Infill Density Research Articles

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.

Analyzing the effects of printing parameters to minimize the dimensional deviation of polylactic acid parts by applying three different decision-making approaches.

This article examines the influence of various factors on the precision of 3D printed objects produced through Fused Filament Fabrication (FFF) using Polylactic Acid (PLA) as the primary material. While PLA is widely chosen for its compatibility with biological applications, it does suffer from limited dimensional accuracy. The study focuses on investigating the effects of four independent parameters, namely layer height, infill density, printing speed, and the number of top and bottom layers, on accuracy along the three axes of length, width, and depth. The research objective is to identify the optimal levels of these parameters that minimize dimensional errors across all axes. However, due to conflicting requirements among different dimensions, determining a comprehensive decision-making methodology presents a significant challenge. To address this issue, three distinct approaches are proposed, each offering a unique perspective and practical application. Interestingly, the outcomes of these approaches converge on a single solution. Among these parameters, printing speed emerges as the dominant factor, while, the number of layers is the least influential. Moreover, consistent shrinkage is observed in the length and width dimensions, with greater errors evident in longer dimensions. Overall, a preference for lower layer height and infill density, along with higher printing speed and increased top and bottom layers, is recommended. The study findings indicate that the most effective parameter selection for reducing errors in all dimensions involves a layer height of 0.2mm, infill density of 60%, printing speed of 50mm/s, and the use of four top and bottom layers.

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%.

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.

Effect of Material Extrusion Process Parameters to Enhance Water Vapour Adsorption Capacity of PLA/Wood Composite Printed Parts

This study aims to optimise the water vapour adsorption capacity of polylactic acid (PLA) and wood composite materials for application in dehumidification systems through material extrusion additive manufacturing. By analysing key process parameters, including nozzle diameter, layer height, and temperature, the research evaluates their impact on the porosity and adsorption performance of the composite. Additionally, the influence of different infill densities on moisture absorption is investigated. The results show that increasing wood content significantly enhances water vapour adsorption, with nozzle diameter and layer height identified as the most critical factors. These findings confirm that composite materials, especially those with higher wood content and optimised printing parameters, offer promising solutions for improving dehumidification efficiency. Potential applications include heating, ventilation, and air conditioning systems or environmental control. This work introduces an innovative approach to using composite materials in desiccant-based dehumidification and provides a solid foundation for future research. Further studies could focus on optimising material formulations and scaling this approach for broader industrial applications.

The effective elastic thickness along the Emperor Seamount Chain and its tectonic implications

Summary The Hawaiian-Emperor Seamount Chain, a pre-eminent example of a hotspot-generated intraplate seamount chain, provides key constraints not only on the kinematics of plates but also on their rigidity. Previous studies have shown that the effective elastic thickness, Te, a proxy for the long-term strength of the lithosphere, changes abruptly at the Hawaiian-Emperor ‘bend’ from low values (∼16 km) at the Emperor Seamounts to high values (∼27 km) at the Hawaiian Ridge. To better constrain Te along the poorly explored Emperor Seamounts we have used a free-air gravity anomaly and bathymetry gridded data set, together with fully 3-dimensional elastic plate (flexure) models, to estimate the continuity of Te and volcano load and infill densities along 1000 profiles spaced 2 km apart of the chain. Results show that Te generally decreases northward along the chain. The decrease is most systematic between Ojin and Jimmu guyots where Te depends on the age of the lithosphere at the time of volcano loading and is controlled by the 340°C and 400°C oceanic isotherms. The largest variation from these isotherms occurs at the northern and southern ends of the chain where Te is smaller than expected suggesting the influence of pre-existing, older, loads. We use these results to constrain the subsidence, flexural tilt, rheological properties, and tectonic setting along the seamount chain. We found an excess subsidence in the range 1.2-2.4 km, a tilt as large as 2-3°, oceanic lithosphere that is weaker than it is seaward of the weak zone at subduction zones, and a tectonic setting at Detroit and Koko seamounts that, despite their forming an integral part of the hotspot generated seamount chain, retains a memory of their proximity to earlier loads associated with plume influenced mid-oceanic ridges.

Compressive behavior of additively manufactured lightweight structures: Infill density optimization based on energy absorption diagrams

The use of 3D-printed components as load-bearing structures is widely studied, while their use as energy absorbers constitutes a gap in the additive manufacturing (AM) field. Most of the reported works address the compressive behavior of AM parts up to low strains (<15%), thus omitting many important properties. Therefore, this paper presents the compression characterization of Polylactic Acid (PLA) samples with different infill densities-IDs (10–100% range, with a step of 10%) fabricated by material extrusion (MEX) AM process. The physical (dimensional accuracy, printing time and sample mass) and mechanical (elastic, strength, strain and energy absorption) properties are determined and discussed in detail, along with the failure mechanisms that occur in the samples. Moreover, an ID optimization is performed based on the energy absorption diagrams (EAD), a unique approach in the AM field. The highest values of compressive strength (81 MPa) and modulus (1306.6 MPa) are found for 90%-ID, over 2.2% higher than those obtained for 100%-ID. On the other hand, based on three different approaches, EAD identified 30%-ID as optimal. The 30%-ID samples absorb the largest amount of energy (12 MJ/m3) at the lowest (ideal) peak stress value (23.57 MPa), which is 69.1% lower than that for 100%-ID. At low IDs (<30%), the samples exhibit a brittle behavior, changing to a ductile one with the increase of ID (≥40%). The MEX-printed PLA samples show a dimensional relative error below 0.15%, and the optimization process reduces the amount of filament material by 54.3% and the printing time by 42.7%.

Drilling parameter optimisation for three-dimensional prints of acrylonitrile butadiene styrene

Abstract Over the past decade, additive manufacturing has transformed the industry, leading to a range of innovative products. In this study, the acrylonitrile butadiene styrene specimen was produced using the fused deposition modeling process. To assess the effectiveness of additive manufacturing parts in final product development, it’s crucial to establish the optimal drilling process parameters to minimize thrust force and torque. The investigation utilized two different drill geometries. Drilling with an end mill resulted in a 24.22% reduction in thrust force and a 12.37% decrease in torque compared to using a twist drill. Additionally, factors such as orientation, infill density, feed rate, and drill geometry have a significant impact on drilling forces.

Characterization of PLA/LW-PLA Composite Materials Manufactured by Dual-Nozzle FDM 3D-Printing Processes.

This study investigates the properties of 3D-printed composite structures made from polylactic acid (PLA) and lightweight-polylactic acid (LW-PLA) filaments using dual-nozzle fused-deposition modeling (FDM) 3D printing. Composite structures were modeled by creating three types of cubes: (i) ST4-built with a total of four alternating layers of the two filaments in the z-axis, (ii) ST8-eight alternating layers of the two filaments, and (iii) CH4-a checkered pattern with four alternating divisions along the x, y, and z axes. Each composite structure was analyzed for printing time and weight, morphology, and compressive properties under varying nozzle temperatures and infill densities. Results indicated that higher nozzle temperatures (230 °C and 240 °C) activate foaming, particularly in ST4 and ST8 at 100% infill density. These structures were 103.5% larger on one side than the modeled dimensions and up to 9.25% lighter. The 100% infill density of ST4-Com-PLA/LW-PLA-240 improved toughness by 246.5% due to better pore compression. The ST4 and ST8 cubes exhibited decreased stiffness with increasing temperatures, while CH4 maintained consistent compressive properties across different conditions. This study confirmed that the characteristics of LW-PLA become more pronounced as the material is printed continuously, with ST4 showing the strongest effect, followed by ST8 and CH4. It highlights the importance of adjusting nozzle temperature and infill density to control foaming, density, and mechanical properties. Overall optimal conditions are 230 °C and 50% infill density, which provide a balance of strength and toughness for applications.

Upcycling end-of-life carbon fiber in high-performance CFRP composites by the material extrusion additive manufacturing process

Each year, a significant amount of waste is produced from carbon fiber polymer composites at the end of its lifecycle due to extensive use across various applications. Utilizing regenerative carbon fiber as a feedstock material offers a promising and sustainable approach to additive manufacturing based on materials. This study proposes the additive manufacturing of recycled carbon fiber with a polyamide-12 polymer composite. Filaments of recycled carbon fiber-reinforced polyamide-12 (rCF-PA12) with different recycled carbon fiber contents (0%, 10%, and 15% by weight) in the polyamide-12 matrix are developed. These filaments are utilized for 3D printing of specimens by using various infill density parameters (80% and 100%) on a fused deposition modeling 3D printer. The study examined how the fiber content and infill densities influenced the flexural performance of the printed specimens. Notably, the part containing 15 wt% recycled carbon fiber (rCF) composites showed a significant improvement in flexural performance due to enhanced interface bonding and effective fiber alignment. The results indicated that reinforcing the printed part with 10% and 15 wt% recycled carbon fiber (rCF) improved the flexural properties by 49.86% and 91.75%, respectively, compared to the unreinforced printed part under the same infill density and printing parameters. The investigation demonstrates that the additive manufacturing-based technique presents a potential approach to use carbon fiber-reinforced polymers waste and manufacture high-performance engineering, economic, and environmentally friendly industrial applications with the complicated design using different polymer matrices.

Robust design optimization of Critical Quality Indicators (CQIs) of medical-graded polycaprolactone (PCL) in bioplotting

Polycaprolactone (PCL), either in its pure grade or as a polymeric matrix for bio-composites, plays a key role in the biomedical and bioengineering industries. It is also considered a multifunctional and versatile polymer for bioprinting and bioplotting purposes, especially in tissue engineering. Herein, an undiscovered yet valuable aspect of PCL extrusion-based bioprinting, such as the predictability of Critical Quality Indicators (CQIs), is investigated in depth. With the aid of the robust L25 orthogonal matrix design, the six most generic and device-independent control factors proved their impact on quality metrics such as global porosity, dimensional conformity, and surface roughness, determined with the aid of highly evolved Nondestructive Testing (NDT) and algorithms. To this end, 25 experimental runs were set, and 125 specimens were fabricated using an industrial-scale bio-plotter and medical-graded polycaprolactone. Various infill densities (ID), layer thicknesses (LT), raster deposition angles (RDA), printing speeds (PS), nozzle temperatures (NT), and bed temperatures (BT) were applied. CQIs were determined using optical profilometry and microscopy, and micro-computed tomography. Quadratic predictive equations were compiled and verified using two additional, well-chosen experimental runs. These generally applicable predictive models carry a massive amount of research and industrial merit, as they ensure visibility in bioprinting with PCL.

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.

Analysis of Impact Attenuation in 3D Printed Hip Protectors: A Support Vector Regression Approach

This study examined the impact attenuation of 3D printed hip protectors using thermoplastic polyurethanes with different shore hardness values for preventing osteoporotic hip fractures. Rigorous testing at various energy levels were carried out to determine the protector’s abilities to attenuate impact. Subsequently, the prediction of impact attenuation capacity based on key design parameters was achieved from developed Support Vector Regression (SVR) model generated from the data of the impact attenuation capabilities. The key design parameters were shell thickness, infill density and shore hardness. The results demonstrated a significant correlation between the impact attenuation ability and the infill density of the hip protectors with R2 of 91% for the training set and 99% for the test set. The generated RMSE values are 0.0012 and 0.0208, respectively. Remarkably, the SVR model exhibited excellent agreement with the experimental test results, affirming the efficacy of SVR in the design of hip protectors to enhance protective performance and cut the cost of experimentation.