Fused Deposition Modeling Research Articles

Advancement of nanofiller reinforced fused filament fabrication polymers: A path to sustainable, weather-resistant 3D printing materials

Recent studies have focused on developing new materials capable of withstanding diverse environmental or weathering conditions, including sunlight, temperature, moisture, and chemicals, for various outdoor applications. Nowadays, nanotechnological advancements have opened possibilities for the development of polymer nanocomposites, which exhibit superior mechanical and weathering properties over traditional materials. However, there is limited literature available that summarizes the improvements in the mechanical and weathering properties of nanocomposites specifically for FFF. This paper provides a concise review of composite material development through the incorporation of nanofillers (NFs) to enhance product strength and durability. The primary focus is on examining the effect of the inorganic nanofillers, especially metal oxides NFs (TiO2, ZnO, SiO2), on the mechanical and weathering properties of the polymers in different manufacturing processes. Paper also covered the challenges and opportunities along with the applications of metal oxide-based polymer nanocomposites for outdoor use.

Development of ANN model for predicting mechanical properties of 3D printed PEEK polymer using FDM and optimization of process parameters for better mechanical properties

Additive manufacturing (AM) has evolved from a proven technology to a rapid prototyping tool with great potential. This technology is widely used in many industries such as automotive, aerospace, and medical; fused deposition modeling (FDM) is a popular 3D printing technique for producing PEEK (polyether ether ketone) parts, including implant prosthetic teeth. In this study, artificial neural network (ANN) modeling, parametric optimization, and experimental examination of PEEK 3D printing were conducted to enhance 3D printing processes. In this study, four critical process factors (infill density, layer height, printing speed, and infill pattern) influence the surface roughness, mechanical strength, and elastic modulus of the printed samples. Utilizing a 4–12–3 network design, this study demonstrates that an ANN model with an average error of less than 5% is optimal for all three responses. Furthermore, the study employed a teaching and learning based optimization algorithm (TLBO) and a non-dominated sorting genetic algorithm (NSGA) to optimize the printing process to obtain improved mechanical properties. The findings highlight TLBO’s ability to minimize surface roughness to 6.01 μm and NSGA’s capability to maximize the elastic modulus to 1253.35 MPa and ultimate tensile strength to 65.55 MPa. Microstructural studies supported the results obtained through parametric analysis and optimization.

Investigation of The Effect of CNC Milling Cutting Process on The Tensile Test of PLA Samples Produced Using Two Different 3D Printers with The FDM Method

One of the most commonly used materials in additive manufacturing with the fused deposition modeling (FDM) method is polylactic acid (PLA) filaments. In 3-dimensional (3D) printed products, an external wall is also used in addition to the internal structure pattern. The exterior wall pattern differs from the interior structure pattern. The 3D products obtained by this method contain two different pattern structures, which is not desired when determining the mechanical properties. In this study, tensile test specimens were produced with two different 3D printers using 1.75 mm and 2.85 mm diameter PLA filaments. Some tensile test specimens were directly produced in ASTM D638-14 Type 1 dimensions and subjected to tensile testing. The rest of the specimens were produced in a rectangular shape with 19 mm x 165 mm dimensions and the side edges of those specimens, produced in rectangular shape, were cut with CNC milling to bring their dimensions to ASTM D638-14 Type 1. All tensile test specimens were manufactured with a thickness of 4 mm. The test specimens cut with CNC milling after 3D printing were compared with the specimens tested only by 3D printing. The effects of CNC milling cutting on the tensile test properties of specimens produced on two different 3D printers using 1.75 mm and 2.85 mm diameter PLA filaments were investigated. Consequently, it was observed that cutting the side edges with CNC milling eliminated irregularities caused by 3D printing due to the tensile stress in those areas and allowed for more regular and consistent fractures of test specimens. When compared with only the 3D-printed specimens, the elongation at break of the tensile test specimens whose side edges were cut with CNC milling resulted in 13.45% and 33.55% higher using 1.75 mm and 2.85 mm PLA filaments, respectively. It was determined that the toughness of the samples cut by CNC milling was higher than the test samples that were only 3D printed.

Prediction of tensile strength using machine learning algorithms in fused deposition modeling

Prediction of tensile strength using machine learning algorithms in fused deposition modeling

Numerical simulation of the first layer printing in electric field-assisted fused filament fabrication for robust unconventionally oriented additive manufacturing

Fused filament fabrication (FFF) stands as a prominent thermoplastic additive manufacturing technique that has a wide range of potential applications. However, the conventional FFF process encounters limitations in unconventional environments, particularly in environments devoid of gravity, such as in extraterrestrial environments or in limited manufacturing conditions where maintaining consistent nozzle standoff distance becomes a challenging task. Fluctuations in nozzle standoff distance lead to inadequate material adhesion and dimensional errors, which results in a high failure rate and prolonged completion time. Thus, the conventional FFF process requires continuous monitoring or human intervention to ensure successful operation. To overcome the shortcomings of the traditional FFF process, an electric field-assisted FFF (E-FFF) process can be utilized to reduce the need for constant supervision and enable reliable production of parts. The E-FFF process integrates a high-voltage power supply unit with a standard FFF printer, generating an electrostatic force between the nozzle and the build plate. The generated electrostatic force can effectively attract the extruded molten polymer toward the build plate, even at a larger z-height of up to 1200 μm in unconventional build platform orientations such as vertical or reverse printing orientation. In this paper, finite element analysis is used to simulate the FFF and E-FFF process. The simulation focuses on the adhesion between extruded material and build plate with extended nozzle standoff distances and predicts the minimum voltage required to achieve a good material adhesion in unconventional orientations for the E-FFF process. The simulation model demonstrated its efficacy by estimating the minimum required voltage levels necessary for successful printing within the E-FFF process across a range of nozzle standoff distances in unconventional orientations.

Microhole Creation in FDM-Printed Sheet Polymers: A Punching Process Approach

Fused deposition modeling (FDM) 3D printing is one of the additive manufacturing processes that can make components with complex shapes, require no tools, are cheap, safe, and have minimal waste. Despite all the advantages of the FDM process, the inability of this technique to create holes on a micro scale can be a problem and limits its application. In this research, a combination of FDM and machining processes was carried out, where micro holes in FDM printed components were created using a punching process. The punching process is carried out by varying pressure and speed. Furthermore, the diameter of the hole and the quality of the sheared edge of the hole resulting from the punching process were evaluated through observation using an optical microscope. The results show that the holes resulting from the punching process have a better shape and diameter than the FDM process. Then, the analysis of the sheared edge from punching shows that pressure and speed significantly affect the surface quality of the resulting sheared edge, where the quality increases with increasing pressure and speed. In the end, the punching process was proven to create micro-scale holes in FDM-printed polymer, especially at minimum thickness.

An alternative filament fabrication method as the basis for 3D-printing personalized implants from elastic ethylene vinyl acetate copolymer

In this work, a novel tool for small-scale filament production is presented. Unlike traditional methods such as hot melt extrusion (HME), the device (i) allows filament manufacturing from small material amounts as low as three grams, (ii) ensures high diameter stability almost independent of the viscoelastic behavior of the polymer melt, and (iii) enables processing of materials with rheological profiles specifically tailored toward fused filament fabrication (FFF). Hence, novel materials, previously difficult to process due to HME limitations, become easily accessible for FFF for the first time. Here, we showcase the production of highly flexible drug-free, and drug-loaded filaments based on ethylene-vinyl acetate polymers with a vinyl acetate content of 28 w% (EVA28) and unprecedented high melt flow rates of up to 400 g/10 min. Owing to their low viscosity, FFF with low print nozzle sizes of 250 μm was achieved for the first time for EVA28. These small nozzle diameters facilitate 3D-printing of high-resolution structures in small-dimensional dosage forms such as subcutaneous implantable drug delivery systems, which can later be used for personalization. Consequently, the material portfolio for FFF is tremendously broadened, allowing material and formulation optimization toward FFF, independent of a preliminary extrusion process.

3D printing novel enteric capsule shells for personalized drug delivery

Individualized drug delivery presents a viable strategy for enhancing medication efficacy and patient safety. It involves producing small batches of custom dosages tailored to each patient’s individual needs. However, current pharmaceutical manufacturing processes are not designed for personalized dosage forms. Additive manufacturing processes have great potential in the pharmaceutical industry due to the customizable nature of 3D printing technologies and the increasing demand for customized pharmaceutics and drug delivery systems. Conventional enteric capsules are prepared by dip coating to achieve gastro-resistant release, but the manufacturing process is erratic and unreliable. This study aimed to investigate the feasibility of manufacturing enteric capsules from enteric polymers using the hot melt extrusion (HME) and fused filament fabrication (FFF) process. HME was utilized to prepare filaments using enteric polymers, Hypromellose acetate succinate (HPMC-AS), and Eudragit-L 100–55, with plasticizers, sorbitol, and polyethylene glycol 4000 (PEG-4000), and a thermoplastic polymer, polyvinyl alcohol (PVA). A computer-aided design program was utilized to design size 0 capsules. The prepared capsule design and filaments were used to fabricate capsules using the FFF process. Powdered red dye was used to simulate the drug and its release from FFF fabricated capsules was evaluated in simulated gastric and intestinal fluids, pH 1.2 and 6.8, respectively. Various combinations of enteric polymer, plasticizer, and thermoplastic polymer were examined. Thermogravimetric analysis (TGA) showed that the temperatures used for processing polymer blends were well below their thermal degradation temperatures, and dye release profiles were generated using image analysis software. This study demonstrates that capsules made with HPMCAS, PEG-4000, and PVA via the FFF process are suitable for controlling drug release and that the release profile can be modified by making small changes to the formulation.

The acoustic properties of FDM printed wood/PLA-based composites

The acoustic properties of the Fused Deposition Modelling (FDM) printed PLA wood composite was investigated. Initially tensile and flexural of wood PLA composite was studied with respect to varying layer thickness (0.15 mm, 0.20 mm, and 0.30 mm), infill density (30 %, 60 %, and 90 %), and pattern (Layer, Triangle, and Hexagon). The outcomes demonstrated that the specimen produced with a hexagonal pattern, 90% infill density, and 0.2 mm layer thickness had the highest tensile (16 MPa) and flexural strength (16 MPa). Utilizing this optimized parameter, micro-perforated panels were printed and acoustic properties were studied. Five specimens with a 3 mm thickness, various perforation diameters (5 mm, 4 mm, and 3 mm), and architecturally tapered perforations were fabricated. Using the impedance tube approach, the sound transmission loss and sound absorption coefficients were measured. The findings indicate that, in comparison to all the printed specimens, tapered type perforation with an exterior diameter of 5 mm and an internal diameter of 4.7 mm showed highest sound absorption coefficient of 0.60 Hz. A viscous loss is obtained by its convergent hole diameter reduction, which results in sound attenuations and is easily absorbed in the micro-perforated panel. Similar to this, the specimen printed with smaller perforation diameters (3 mm) had a high sound transmission loss of 79 dB. The small diameter of the perforations prevented the passage of sound waves. The current study is anticipated to lay the groundwork for extensive future research on these classes of materials, potentially serving as a catalyst for advancements in FDM based polymeric materials research and development.

Optimization and prediction of additively manufactured PLA-PHA biodegradable polymer blend using TOPSIS and GA-ANN

Recent years have seen the proliferation of fused deposition modeling (FDM) as a means of manufacturing biodegradable products, for different applications such as rigid packaging, agricultural and biomedical. Blends of Polyhydroxyalkanoates (PHA) and polylactic acid (PLA) have been investigated to ascertain their prospective applications through FDM. This paper includes three parameters that affect the build process: layer height, nozzle temperature, and flow rate. 3D printed PLA/PHA can be characterized mechanically, and process parameters can be optimized to maximize design functionality. The experimental setup utilized a Taguchi L9 design, and TOSPIS was employed to optimize the output results. Using TOPSIS analysis, 0.2 mm layer thickness, 195 °C nozzle temperature, and 100 % flow rate were found to be the most optimal initiation parameters. The Taguchi analysis was used to analyze the output responses, and it was found that layer height had the greatest influence on mechanical properties, followed by flow rate and nozzle temperature. The percentage elongation at break has been improved significantly by adding PHA i.e., 170 % compared to PLA (5–10 %). This paper presents a framework for in-depth mechanical characterization of PLA-PHA 3D-printed parts, along with methods for optimizing process parameters to achieve optimal performance, as well as tools for modeling output responses using GA-ANN with an accuracy of 95 %.

Melt flow analysis in rotational nozzle fused filament fabrication process

Fused filament fabrication (FFF) is a widely used processing method; however, heat transfer limitations within a conventional nozzle result in relatively low flow rates, leading to lengthy production times, compared to traditional processing methods, ultimately restricting its industrial application. Recently, a novel rotational nozzle FFF three-dimensional (3 D) printer has been patented and developed to enhance processing efficiency. Despite this achievement, the fundamental mechanisms behind this novel process remain unclear. In this study, both analytical analysis and numerical simulations were conducted based on a force-controlled scaled-down experimental setup. This setup, designed according to the pressure-induced melt removal theory, provided melt throughput data under varying heater temperatures, extrusion forces, and rotational speeds. Agreement between the modeling and experimental results confirms the generalizability of the models. Modeling predictions of temperature and velocity distributions indicate that viscous dissipation affects the average temperature and filament velocity. To simulate the real-world working conditions of FFF 3 D printing, a velocity-controlled simulation was introduced. It was observed that the average melt film thickness increases with nozzle rotational speed due to viscous dissipation. Additionally, the extrusion force required for the same printing speed decreases with increasing nozzle rotational speed, primarily due to the higher shear rate reducing melt viscosity.

Advancing 3-Dimensional Printed Burr Hole and Craniotomy Models for Neurosurgical Simulation Through Multimaterial Methods

Objective3D printing technology presents a promising avenue for the development of affordable neurosurgical simulation models, addressing many challenges related to the use of cadavers, animal models, and direct patient engagement. The aim of this study is to introduce and evaluate a new high-fidelity neurosurgical simulation model targeted for both burr hole and craniotomy procedures. MethodsTwelve different 3D printed skull models were manufactured using five different materials (PEEK, White Resin, Rigid10K, BoneSTN, SkullSTN) from three different 3D print processes (Fused Filament Fabrication, Stereolithography, Material Jetting). Six consultant neurosurgeons conducted burr holes and craniotomies on each sample while blinded to these manufacturing details. Participants completed a survey based on the qualities of the models, including; mechanical performance, visual appearance, interior feeling, exterior feeling, sound, overall quality, and recommendations for training purposes based on their prior experience completing these procedures on human skulls. ResultsThis study found that the multi-material stereolithography printed models consisting of White Resin for the outer table and Rigid 10K for the diploe and inner table were successful in replicating a human skull for burr hole and craniotomy simulation. This was followed by the porous General BoneSTN preset material on a Stratasys J750 Digital Anatomy Printer. ConclusionsThe findings indicate that widely accessible and economical desktop stereolithography 3D printers can provide an effective solution in neurosurgical training, thus promoting their integration in hospitals.

Dynamics of non-Newtonian fluid–fiber interactions and void formation mechanism based on fused filament fabrication

Due to the presence of internal defects such as voids in the composites manufactured by material extrusion additive manufacturing (MEX AM), the mechanical properties of the composites are significantly below the theoretical optimum. Under this circumstance, this paper is intended to investigate the effects of nozzle feeding angles and to analyze the void formation and evolution of multiphase flow, in which systematic computational fluid dynamics numerical simulations are conducted. The volume of fluid model and overset grid method are used to simulate the extrusion deposition process of carbon fiber-reinforced polymer composites, and the Carreau model is used to represent the shear-thinning behavior of molten polymer. The numerical method is validated against previously experimental and numerical simulation data. The numerical results show that the key factor leading to void formation is the vortices caused by fiber oscillation. The intense vortex at the front end of the fibers disrupts the interface between molten polymer and air, creating a beneficial condition for air to enter. Nozzle tilting can effectively reduce the probability of void formation by decreasing the fiber oscillation velocity. The results of the present study provide insights into the development and optimization of printer nozzles to enable the printing of longer fibers with less probability of potential void formation.

Microstructure and compressive behaviour of PLA/PHA-wood lattice structures processed using additive manufacturing

This study investigates the microstructure and compressive behaviour of PLA/PHA-wood lattice structures manufactured using fused filament fabrication (FFF). The primary objective is to evaluate the effects of defects, such as porosity and surface roughness, on the mechanical properties of these lattice structures. X-ray micro-tomography (XRT) and finite element analysis are employed to compare CAD models with real lattice structures, offering insights into defect-induced performance deviations. The novel approach integrates experimental and numerical methods to better understand damage accumulation in porous structures. The methodology includes uniaxial compression testing and image processing for microstructural characterization. Results reveal significant differences in relative density and stress concentration due to manufacturing defects. In particular, 3D printed lattice structures display typical cellular material behaviour with a primary bending deformation mechanism. X-ray tomography reveals that process-induced porosity generate stress heterogeneity, which is not captured from CAD-based model resulting in an overestimation of the stiffness. The study concludes that accounting for these defects can be quantified by shifting the target relative density to compensate lack of performance in 3D-printed lattice materials.

A deep learning framework for automated anomaly detection and localization in fused filament fabrication

Under-extrusion poses a common challenge in filament 3D printing, necessitating precise adjustments to printing parameters for optimal resolution. Swift identification of this flaw is crucial for implementing timely corrective measures. In response, we present a novel machine learning approach designed to detect anomalies in 3D printing, specifically in the fused filament fabrication process (FFF). Our framework utilizes “You Only Look Once” (YOLO), a real-time object detection system, and “Visual Geometry Group-16” (VGG-16), a Convolutional Neural Network (CNN) model for image recognition, to accurately identify and localize under-extrusion events. Initially, models such as VGG-16, VGG-19, and ResNet-50 were trained without the inclusion of YOLO to establish baseline accuracies. Subsequently, an automated image pre-processing phase employs YOLO to discern the nozzle head, facilitating subsequent cropping around the region of interest for retraining the models. This inclusion of the nozzle head detection approach significantly improved the accuracy of all models, with the combined application of YOLO and VGG-16 demonstrating the most substantial enhancement, boosting detection accuracy to 97%. Moreover, Gradient-weighted Class Activation Mapping (Grad-CAM) technique, another CNN-based method, is employed to effectively highlight predicted areas in under-extrusion scenarios. While our method significantly advances the automatic detection of printing anomalies, it primarily serves as a diagnostic tool, signaling the need for intervention. Our rigorous testing on images of varying complexities confirms the model’s robustness, evaluated using comprehensive metrics such as precision, recall, and F1 score.

Effects of Ultrasonic Vibration on 3D Printing of Polylactic Acid/Akermanite Nanocomposite Scaffolds

The mechanical properties of 3D-printed scaffolds for load-bearing implantation are crucial. Although the addition of nanoparticles to polymeric matrix scaffolds can improve their mechanical and biological properties, due to certain limitations in printability, high amounts of reinforcement cannot be used. Therefore, in this study, an attempt was made to use ultrasonic (UT) vibration to inhibit nozzle clogging during fused filament fabrication (FFF) of polylactic acid (PLA) scaffolds including 0, 20, and 40 wt.% Akermanite (Ak). Nozzle clogging happened during the conventional 3D printing of PLA-40wt.%Ak, while that did not occur during UT-assisted 3D printing of PLA-40wt.%Ak. Results of X-ray Diffraction (XRD) analysis and Scanning Electron Microscopy (SEM) indicated that applying ultrasonic (UT) vibration had no negative effect on the phases and morphology of the scaffolds. The results obtained by the compression test indicated that applying UT during 3D-printing resulted in almost 27% increment of elastic modulus and almost 25% increase of the compressive strength of the scaffolds. As the conclusion, this study highlights the effectiveness of ultrasonic-assisted 3D printing in producing nanocomposite scaffolds with significantly higher nanoparticle loadings, as compared to conventional printing methods. By utilizing ultrasonic vibration during the printing process, the study showcases the possibility of overcoming viscosity limitations and optimizing the mechanical performance of scaffolds for various biomedical applications, including bone tissue engineering.

Influence of Printing Parameters to optimize mechanical properties in additive manufacturing – A Review

Abstract Additive manufacturing (3D printing) is a revolutionary technology with widespread applications among various industries. It is a cost effective and fast prototyping technology of 20th century, the parts produced by 3D printing are not only used for pre-production samples but also for replacement of functional parts in various applications. Various methods of 3D printing technologies viz., Fused Deposition, Resin printing etc., are available, however Fused Deposition Modelling (FDM) technique is very popular since it is promising and cost effective. There are two major aspects needs to be considered in preparing a sample from 3D printing, i.e., selection of material and printing parameter. With the advancement of material technology from time to time, the efficient and quality products that are produced with this technology. The present study explores the impact of various parameters that affect mechanical properties of 3D printed Polylactic Acid (PLA) in horizontal orientation.

Investigating the mechanical properties and crashworthiness of hybrid PLA/GFRP composites fabricated using FDM-filament winding

The failure and crashworthiness performance of hybrid Polylactide (PLA)/Glass Fiber Reinforced Polymer (GFRP) composite tubes subjected to axial and radial quasistatic compression loads were investigated in the present study. The composite tubes are fabricated using hand lay-up and Fused Deposition Modeling (FDM)-filament winding processes. The crashworthiness performance was studied using parameters such as the peak load, energy absorption, crush load, crushing load efficiency, and specific energy absorption. The highest peak loads from the compression test results in the axial and radial directions are calculated using variations in the filament winding PLA/GFRP (FPG) specimen, whose values were 16130.50 N and 12077.33 N, respectively. The highest mean crush load is found in the material variation with the FPG specimen, which is 5734.43 J/mm for axial loading and 4886.75 J/mm for radial loading. The highest energy absorption (EA) value is found in the material variation with the FPG specimen, which is 262.18 J for axial direction loading and 94.02 J for radial direction loading. The highest specific energy absorption (SEA) value is found in the material variation with the specimen Filament Winding PLA/GFRP, which is 16.92 J/g for axial loading and 10.98 J/g for radial loading. There are three main types of failure of the composite: matrix cracking, fiber damage, and folding. The study showed that by combining Additive Manufacturing and composite lamination, the hybrid PLA/GFRP specimen outperformed the existing structures.

Direct Ink Writing 3D Printing Elastomeric Polyurethane Aided by Cellulose Nanofibrils.

3D printing of a flexible polyurethane elastomer is highly demandable for its potential to revolutionize industries ranging from footwear to soft robotics thanks to its exceptional design flexibility and elasticity performance. Nevertheless, conventional methods like fused deposition modeling (FDM) and vat photopolymerization (VPP) polyurethane 3D printing typically limit material options to thermoplastic or photocurable polyurethanes. In this research, a water-borne polyurethane ink was synthesized for direct ink writing (DIW) 3D printing through the incorporation of cellulose nanofibrils (CNFs), enabling direct printing of complex, monolithic elastomeric structures at room temperature that can maintain the designed structure. Additionally, a solvent-induced fast solidification (SIFS) method was introduced to facilitate room-temperature curing and enhance mechanical properties. The 3D-printed WPU structures demonstrated strong interfacial adhesion, exhibiting high ultimate tensile strength of up to 22 MPa and an elongation at break of 951%. The 3D-printed WPU structures also demonstrated outstanding resilience and durability, capable of enduring more than 100 cycles of compression and tension as well as withstanding vehicle crushing and heavy lifting. This method also shows suitability for 3D printing complex structures such as a vase and an octopus.

An experimental analysis of mechanical properties for a dissimilar pattern structure in the 3-D printing of a PLA5F filament using the Taguchi method

Abstract Many automobile components and machine parts can be fabricated using the Fused Deposition Modeling (FDM) process with materials such as Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS), Polyethylene Terephthalate Glycol (PET-G), and polymeric composite materials (e.g., PLA with carbon fiber, PLA with glass fiber). In this study, a new polymeric composite material was fabricated using Polylactic Acid and natural flax fiber was analysed for tensile stress, elongation, and impact load resistance using Taguchi Analysis. This analysis optimized the printing parameters, including layer thickness (0.15, 0.25, 0.35 mm), nozzle movement speed (80, 100, 120 mm s−1), filling structure (Lines - a, Triangular - b, and Octet - c), and occupancy rate (20%, 40%, 60%). The American Society for Testing and Materials (ASTM) standards for tensile strength (ASTM D638) and impact strength (ASTM D256) were used for evaluation. As a result, layer thickness was found to be the most effective variable for improving tensile characteristics, compared to extruder temperature, occupancy rate, or filling structure pattern. Mechanical properties including a layer thickness of 0.25 mm, an occupancy ratio of 20% for the bottom of the 2nd layer and 40% for the top of the 4th layer, triangular and octet filling structures, a nozzle speed of 100 mm s−1, and an extruder temperature of 200 °C are considered the most appropriate parameters for producing automotive parts in Three Dimensional (3D) Printing. Due to its tensile properties and impact strength resistance, these settings can be utilized in potential application in a wide variety of machine parts and vehicle components.