Optimizing 3D printing parameters for enhanced compression behavior in chiral-core PLA sandwich structures

The integrated of bio-based and sustainable composite materials had advanced the additive manufacturing (AM) industry, particularly for fused deposition modelling (FDM). Natural fibre-reinforced composites are gaining prominence due to their eco-friendly properties and compatibility with thermoplastics. This study investigates the influence of infill density and layer thickness on the mechanical properties of a novel pineapple leaf fibre (PALF)reinforced poly-lactic acid (PLA) composite filament used for 3D printing. The composite filament was fabricated through a structured process involving fibre crushing, sieving, mixing with PLA matrix and extrusion. To study the effects of infill density and layer thickness, a series of tensile and flexural test specimens were fabricated in accordance with ASTM D638 and D790 standards, respectively. A design of experiments (DoE) approach, specifically the Taguchi method, was employed to systematically evaluate the influence of layer thickness (0.1 mm, 0.2 mm, 0.3 mm), printing speed (25 mm/s, 50 mm/s, 100 mm/s) and infill density (25%, 50%, 100%), on the mechanical performance. The results revealed a significant correlation between the chosen FDM parameters and the mechanical properties of the PALF/PLA composite. Higher infill density generally contributed to improved tensile and flexural strength due to increased internal material support and reduced void formation. Conversely, lower infill densities, while reducing material consumption and printing time, exhibited reduced mechanical strength. Layer thickness also demonstrated the least influence on the mechanical properties. However, increased layer thickness reduced build time and material overlap. The interaction between infill density and tensile performance is also confirmed in this study with the score of r꞊0.9799 and r꞊0.9806. Negative effect between the printing speed and all mechanical properties with the range values between r꞊-0.0569 and r꞊-0.3608. The study concludes that optimizing these parameters is essential to balance mechanical strength, material efficiency, and printing time. This research contributes to the growing body of knowledge on sustainable 3D printing materials and provides practical insights for optimizing process parameters when using natural fibre composites. It highlights the potential of pineapple leaf fibre as a valuable reinforcement in biodegradable thermoplastics, promoting a circular economy and sustainable manufacturing practices.

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.

A rapid emerging additive manufacturing technology for various engineering applications is fused deposition modelling (FDM). Several parameters affect the mechanical qualities of 3D printed materials using FDM technology. According to the literature, the density of infill, Infill Pattern and Print Speed, are the factors that directly affect the Tensile Strength of 3D printed materials. The effects of infill pattern and density and Print speed on tensile properties, and material used in 3D printing will all be examined and discussed in this article. There are a total of 16 different forms of infill pattern, and out of these 6 different types of infill pattern with varying infill densities from 20% to 100% and constant print speed of 80mm/min will be evaluated. To minimize the impact of other factors on the mechanical properties of the material, each specimen would be 3D printed using ABS material using the same color and 3D printing parameters, as well as in the same position on the printer bed. The results will provide us with a clearer idea of how to print objects in 3D as quickly as possible while still maintaining the necessary tensile qualities.

This research aims to optimize polylactic acid (PLA) materials with varying process parameter levels using the Taguchi method, compare tensile strengths, generate stress-strain curves, and achieve high-strength structures efficiently in a shorter production time while minimizing material use via fused deposition modeling (FDM). For this purpose, three factors were considered, and experiments were carried out using the Taguchi L9 orthogonal array. At the first stage, relationships between the measured tensile strength, the filament used, the production time, and the input factors were analyzed. The results revealed that tensile strength is predominantly influenced by wall line count (WLC), with a contribution of 56.2 %, followed by infill density (ID) at 33.5 % and print speed (PS) at 8.5 %. Conversely, ID emerges as the principal factor in material consumption, accounting for 95.7 % of the contribution margin. Similarly, printing time was largely determined by PS (71.5 %), followed by ID (27.7 %), indicating that significant reductions in production time can be achieved through PS optimization. At the second stage, a multi-criteria optimization and the VIKOR compromise solution, a multi-criteria decision-making (MCDM) method, were applied, with the trials as decision alternatives and the responses as criteria. As a result, the optimal combination was found to be WLC 6, ID 50 %, and PS 40 mm/s. Remarkably, the MCDM methodology has yet to be applied to Additive Manufacturing processes, with criteria importance determined through intercriteria correlation (CRITIC) approaches. This establishes a novel research pathway for multi-criteria optimization in 3D printing using PLA materials by addressing this gap through a unique optimization methodology.

This study investigates the correlation among the impact strength of Polylactic acid (PLA) material as well as many 3D printing parameters, including layer height, infill density, extrusion temperature, and print speed, using Fused Deposition Modelling (FDM) in Additive Manufacturing (AM). By using well-planned trials, the ASTM D256 standard assessed the impact strength of samples. Impact strength was optimized using six distinct techniques: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Teaching Learning Based Optimization (TLBO), and Cohort Intelligence (CI). These approaches are reliable since they consistently delivered similar impact strength values after several iterations. The best algorithms, according to the study, were TLBO and JAYA, which produced a maximum impact strength of 4.08 kJ/m2. The algorithms’ effectiveness was validated by validation studies, which showed little error and near matches between the expected and actual impact strength values. The advantages of employing these methods to increase the impact strength of PLA material for 3D printing are illustrated in the present research, which provides helpful insights on how to improve FDM procedures.

The mechanical properties such as tensile behavior of a 3D printed object can be influenced by various printing parameters, including printing temperature, orientation, infill density, and printing speed. This study focuses on investigating the effects of infill density and printing speed. Thirty dog-bone specimens were 3D printed using Fused Deposition Modelling (FDM) technique with Polylactic Acid (PLA) filament. Three different infill density settings (40%, 60%, and 80%) and three printing speed settings (30 mm/s, 60 mm/s, and 90 mm/s) were used. Tensile tests were performed on each specimen using a Universal Testing Machine. The experimental results indicate a clear trend of tensile behaviour with infill density. Increasing the infill density leads to improved tensile behaviour in the specimen. The highest Young’s Modulus and ultimate tensile strength (UTS) were achieved at 541.67 MPa and 24.3 MPa, respectively, with an infill density of 80%. On the other hand, printing speed showed an inverse relationship with tensile behaviour. As the printing speed increased, the Young’s Modulus and UTS decreased. However, the effect of printing speed on the mechanical properties was not as significant as that of infill density. When increasing the printing speed from 30 mm/s to 90 mm/s, the UTS only decreased by 5.61%. In contrast, increasing the infill density from 40% to 80% resulted in a UTS increase of 35.23%.

This research employs the Taguchi method and analysis of variance (ANOVA) to investigate, analyze, and optimize the impact strength of tough polylactic acid (PLA) material produced through fused deposition modeling (FDM). This study explores the effect of key printing parameters-specifically, infill density, raster angle, layer height, and print speed-on Charpy impact strength. Utilizing a Taguchi L16 orthogonal array experimental design, the parameters are varied within defined ranges. The results, analyzed through signal-to-noise (S/N) ratios and ANOVA, reveal that infill density has the most substantial impact on Charpy impact strength, followed by print speed, layer height, and raster angle. ANOVA identifies infill density and print speed as the most influential factors, contributing 38.93% and 36.51%, respectively. A regression model was formulated and this model predicted the impact strength with high accuracy (R2 = 98.16%). The optimized parameter set obtained through the Taguchi method, namely, a 100% infill density, 45/-45° raster angle, 0.25 mm layer height, and 75 mm/s print speed, enhances the impact strength by 1.39% compared to the experimental design, resulting in an impact strength of 38.54 kJ/m2. Validation experiments confirmed the effectiveness of the optimized parameters.

Nowadays, Fused Filament Fabrication (FFF) 3D printing offers promising opportunities for the customized manufacturing of ankle–foot orthoses (AFOs) targeted towards rehabilitation purposes. Polypropylene (PP) represents an ideal candidate in orthotic applications due to its light weight and superior mechanical properties, offering an excellent balance between flexibility, chemical resistance, biocompatibility, and long-term durability. However, Additive Manufacturing (AM) of AFOs based on PP remains a major challenge due to its limited bed adhesion and high shrinkage, especially for making large parts such as AFOs. The primary innovation of the present study lies in the optimization of FFF 3D printing parameters for the fabrication of functional, patient-specific orthoses using PP, a material still underutilized in the AM of medical devices. Firstly, a thorough thermomechanical characterization was conducted, allowing the implementation of a (thermo-)elastic material model for the used PP filament. Thereafter, a Taguchi design of experiments (DOE) was established to study the influence of several printing parameters (extrusion temperature, printing speed, layer thickness, infill density, infill pattern, and part orientation) on the mechanical properties of 3D-printed specimens. Three-point bending tests were conducted to evaluate the strength and stiffness of the samples, while additional tensile tests were performed on the 3D-printed orthoses using a home-made innovative device to validate the optimal configurations. The results showed that the maximum flexural modulus of 3D-printed specimens was achieved when the printing speed was around 50 mm/s. The most significant parameter for mechanical performance and reduction in printing time was shown to be infill density, contributing 73.2% to maximum stress and 75.2% to Interlaminar Shear Strength (ILSS). Finally, the applicability of the finite element method (FEM) to simulate the FFF process-induced deflections, part distortion (warpage), and residual stresses in 3D-printed orthoses was investigated using a numerical simulation tool (Digimat-AM®). The combination of Taguchi DOE with Digimat-AM for polypropylene AFOs highlighted that the 90° orientation appeared to be the most suitable configuration, as it minimizes deformation and von Mises stress, ensuring improved quality and robustness of the printed orthoses. The findings from this study contribute by providing a reliable method for printing PP parts with improved mechanical performance, thereby opening new opportunities for its use in medical-grade additive manufacturing.

This study utilizes the Taguchi optimization technique to investigate the effects of FDM processing parameters on the Charpy impact strength of 3D printed CF/PA composites experimentally and statistically. The four 3D printing parameters employed in the experiment are the infill density, raster angle, extruder temperature, and printing speed, which were used to create the experimental plan with the L18 orthogonal array. Signal to noise (S/N) ratios and analysis of variance (ANOVA) were utilized to identify the optimum values and the interactions between the process parameters. SEM and thermography techniques were employed to assess the microstructural and damage status of the CF/PA composite specimens. ANOVA results determined that only three factors–infill density, raster angle, and extruder temperature–had a statistical significance, while printing speed did not. The outcomes demonstrated that the optimal 3D printing parameters are infill density (100%), raster angle (60°), extruder temperature (260°C), infill density (100%), and printing speed (30 mm/s), with the maximum contribution of 54.19% belonging to infill density, and the minimum contribution of 2.84% belonging to printing speed. The optimal combination of these 3D printing parameters yielded a Charpy impact strength of 10.54 kJ/m2, resulting in an increase of almost 150% compared to the worst‐case situation. The Taguchi approach proves to be a proficient technique to boost the Charpy impact strength of 3D‐printed CF/PA composites.

Additive manufacturing (AM) has revolutionized the manufacturing sector, particularly with the advent of 3D printing technology, which allows for the creation of customized, cost-effective, and waste-free products. However, concerns about the strength and reliability of 3D-printed products persist. This study focuses on the impact of three crucial variables—infill density, printing speed, and infill pattern—on the strength of PLA+ 3D-printed products. Our goal is to optimize these parameters to enhance product strength without compromising efficiency. We employed Charpy impact testing and Response Surface Methodology (RSM) to analyze the effects of these variables in combination. Charpy impact testing provides a measure of material toughness, while RSM allows for the optimization of multiple interacting factors. Our experimental design included varying the infill density from low to high values, adjusting printing speeds from 70mm/s to 100mm/s, and using different infill patterns such as cubic and others. Our results show that increasing infill density significantly boosts product strength but also requires more material and longer processing times. Notably, we found that when the infill density exceeds 50%, the printing speed can be increased to 100mm/s without a notable reduction in strength, offering a balance between durability and production efficiency. Additionally, specific infill patterns like cubic provided better strength outcomes compared to others. These findings provide valuable insights for developing stronger and more efficient 3D-printed products using PLA+ materials. By optimizing these parameters, manufacturers can produce high-strength items more efficiently, thereby advancing the capabilities and applications of 3D printing technology in various industries.

Additive manufacturing (AM) or 3D printing technology creates a tangible object by adding successive layers of materials. Nowadays, 3D printing is used for developing both metal and non-metal products. In the advancement of 3D printing technology, material specimen design, modification, and testing become very simple, especially for non-metal materials, such as hyperelastic, thermoplastic, or rubber-like materials. However, proper material modeling and validation are required for the analysis of these types of materials. In this study, 3D printed poly lactic acid (PLA+) material behavior is analyzed numerically for validation in the counterpart of experimental analysis to evaluate their behavior in both cases. The specimen was designed in SolidWorks by following ASTM D638 dimension standards with proper infill densities and raster angle or infill orientation angle. These infill layer densities and angles of orientation play an important role in the mechanical behavior of the specimen. This paper aims to present a numerical validation of five infill densities (20%, 40%, 60%, 80%, and 100%) for a ±45-degree infill angle orientation by incorporating a nonlinear hyperelastic model. Results indicate that infill densities affect the mechanical behavior of PLA+ material. The result also suggested that neo-Hookean and Mooney–Rivlin are the best-fitted hyperelastic material models for these five separate linear infill densities. However, neo-Hookean is easier to analyze, as it has only one parameter and a new equation is developed in this study for determining the parameter for different infill densities.

Additive manufacturing such as 3D printing is considered as a highly convenient manufacturing process since it enables to create any 3D objects. It is known that different materials, printing techniques, and printing parameters are affecting the mechanical properties of the printed objects. However, studies on the mechanical properties of the 3D printed structure are still limited. In this work, investigation of the relationship between two printing parameters, i.e. infill pattern and infill density were conducted on the Polylactic Acid (PLA) material. Three infill densities, 25%, 50%, and 75%, and three infill patterns, grid, tri-hexagon, and concentric, were chosen. The tensile test, ASTM D638, was employed to obtain the material properties based on these two printing parameters. An open-source 3D printing slicer software, Cura, was used to manufacture the tensile specimens. The Young’s modulus, yield strength, and ultimate strength were recorded and examined. The results showed that the tensile properties increase as infill density increases. Of the three-printing pattern, the concentric has the highest values of tensile properties regardless of the infill densities. This finding can be used as a reference for creating a finite element model (FEM) as well as predicting the optimum tensile properties with respect to the printing parameters.

Process sustainability vs. mechanical strength is a strong market-driven claim in Material Extrusion (MEX) Additive Manufacturing (AM). Especially for the most popular polymer, Polylactic Acid (PLA), the concurrent achievement of these opposing goals may become a puzzle, especially since MEX 3D-printing offers a variety of process parameters. Herein, multi-objective optimization of material deployment, 3D printing flexural response, and energy consumption in MEX AM with PLA is introduced. To evaluate the impact of the most important generic and device-independent control parameters on these responses, the Robust Design theory was employed. Raster Deposition Angle (RDA), Layer Thickness (LT), Infill Density (ID), Nozzle Temperature (NT), Bed Temperature (BT), and Printing Speed (PS) were selected to compile a five-level orthogonal array. A total of 25 experimental runs with five specimen replicas each accumulated 135 experiments. Analysis of variances and reduced quadratic regression models (RQRM) were used to decompose the impact of each parameter on the responses. The ID, RDA, and LT were ranked first in impact on printing time, material weight, flexural strength, and energy consumption, respectively. The RQRM predictive models were experimentally validated and hold significant technological merit, for the proper adjustment of process control parameters per the MEX 3D-printing case.

Energy consumption versus strength in MEΧ 3D printing of polylactic acid

Manufacturing industry has been evolving during the last few centuries. Industry 1.0 started with mechanization and the use of steam power. Mass production using production lines and assembly lines dominated Industry 2.0 era. Industry 3.0 era brought automation, flexibility and product diversity and Flexible Manufacturing Systems (FMS) and cellular systems were extensively used. Recently, there is a shift towards the fourth industrial revolution (Industry 4.0). Industry 4.0 includes the combination of technologies working together to fulfill a manufacturing task. Industry 4.0 utilizes internet of things (IIoT), big data, cloud computing, cybersecurity, autonomous robotics, augmented reality, and additive manufacturing (AM). The purpose of Industry 4.0 is to integrate the entire network to function as one system. In this study, we are focusing on scheduling 3D printing machines, namely Markforged Mark Two printers. Process parameters that can be considered in these printers are layer height, infill density, print speed, build orientation, infill patterns, and print temperature. These machines are Fused Filament Fabrication (FFF) 3D printers. The parameters considered in this study are infill density and layer height. Infill density dictates the amount of material that is filled on the inside of an object while it prints. Infill density has a role in a part’s strength and weight. Generally speaking, the greater the infill density, the stronger and heavier an object will be. Lower infill densities on a part suggest that the object’s intentions are purely visual with higher infill densities meant for functional parts. Markforged Mark Two allows infill density for rectangular infill to be from 0–92%. On the other hand, layer height determines the amount of material that is extruded through the nozzle during each pass. Markforged Mark Two allows for three different layer heights to be examined, 100, 125 and 200 mm. Layer height plays a large role in print time as the amount of material extruded effects the completion rate of the object. Layer height’s impact can also be seen by a part’s fineness or detail. This is represented visually on the object by being able to see each pass of the plastic material. For example, an object with a larger layer height will look rougher and not as smooth as an object with a lower layer height. However, it is well known that a lower layer height increases print time whereas a larger layer height implies a faster print time. Several parts with different geometries and also sizes are included in the study. The scheduling performance measure considered is makespan. The objective of the study is to find the optimal parameter settings for multiple jobs such that makespan is minimized subject to minimum restrictions on print parameters for various jobs. A mathematical model is presented to minimize makespan first. Once the optimal makespan is found, the model is re-run such that better quality parameter settings are determined while keeping the optimal makespan unchanged. Later, the results of the experimentation with various parts are discussed and future work is recommended.Keywords3D PrintingSchedulingMakespan