Infill Density Research Articles

Effect of Infill Density Percentage and Printing Direction on Bending Fatigue Properties of Polylactide Specimens Manufactured by Fused Filament Fabrication

Effect of Infill Density Percentage and Printing Direction on Bending Fatigue Properties of Polylactide Specimens Manufactured by Fused Filament Fabrication

Effect of Curvature Shape on the Impact Strength of Additively Manufactured Acrylonitrile Butadiene Styrene Parts Produced via Fused Deposition Modeling

Additive manufacturing (AM) has greatly revolutionized manufacturing due to its ability to manufacture complex shapes without the need for additional tooling. Most AM applications are based on geometries comprising curved shapes subjected to impact loads. The main focus of this study was on investigating the influence of infill density and the radius of curvature on the impact strength of parts manufactured via an FDM process. Standard geometrical specimens with varying part infill densities and radii of curvature were produced and subjected to Charpy impact tests to evaluate their impact strength. The results suggest that the impact strength increases with the increased density caused by higher amounts of material as well as by the changing cross-sectional areas of the beads. Also, the radius of curvature of the parts shows a clear inverse relationship with the impact energy absorbed by the specimens (i.e., increasing the radius decreased the impact energy of the parts) produced via an FDM process, which can be explained using the beam theory of structural mechanics. The maximum value of impact strength obtained was 287 KJ/m2, and this was achieved at the highest infill density (i.e., solid) and for the smallest radius of curvature.

Precision in dentistry: how PLA 3D printing settings influence model accuracy.

Advancements in computer-aided design and manufacturing (CAD/CAM), such as intraoral scanners, digital treatment planning, and 3D printers, offer digital alternatives to conventional orthodontics. For transforming digital data into atraditional model, precise 3D printing technologies are necessary. With numerous settings available on each 3D printer, selecting the most precise one is challenging. Therefore, the impact of layer height, printing temperature, print speed, and infill density on the accuracy of dental models was analyzed in this study. A3D file of aright upper central incisor was designed and printed 275 times in total with different settings for temperature, layer height, print speed, and infill density by using polylactic acid (PLA) filament on an industrial 3D printer. After scanning the models, root mean square error was calculated for analysis of precision. For each group, R2 value was calculated and linear regression as well as an ANOVA was performed for the factors influencing accuracy. Printing temperature as well as layer height had statistically significant impacts on printing 3D tooth models (p < 0.05). R2 values of 0.43 for printing temperature as well as of 0.11 for layer height were detected. The infill density as well as the print speed had no statistically significant impacts on accuracy (p > 0.05). This study confirms that choosing the correct printing temperature and layer height for printing dental models with PLA is important for obtaining good accuracy, whereas print speed and infill density have less of an impact.

Optimizing Mechanical Properties of Recycled 3D-Printed PLA Parts for Sustainable Packaging Solutions Using Experimental Analysis and Machine Learning

Abstract: Increasing environmental concerns and the need for sustainable materials have driven a focus towards the utilization of recycled polylactic acid (PLA) in additive manufacturing as PLA offers advantages over other thermoplastics, including biodegradability, ease of processing, and a lower environmental impact during production. This study explores the optimization of the mechanical properties of recycled PLA parts through a combination of experimental and machine learning approaches. A series of experiments were conducted to investigate the impact of various processing parameters, such as layer thickness and infill density, as well as annealing conditions, on the mechanical properties of recycled PLA parts. Machine learning algorithms have proven the possibility to predict tensile behavior with an average error of 6.059%. The results demonstrate that specific combinations of processing parameters and post-treatment annealing differently improve the mechanical properties (with 7.31% in ultimate tensile strength (UTS), 0.28% in Young’s modulus, and 3.68% in elongation) and crystallinity (with 22.33%) of recycled PLA according to XRD analysis, making it a viable alternative to virgin PLA in various applications such as sustainable packaging solutions, including biodegradable containers, clamshell packaging, and protective inserts. The optimized recycled PLA parts exhibited mechanical properties and crystallinity levels comparable to those of their virgin counterparts, highlighting their potential for reducing environmental impact and saving costs. For both as-built and annealed samples, the optimal settings for achieving high composite desirability involved a 0.2 mm layer thickness, with 75% infill for the as-built samples and 100% infill for the annealed samples. This study provides a comprehensive framework for optimizing recycled PLA in additive manufacturing, contributing to the advancement of sustainable material engineering and the circular economy.

Optimizing the Material Extrusion Process for Investment Casting Mould Production

This study investigates the optimization of the Material Extrusion (MEX) process for producing polylactic acid (PLA) patterns used in investment casting moulds, specifically targeting the casting of non-ferrous alloys such as brass. Key MEX process parameters—layer thickness, wall thickness, infill density, and post-processing with dichloromethane vapour for surface enhancement—were systematically analyzed for their impact on mould quality. Results indicate that an optimized combination of MEX parameters yields moulds with high dimensional accuracy, low surface roughness, and minimal pattern residue within the mould cavity. These optimized moulds were subsequently used in brass casting, with the final cast parts evaluated for dimensional precision and surface finish. The study concludes that PLA patterns manufactured via optimized MEX parameters provide a precise, cost-effective, and easy-to-implement solution for industry applications. Additionally, this process is environmentally friendly and presents clear advantages over other pattern-making methods, offering a sustainable alternative for producing complex metal parts with reduced environmental impact. The findings underscore the significant role of post-processing in enhancing mould quality and, consequently, the quality of the cast parts.

Impact of structural characteristics on energy-absorption of 3D-printed thermoplastic polyurethane line-oriented structures

Purpose Additive manufacturing offers the ability to produce complex, flexible structures from materials like thermoplastic polyurethane (TPU) for energy-absorption applications. However, selecting optimal structural parameters to achieve desired mechanical responses remains a challenge. This study aims to investigate the influence of key structural characteristics on the energy absorption and dissipation behavior and the deformation process of 3D-printed flexible TPU line-oriented structures. Design/methodology/approach Samples with varying line orientations and infill densities were fabricated using material extrusion and subjected to quasi-static compression tests. The design of experiments methodology explored the significance of design variables and their interaction effects on energy absorption and dissipation. Findings The results revealed a statistically significant interaction between infill density and orientation, highlighting their combined influence; however, the effect was less pronounced compared to infill density alone. For low-density structures, changing the orientation from 0°/90° to 45°/−45° and increasing infill density enhanced energy absorption and dissipation, while high-density structures exhibited unique energy absorption behavior influenced by deformation patterns and heterogeneity levels. This study facilitates the prediction of mechanical responses and selection of suitable TPU line-oriented printed parts for energy absorbing applications. Originality/value To the best of the authors’ knowledge, the present work have investigated for the first time the energy-related responses of flexible line-oriented TPU structures highlighting the distinction between the low and high density structures.

Evaluation of flexural strength of 3D-Printed nylon with carbon reinforcement: An experimental validation using ANN

This study investigates the flexural strength of 3D-printed nylon-carbon reinforced composite specimens, highlighting the impact of infill density and layer height on mechanical performance. The findings indicate that a printing layer height of 0.10 mm with 100 % infill density exhibits the highest flexural strength, supporting a maximum load of 127 N, compared to 76.7 N at 50 % infill density. Microstructural study has clearly illustrated the structural distortion, revealing that a rise in layer height correlates with an escalation in structural distortion. An Artificial Neural Network (ANN) model is thus utilized to achieve high predictive accuracy in order to predict flexural behaviour. R-values above 0.98 are obtained across training, validation, and test datasets, indicating that ANN-based modelling may be able to facilitate quick optimization of 3D printing parameters for high-performance applications. These findings establish carbon-reinforced nylon as a formidable competitor for use in industries such as aerospace and automotive, where strength and durability are important.

Effect of the Infill Density on 3D-Printed Geometrically Graded Impact Attenuators.

Three-dimensional printing is widely becoming prevalent in various industries, including the automotive sector. As this technology advances, critical structures subjected to impact loads may also be produced using additive manufacturing. A key parameter in this technique is the infill density of the printed geometry, which directly affects mechanical properties such as strength, stiffness, and ductility. Functionally graded layouts present themselves as one of the best techniques to design effective impact attenuators. The present work combines these techniques and parameters to evaluate the behaviour of geometrically graded impact attenuators produced through additive manufacturing, with different infill densities for polylactic acid (PLA) and polycarbonate (PC) materials. The results obtained show an increase in the mechanical strength for both materials and all the infill densities when compared to reference quasi-static results.

Effect of process variables on Ultimaker 2+ 3D FDM printed Tough PLA parts

ABSTRACT Fused Deposition Modeling (FDM) is pivotal in creating functional prototypes and end-use parts, with Tough PLA emerging as a favored material due to its durability. However, fine-tuning printing process variables for Tough PLA on the Ultimaker 2 + 3D printer remains challenging. This study employs Taguchi Grey relational analysis to optimize these process variables. L09 Taguchi’s systematic approach and Taguchi Grey Relational Grade Analysis (TGRGA) investigated Layer Thickness (LT), Infill Density (ID), and Nozzle Temperature (NT) at varying levels for which response variables such as Ultimate Tensile Strength (UTS), Average hardness (AH), and Surface Roughness (Ra) are evaluated. Utilizing Taguchi Grey Relational Grade Analysis (TGRGA), enhancements in ultimate tensile strength from 43.182 N/mm2 to 46.56 N/mm2, average hardness from 64 to 67, and Surface roughness from 8.60 µm to 8.35 µm are achieved. This study contributes to advancing additive manufacturing optimization, offering insights into refining Tough PLA part production on the Ultimaker 2 + 3D printer for bio implants like stent application.

Mechanical properties and crack deflection mechanisms in 3D-Printed porous geopolymers with cellular structures

ABSTRACT This study focuses on using helical design patterns via 3D printing to create geopolymer with a highly porous structure in order to enhance their strength-density relationship and fracture properties. In this regard, to create porous structure, different pitch angles and infill densities were chosen, and mechanical and fracture properties were examined. The results of mechanical strength tests revealed that while the pitch angle does not significantly affect compressive strength, flexural strength is improved by implementing a low pitch angle helical structure, which leads to the strength-density relationship improvement. Additionally, the work of fracture results demonstrated an enhancement for samples with low pitch angles, such as α15° and α30°, compared to cast and non-directional printed samples. The digital image correlation and fracture surface analysis showed several fracture mechanisms, predominantly crack deflection and twisting, in samples with low pitch angles, which contributes to the observed improvements in the work of fracture.

Mechanical and surface characterisation of additively manufactured polyetheretherketone for the tribo test

Purpose The additive manufacturing process, such as fused filament fabrication based on material extrusion, fabricates the samples layer-by-layer. The various parameters in the process significantly affect the dimensions, structure and mechanical properties of the fabricated parts. The purpose of this paper is to investigate the surface and mechanical properties that can affect the contact characteristics with other materials during tribological tests. Design/methodology/approach The investigation of 3D-printed Polyetheretherketone (PEEK) includes the measurement of dimensions, microhardness, surface roughness, surface energy and tensile strength to define material characteristics. The crystallinity is measured using an X-ray diffractometer to understand the hardness behaviour. Findings The printing parameters affect its surface roughness, hardness and crystallinity. This change in parameters such as layer thickness and infill density impacts mechanical properties such as hardness and surface roughness, which will influence the contact mechanism with the counter body during any tribological test. The change in a single parameter during the sample fabrication and the change in the surface and mechanical properties are observed. Research limitations/implications The material cost plays an important role in conducting numerous destructive tests, which is a major limitation to conducting parameter optimisation by varying more parameters. The study is limited to the as-fabricated samples rather than finished samples and without any heat treatment. Achieving optimal parameters is integral to the success of additive manufacturing, ensuring the production of components with consistent performance. Practical implications The study aims at the application of 3D-printed PEEK for bush or journal bearings that can be directly used in practice. The mechanical properties discussed in this paper can fill the gap between theory and practice. Social implications The research provides all fundamental properties, including the printing parameters and their effect on the dimensions and surface structure, which are required to understand the material and its use. The results are consistent as at least four samples were tested for tribological behaviour. The conclusion is updated as per suggestions. Originality/value The study outlines the relationship between the change in layer thickness and infill density with changes in surface energy, surface roughness, hardness and tensile strength. The deformation and adhesion during the friction test depend on these properties.

Optimization of Tensile Strength and Cost-Effectiveness of Polyethylene Terephthalate Glycol in Fused Deposition Modeling Using the Taguchi Method and Analysis of Variance.

This paper investigates the optimization of tensile strength, tensile strength per unit weight, and tensile strength per unit time of polyethylene terephthalate glycol (PETG) material in fused deposition modeling (FDM) technology using the Taguchi method and analysis of variance (ANOVA). Unlike previous studies that typically focused on optimizing a single mechanical property, our research offers a multi-dimensional evaluation by simultaneously optimizing three critical quality characteristics: tensile strength, tensile strength per unit weight, and tensile strength per unit time. This comprehensive approach provides a broader perspective on both the mechanical performance and production efficiency, contributing new insights into the optimization of PETG in FDM. The Taguchi method (L16 45) was designed and executed, with the layer height, infill density, print temperature, print speed, and infill line direction as the control factors. Sixteen tensile tests were conducted, and ANOVA was employed to identify the main influencing factors for each quality characteristic. For the tensile strength, the infill density was found to have the greatest impact (48.45%), while the print temperature had the least impact (0.78%). The optimal parameter combination reduced the quality loss to 31.28% and standard deviation to 55.93%. For tensile strength per unit weight, the infill line direction had the greatest impact (87.22%), whereas the print temperature had the least impact (0.77%). The optimal parameter combination reduced the quality loss to 54.09% and standard deviation to 73.54%. Regarding the tensile strength per unit time, the layer height had the greatest impact (82.12%), while the print temperature had the least impact (0.08%). The optimal parameter combination reduced the quality loss to 10.81% and standard deviation to 32.87%.

Developing lightweight steel profile and lattice polymeric core composite for structural use

Embracing modular construction, advanced materials, and digital technologies can drive innovation in the building industry, address global material consumption challenges, and foster a sustainable future. This paper presents the innovative concept of the lightweight hybrid lattice-filled profile (HLFP) for modular engineering, which combines a thin-walled steel tubular shell and additively manufactured lattice structure (AMLS) as a lightweight core. The AMLS achieves precise shape, internal structure, and stiffness, ensuring the decided structural performance with minimum materials. This study provides a theoretical model of HLFP, focusing on adhesively bonded AMLS. The experimental verification demonstrates that the adhesively bonded AMLS ensures an additional 130 % during the elastic stage and, even after partial debonding, maintains 50 % of the mechanical resistance compared to the theoretical sum of the HLFP components. Reducing the infill density does not severely affect the load-bearing capacity of the HLFP—a fourfold decrease of the ALMS density (from 10 % to 2.5 %) results in a 20 % decrease in the ultimate load. However, the sparse lattice structure alters the failure mechanism of ALMS, changing it from favorable ductile to dangerous brittle and determining the object for further optimization. The parametric study reveals the efficiency of the theoretical model for predicting the load-bearing capacity of HLFP. However, the finite element model developed in this study should be used for a more detailed analysis of the HLFP's structural behavior.

Innovative spiral nerve conduits: Addressing nutrient transport and cellular activity for critical-sized nerve defects

Large-gap nerve defects require nerve guide conduits (NGCs) for complete regeneration and muscle innervation. Many NGCs have been developed using various scaffold designs and tissue engineering strategies to promote axon regeneration. Still, most are tubular with inadequate pore sizes and lack surface cues for nutrient transport, cell attachment, and tissue infiltration. This study developed a porous spiral NGC to address these issues using a 3D-printed thermoplastic polyurethane (TPU) fiber lattice. The lattice was functionalized with poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) electrospun aligned (aPHBV) and randomly (rPHBV) oriented nanofibers to enhance cellular activity. TPU lattices were made with 25 %, 35 %, and 50 % infill densities to create scaffolds with varied mechanical compliance. The fabricated TPU/PHBV spiral conduits had significantly higher surface areas (25 % TPU/PHBV: 698.97 mm2, 35 % TPU/PHBV: 500.06 mm2, 50 % TPU/PHBV: 327.61 mm2) compared to commercially available nerve conduits like Neurolac™ (205.26 mm2). Aligned PHBV nanofibers showed excellent Schwann cell (RSC96) adhesion, proliferation, and neurogenic gene expression for all infill densities. Spiral TPU/PHBV conduits with 25 % and 35 % infill densities exhibited Young's modulus values comparable to Neurotube® and ultimate tensile strength like acellular cadaveric human nerves. A 10 mm sciatic nerve defect in Wistar rats treated with TPU/aPHBV NGCs demonstrated muscle innervation and axon healing comparable to autografts over 4 months, as evaluated by gait analysis, functional recovery, and histology. The TPU/PHBV NGC developed in this study shows promise as a treatment for large-gap nerve defects.

Correlating FDM printing parameters with mechanical properties and surface quality of PLA printouts

Abstract This study explores the correlation between four critical Fused Deposition Modeling (FDM) parameters—extrusion temperature, layer height, print speed, and infill density—and the mechanical properties and surface quality of PLA (Polylactic Acid) printouts. The mechanical properties, including Young’s modulus, tensile strength, and bending strength, were evaluated alongside surface roughness and dimensional accuracy. The results indicate that extrusion temperatures between 200°C and 220°C optimize mechanical performance, enhancing tensile strength and bending strength, while smaller layer heights (0.1 mm) improve surface smoothness but increase print time. Moderate print speeds (around 60 mm/s) offer the best balance between strength and efficiency, while higher infill densities (above 80%) enhance mechanical properties, increasing both tensile and bending strength by up to 25%. These findings provide key insights into optimizing FDM printing parameters to achieve improved structural integrity and aesthetic quality in PLA prints.

Integrating machine learning for predicting biomechanical properties of layered manufactured bone implants

AbstractThe layered manufacturing (LM) based locking bone plates (LBPs) are highly favored for biomedical applications due to its implant customization flexibility, control over porosity, and functional parameters. Design of experiments mainly relies on predefined experimental run orders; however, machine learning (ML) can handle complex and nonlinear relationships for predicting output responses. This research investigates the application of various ML models for predicting the impact strength, torque values, and punch shear strength of poly lactic acid (PLA) based LBPs. A dataset of 100 data points for each response variable was developed, analyzing the influence of printing parameters, like infill density (ID), layer height (LH), wall thickness (WT), and print speed (PS). The ID, LH, WT, and PS were varied within the ranges of 20%–100%, 0.1–0.5 mm, 0.4–1.2 mm, and 20–100 mm/s, respectively. Among the ML models evaluated, XGBoost and Adaboost exhibited strong alignment of the predicted values with actual values. The decision tree regression, showed the lowest predictive accuracy due to its tendency to overfit and lack of iterative refinement. The findings suggest that ML models can effectively predict the mechanical properties of PLA‐based LBPs, offering valuable insights for optimizing printing parameters to enhance the performance of orthopedic implants. The findings can guide biomedical engineers in making data‐driven decisions to enhance the strength of LBPs, thereby improving patient outcomes in orthopedic treatments.Highlights Predicted impact strength, torque, and shear strength of biomedical specimens. Evaluated 100 data points per variable to assess printing parameters' influence. XGBoost and Adaboost showed superior accuracy, with R2 consistently above 0.9. Decision Tree regression exhibited the lowest accuracy due to overfitting issues. Aims to guide biomedical engineers in data‐driven decisions for better patient outcomes.

Extrusion-Based Three-Dimensional Printing of Metronidazole Immediate Release Tablets: Impact of Processing Parameters and in Vitro Evaluation

PurposeThe current study assessed the potential of a pneumatic 3D printer in developing a taste-masked tablet in a single step. Metronidazole (MTZ) was chosen as the model drug, and Eudragit® E PO was used as a taste-masking polymer to produce taste-masked tablets.MethodsThe study focused on optimizing processing parameters, such as the nozzle's printing speed, the printhead's heating temperature, and the pressure. Oval-shaped tablets were printed with a rectilinear printing pattern of 30% and 100% infill and evaluated for in vitro drug release and taste masking. The 3D-printed tablets are also characterized using Differential Scanning Calorimetry (DSC), Fourier-transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy (SEM).ResultsThe infill density impacts the drug release profile of the tablets. F9, F10, and F11 displayed desired printability among the formulations, with F9 and F10 exhibiting over 85% drug release within 60 min in the in vitro dissolution study. The F9 formulation, with 30% infill, effectively masked the bitter taste of MTZ in the in vitro dissolution study carried out in a pH 6.8 artificial salivary medium. The observed release was below the tasting threshold concentration of the model drug.ConclusionIn summary, 3-dimensional extrusion-based printing combines the effects of hot-melt extrusion and fused deposition modeling techniques in a single-step process, demonstrating potential as an alternative to the fused-deposition model 3D printing technique and warranting further exploration.Graphical

Impact of printing parameters on the dynamic outputs of a slider-crank mechanism with FFF-based 3D-printed crank-arms

In this study, the crank-arm of the slider-crank mechanism was produced with different raster angles (45°, 90°, 135°) and infill densities (25%, 50%, 75%, 100%). The effect of these parameters on the dynamics of the slider was investigated experimentally and numerically, and compared with a rigid version of the crank-arm. Firstly, analytical, numerical, and experimental results are obtained for the rigid crank-arm, and the results are compared. Secondly, experiments were carried out on the same experimental setup with 12 crank-arm specimens produced using PLA. Finally, experimental results of sliders were statistically analysed with rigid-body mechanism results, and the flexibility of the crank-arms produced with fused filament fabrication was verified through numerical simulations. As the infill density decreased, the flexibility of the crank-arm increased, and the deviations in the results also grew as the energy change due to the deformation increased. The raster angle had no significant effect on the results except for 25% infill density. However, with 25% infill density, the crank-arm with 90° raster angle followed the rigid crank-arm experimental results best. As a result, it has been observed that the crank-arm produced with different printing parameters has a significant effect on the dynamics of the slider.

PETG as an Alternative Material for the Production of Drone Spare Parts.

Material selection is the main challenge in the drone industry. In this study, hardness, abrasive wear, impact resistance, tensile strength, and durability (frost resistance and accelerated ageing) were identified as important characteristics of drone materials. The additive manufacturing technology was used to produce the drone leg specimens and prototype. The suitability of PETG as a primary filament material in the design of the drone leg was investigated. Nine series were printed with different raster lines (0.1, 0.2 and 0.3 mm) and infill densities (30, 60 and 90%). Printed specimens were annealed in salt and alabaster, as well as immersed in liquid nitrogen. Series with raster line-infill densities of 0.1-30, 0.3-30, 0.1-90 and 0.3-90 were identified as the most interesting ones. Thermally treated specimens had better mechanical and durability properties, and infill density was found to be the most important printing parameter. Specimen annealed in salt with a raster line of 0.1 mm and infill density of 90% had the best results. Since ABS is the most common material used for drone leg production, its properties were compared with the PETG specimen, which showed the best properties. The potential of PETG as an alternative material was proven, while the flexibility, productivity and suitability of the leg drone design were additionally confirmed.

Optimizing Tilapia-based surimi ink for 3D printing: Enhancing physicochemical properties and printability with Ulva powder

The elderly face malnutrition and dysphagia. 3D printing with high-protein surimi offers an innovative way to customize nutrition and texture of foods for the elderly. This study explored whether tilapia-based surimi ink (TBSI) with Ulva powder (UP, 0–3 %) could improve physicochemical properties and printability as an alternative to traditional pollock-based surimi ink (PBSI). TBSI showed a more uniform microstructure, greater water-holding capacity (WHC), and better printability with consistent extrusion than PBSI. Adding UP to TBSI promoted cross-linking and enhanced microstructure and WHC. Rheological analysis revealed that all inks exhibited shear-thinning behavior. UP increased complex viscosity, storage modulus, and loss modulus. Notably, UP above 2 % improved protein matrix uniformity, structural integrity, and printability, as confirmed by FT-IR and 3D printing tests. The hardness of steamed TBSI fish cake increased when infill density increased. This study highlights the potential of TBSI with UP for 3D printing to prepare personalized and elderly-friendly food.