceramic resin exhibiting suitable rheological and optical properties, as well as tunable curing property to achieve the desired level of resolution of complex 3D parts. However, tailoring the cure depth for each layer is challenging for functional ceramics due to their high refractive index giving increased light scattering. Here, the stereolithography 3D printing of BaTiO3 ceramic resins is investigated by employing a desktop 3D printer (λ = 405 nm) and a commercial base resin. The effects of two BaTiO3 powders with different size distributions (one micro-sized powder with grains in the range 1–20 µm, and one agglomerated nano-sized powder in the range 60–100 nm), on the viscosity and curing characteristics of the ceramic resins were investigated. It is shown that the nano-sized powder resulted in increased viscosity, increased scattering, and reduced cure depth compared to the micro-sized BaTiO3 ceramic resin. In general, the cure depth decreased with increasing ceramic loading. Successful prints were obtained for an overcuring of at least 40% between layers to assure good adherence between the layers. The printing properties of the ceramic resins from both powders were suitable for printing green parts with 50 µm layer thickness.

Direct Energy Depositions of a 17-4 PH Stainless Steel: Geometrical and Microstructural Characterizations

Direct energy deposition (DED) is a widely accepted additive manufacturing process and a possible alternative to the subtractive manufacturing processes due to its high flexibility in fabricating new 3D parts. DED enables the manufacture of complex parts without using costly and time-consuming conventional processes, even though building parameters need to be accurately determined. In the present investigation, the effect of different process parameters on geometrical features, quality, microstructure, and microhardness of 17-4 PH stainless steel single tracks deposited onto an AISI 316L stainless steel substrate was investigated. Four sets of process parameters, considering different values of laser power, scanning speed, and powder feed rate, were selected in the manufacturing strategy, and specimens drawn from each single-track deposition were analyzed by stereomicroscopy, optical microscopy (OM), scanning electron microscopy (SEM-EDS), and X-ray diffraction (XRD). The results show that the optimized geometrical features of the track, together with the best microstructural and hardness properties, were obtained with the highest values of the laser energy input.

Fast layer fiber orientation optimization method for continuous fiber-reinforced material extrusion process

Material extrusion (MEX) is an additive manufacturing process that uses thermoplastic layer-by-layer building. The use of continuous fiber-reinforced filament enhances mechanical properties, making MEX suitable for use in aerospace, automotive, and robotics industries. This study proposes a laminate optimization method to improve the stiffness of printed parts with low computing time. The 2D stress-flow-based method optimizes fiber’s orientation for each layer in the stacking direction, giving results for a 3D part optimization in a few minutes. Developed with Ansys Parametric Design Language, the computation tool was tested on printed wrenches, resulting in an 18% increase in stiffness. The proposed method is applicable to any printable shape.

Conduction Heat Study of Different Coil Design of Electric Iron

Electric iron pulls energy from the mains supply and heats a coil within then the heat is transferred to the bottom plate through conduction process which is placed against the wrinkled garment. The problem of existing dry iron is the heating element continues to get hotter until the power source is continuously drawn from electricity, do not heat up sufficiently, needed a continual charge from its platform every few minutes for prolonged use, cannot be heat up rapidly and fast aging problem. Hence, it is necessary to run the finite element analysis on electric iron part model. The simulation focusses on thermal analysis as it can ease the study related to the heat path and thermal design of simulated product that can be used to improve the efficiency of existing product. The 3D part models of electric iron and five different type of heating coil were designed. Rheological data and important properties of the electric irons were imported as a parameter database in the software to create the meshing on the model. The input parameters are heat power, heat flux and convection while the variable for the simulation process are design of heating coil, power supply, thickness of heating coil and material of soleplate. Based on the simulated part model, the features recommended is design coil 4 with power supply 1900W, coil thickness 0.0015m and ceramic soleplate as these variables has highest temperature and shortest steady state time.

3D Printing for Repair: An Approach for Enhancing Repair

The availability and storage of spare parts are the main barriers to product repair. One possibility would be to 3D print spare parts, which would also enable the repair of products not intended to be repaired. Besides manufacturers, 3D printing spare parts is an interesting option for self-repair by consumers. However, the digitisation of spare parts for 3D printing is a challenge. There is little guidance on how to make a 3D-printed version of the original part. This paper establishes a framework through a literature review and experimental study to describe how to use 3D printing to produce spare parts for repair. Additionally, qualitative data coding was used to find the influence of previous experience, process implementation, and part complexity on the overall success of the 3D printing for repair (3DPfR) process. Our study showed that the 3DPfR process can be described as an iterative design for an additive manufacturing process that is integrated into a repair process. Additionally, it was found that the incorrect implementation of process steps was the most important predictor of the repair result. The steps that were performed incorrectly the most were synthesising design concepts (64%) and validating print quality (also 64%).

Preliminary Study of the Bactericide Properties of Biodegradable Polymers (PLA) with Metal Additives for 3D Printing Applications

Plastic is a highly used material in various sectors. Due to its plentiful availability in the environment, microorganism surface contamination is a risk. The aim of this work is to achieve bactericidal capacity in plastics that reduces the microorganism's colonization risk and, consequently, reduces the chances of having an infection with E. coli and Listeria monocytogenes bacteria. Using polylactic acid (PLA) as the polymeric matrix, mixtures in concentrations of metal additive of ions of silver (Ag) R148 and S254 in 1% and 2% have been studied and manufactured. The materials are developed on an industrial scale through a process that proceeds as follows: (I) a mixture of polymer and additive in a double-screw compounder to obtain the compound in different concentrations, (II) the manufacture of filaments with a single-screw extruder, (III) 3D printing parts. Therefore, materials are evaluated in the form of powder, pellets and printed pieces to ensure their antibacterial effectiveness throughout the manufacturing process. The results of the research show antibacterial effectiveness for E. coli and Listeria monocytogenes of metal additives and polymeric compounds for all manufacturing phases on an industrial scale, with the effectiveness for additive R148 predominating at a concentration of 2%, demonstrating its microbial efficacy on surfaces with potential application in medicine.

Kernel-based feature aggregation framework in point cloud networks

Various effective deep networks have been developed for analysis of 3D point clouds. One key step in these networks is to aggregate the features of orderless points into a compact representation for the cloud. As a typical order-invariant aggregation method, max-pooling has been widely applied. However, while enjoying simplicity and high efficiency, max-pooling does not fully exploit the feature information since it not only ignores the non-maximum elements in each feature dimension but also neglects the interactions between different dimensions. These drawbacks of max-pooling motivate us to explore advanced feature aggregation methods for 3D point cloud analysis. The desired advanced method should be capable of modeling richer information between the point features than max-pooling, and, at the same time, it can readily replace max-pooling without the need to modify other parts of the existing network architecture. To this end, this paper proposes a novel kernel-based feature aggregation framework for 3D point cloud analysis for the first time. The proposed method effectively considers all the elements in each dimension and models the nonlinear interactions between feature dimensions as complementary information to max-pooling. In addition, it is a plug-in module that can be integrated to many common networks as a replacement of max-pooling. Comprehensive experiments are conducted to demonstrate the consistently superior performance and high generality of the proposed method over max-pooling. Specifically, the proposed kernel-based feature aggregation framework consistently improves the max-pooling with three representative backbones of PointNet, DGCNN and PCT across four 3D point cloud based analysis tasks, including supervised 3D object classification, 3D part segmentation, indoor semantic segmentation and one additional unsupervised place retrieval task. Especially, it shows remarkable performance improvement over max-pooling in the unsupervised retrieval task, demonstrating its advantage in forming 3D point cloud representation.