Fused Filament Fabrication Parts Research Articles

Uncertainty Quantification of Process- Property-Structure Linkage for Fused Filament Fabrication Parts

Uncertainty Quantification of Process- Property-Structure Linkage for Fused Filament Fabrication Parts

Additive manufacturing and microstructure effects on thermal and mechanical properties of ply-hybrid carbon and glass fiber composites

The fiber hybridization in high-strength composites is one of the most researched strategies to enhance their limited toughness. In this work, hybrid composites at laminate level by stacking together plies of carbon and glass fiber were prepared using fused filament fabrication (FFF) technique. The large void content and the poor adhesion between layers attributed to this technology are overcome by the addition of an optimized thermo-pressurized treatment. The analysis of post-processing temperature effects on the microstructural, thermal and interlaminar properties of additive manufactured hybrid composites, revealed a progressive porosity reduction preserving the dimensional accuracy. The enhancement of mechanical properties is due to different contributions that occurred during post-processing: (i) drying effect, which reduces the plasticization of the composites; (ii) improvement of interface adhesion due to the miscibility of polymers; and (iii) significant porosity reduction (below 1 %). This work opens a wider space of possibilities, since FFF allows more complex designs than traditional composite manufacturing, and additionally provides an approach to promote molecular diffusion at the interface, which is the most critical region of FFF parts.

A comparative analysis between backpropagation and general regression neural networks to predict the tensile properties of fused filament fabricated parts

The Fused Filament Fabrication (FFF) process comprises a large number of process parameters that affect the resultant mechanical properties of the parts, generating uncertainties during the Design for Additive Manufacturing (DfAM) practice. Several studies have used Artificial Neural Networks (ANN) based on classification machine learning techniques such as Backpropagation Neural Network (BPNN), to evaluate the dimensional accuracy, surface roughness, compressive, flexural and tensile strength of FFF parts. As an alternative, in this paper a new General Regression Neural Network (GRNN) approach, based on a regression machine learning technique, is proposed to estimate the tensile structural properties of polylactic acid (PLA)-FFF parts using variable process parameters. The performance of the new proposed GRNN is compared with the performance of a BPNN. The comparison and evaluation are based on their capability to accurately predict the experimental Ultimate Tensile Stress (UTS) and the Elastic Modulus ( E) of FFF parts. The outcomes of this evaluation have shown that although the GRNN and the BPNN are able to estimate with high accuracy the structural behaviour of FFF parts, the performance of the proposed GRNN is superior (0.001 Mean Square Error, MSE) than the BPNN (0.0031 MSE). Moreover, the new proposed GRNN fits the experimental test values with a minimal average error of 0.62%. Thus, the proposed GRNN can be used during the design of components intended to be manufacture by FFF.

Mechanism-Based damage and failure of Fused Filament Fabrication components

Fused Filament Fabrication (FFF) is a polymer-based Additive Manufacturing (AM) technology that produces complex layered components. The characterization of the inherited orthotropic properties of FFF components and their failure analysis is a challenging endeavor. In this paper, the failure mechanics of FFF parts are studied via a Mechanism-Based (MB) damage material model. A MB damage criterion is developed by considering that the damage is driven by different failure modes identified according to the printing pattern. The developed criterion is compared to the Tsai–Wu (TW) criterion, which is commonly used for orthotropic materials with different strengths in tension and compression. Also, a MB cracking model that incorporates the orthotropic brittleness of FFF components is developed. The application of this cracking model requires solely two parameters to be defined.Numerical predictions of the cracking of two different experimental tests illustrate the similarities and the differences between the MB and TW damage criteria. The results demonstrate that the MB damage criterion can accurately match the experimental results, while the TW criterion fails to describe correctly the failure modes in complex 3D stress states.

A simple method for improving the tensile strength of fused filament fabrication part

A simple method for improving the tensile strength of fused filament fabrication part

Exploration of Methodologies for Developing Antimicrobial Fused Filament Fabrication Parts.

Composite 3D printing filaments integrating antimicrobial nanoparticles offer inherent microbial resistance, mitigating contamination and infections. Developing antimicrobial 3D-printed plastics is crucial for tailoring medical solutions, such as implants, and cutting costs when compared with metal options. Furthermore, hospital sustainability can be enhanced via on-demand 3D printing of medical tools. A PLA-based filament incorporating 5% TiO2 nanoparticles and 2% Joncryl as a chain extender was formulated to offer antimicrobial properties. Comparative analysis encompassed PLA 2% Joncryl filament and a TiO2 coating for 3D-printed specimens, evaluating mechanical and thermal properties, as well as wettability and antimicrobial characteristics. The antibacterial capability of the filaments was explored after 3D printing against Gram-positive Staphylococcus aureus (S. aureus, ATCC 25923), as well as Gram-negative Escherichia coli (E. coli, ATCC 25922), and the filaments with 5 wt.% embedded TiO2 were found to reduce the viability of both bacteria. This research aims to provide the optimal approach for antimicrobial and medical 3D printing outcomes.

Predicting Properties of Fused Filament Fabrication Parts through Sensors and Machine Learning

Fused filament fabrication (FFF), colloquially known as 3D-printing, has gradually expanded from the laboratory to the industrial and household realms due to its suitability for producing highly customized products with complex geometries. However, it is difficult to evaluate the mechanical performance of samples produced by this method of additive manufacturing (AM) due to the high number of combinations of printing parameters, which have been shown to significantly impact the final structural integrity of the part. This implies that using experimental data attained through destructive testing is not always viable. In this study, predictive models based on the rapid prediction of the required extrusion force and mechanical properties of printed parts are proposed, selecting a subset of the most representative printing parameters during the printing process as the domain of interest. Data obtained from the in-line sensor-equipped 3D printers were used to train several different predictive models. By comparing the coefficient of determination (R2) of the response surface method (RSM) and five different machine learning models, it is found that the support vector regressor (SVR) has the best performance in this data volume case. Ultimately, the ML resources developed in this work can potentially support the application of AM technology in the assessment of part structural integrity through simulation and can also be integrated into a control loop that can pause or even correct a failing print if the expected filament force-speed pairing is trailing outside a tolerance zone stemming from ML predictions.

Phase-field modeling of fracture in fused filament fabricated thermoplastic parts and experimental validation

In this work, a phase-field fracture model is formulated specifically for thermoplastic parts manufactured by fused filament fabrication (FFF). Due to their layered nature, FFF parts present an orthotropic fracture behavior, with their interfaces representing energetically favorable crack paths. The proposed phase-field model relies on the introduction of two damage variables, one for cross-layer and one for inter-layer crack propagation, allowing to capture the distinct fracture behavior of the thermoplastic filaments and the interfaces. The model is applied to the three-point bending of single-edge notched bending (SENB) FFF specimens with six different material orientations. The comparison with the experimental results shows that the proposed phase-field model can predict the experimentally observed peak load for the six material orientations with a maximum error of ≈ 11%. Furthermore, the model can also accurately predict the crack path and the softening behavior observed experimentally. To validate the capacities of the phase-field model, an experimental campaign on FFF compact-tension (CT) specimens modified with holes was performed. Comparing the numerical prediction with the experimental results for the modified CT specimens shows that, although the model features some limitations, it is still able to accurately capture the location of crack initiation and predict the peak load with a relative error of ≈ 2%.

Influence of Three-Dimensional Printing Parameters on Compressive Properties and Surface Smoothness of Polylactic Acid Specimens.

While the mechanical performance of fused filament fabrication (FFF) parts has been extensively studied in terms of the tensile and bending strength, limited research accounts for their compressive performance. This study investigates the effect of four process parameters (layer height, extrusion width, nozzle temperature, and printing speed) on the compressive properties and surface smoothness of FFF parts made of Polylactic Acid (PLA). The orthogonal Taguchi method was employed for designing the experiments. The surface roughness and compressive properties of the specimens were then measured and optimized using the analysis of variance (ANOVA). A microscopic analysis was also performed to identify the failure mechanism under static compression. The results indicated that the layer height had the most significant influence on all studied properties, followed by the print speed in the case of compressive modulus, hysteresis loss, and residual strain; extrusion width in the case of compressive strength and specific strength; and nozzle temperature in the case of toughness and failure strain. The optimal design for both high compressive properties and surface smoothness were determined as a 0.05 mm layer height, 0.65 mm extrusion width, 205 °C nozzle temperature, and 70 mm/s print speed. The main failure mechanism observed by SEM analysis was delamination between layers, occurring at highly stressed points near the stitch line of the PLA prints.

An Experimental Investigation about the Dimensional Accuracy and the Porosity of Copper-Filled PLA Fused Filament Fabrication Parts

In recent years, metal-filled plastic filaments have begun to be used in fused filament fabrication (FFF) technology. However, the characterization of the parts obtained is still under development. In this work, the results on dimensional accuracy and porosity of copper-filled 3D-printed parts are presented. Cuboid parts were 3D-printed in the vertical position. The three dimensions of each part were measured, and the relative error was calculated for each one of them. Dimensional accuracy in terms of width and depth depends mainly on the layer height and printing temperature, while accuracy in height is mainly influenced by print speed and the interaction of layer height with print speed. Porosity is related to layer height, printing temperature and print speed. According to multiobjective optimization, to minimize dimensional error and obtain a porosity target value of 20%, it is recommended to select a low layer height of 0.1 mm, a high print speed of 40 mm/s, a low extrusion multiplier of 0.94 and a low temperature of 200 °C. The results of the present work will help to select appropriate 3D printing parameters when using metal-filled filaments in FFF processes.

Study of parametric interaction during fused filament fabrication (FFF) using interpretive structural modelling (ISM) followed by experimental analysis

PurposeFused filament fabrication (FFF) is a type of additive manufacturing (AM) based on materials extrusion. It is the most widely practiced AM route, especially used for polymer-based rapid prototyping and customized product fabrication in relation to aerospace, automotive, architecture, consumer goods and medical applications. During FFF, part quality (surface finish, dimensional accuracy and static mechanical strength) is greatly influenced by several process parameters. The paper aims to study FFF parametric influence on aforesaid part quality aspects. In addition, dynamic analysis of the FFF part is carried out.Design/methodology/approachInterpretive structural modelling is attempted to articulate interrelationships that exist amongst FFF parameters. Next, a few specimens are fabricated using acrylonitrile butadiene styrene plastic at varied build orientation and build style. Effects of build orientation and build style on part’s ultimate tensile strength, flexure strength along with width build time are studied. Prototype beams (of different thickness) are fabricated by varying build style. Instrumental impact hammer Modal analysis is performed on the cantilever beams (cantilever support) to obtain the natural frequencies (first mode). Parametric influence on natural frequencies is also studied.FindingsStatic mechanical properties (tensile and flexure strength) are greatly influenced by build style and build orientation. Natural frequency (NF) of prototype beams is highly influenced by the build style and beam thickness.Originality/valueFFF built parts when subjected to application, may have to face a variety of external dynamic loads. If frequency of induced vibration (due to external force) matches with NF of the component part, resonance is incurred. To avoid occurrence of resonance, operational frequency (frequency of externally applied forces) must be lower/ higher than the NF. Because NF depends on mass and stiffness, and boundary conditions, FFF parts produced through varying build style may definitely correspond to varied NF. This aspect is explained in this work.

SANDBLASTING POST-PROCESSING ANALYSIS TO IMPROVE OF FUSED FILAMENT FABRICATIONS PARTS

Sandblasting is a post-processing process that is required to improve the surface due to the layered nature of fused filament fabrication parts. This paper presents preliminary work based on full factorial design of experiment, considering pressure (100 kPa and 700 kPa), time (10 s and 120 s), distance (10 mm and 370 mm) and aluminium oxide abrasive which is 106 µm and 29.5 µm of particles size as the input factors. The effect of the parameters on the surface roughness (Sa) for flat and curve surface, material usage and energy consumption allow were analysed. The result shows that both Sa for flat and Sa curve surface were highly influenced by the abrasive particles size and time with the highest changes of Sa for flat and curve reaches up to 2.825 µm and 6.090 µm respectively. This study provides information on how sandblasting parameters should be selected in improving surface quality and resource usage.

Investigation on the improvement of mechanical properties and surface quality of the polylactic acid (PLA) fused filament fabrication parts manufactured without and with vibrations dependent utilization

Fused Filament Fabrication (FFF), is one of the most widely used additive manufacturing technologies today, which has been used for a variety of applications. Due to the layer-by-layer manufacturing process, FFF parts are inferior to those fabricated by traditional methods in terms of tensile properties, which is one of the most significant defects that hinder the development of this technique. In this study, a vibration was utilized during the FFF process by piezoelectric ceramics electric plates to improve the mechanical properties of the built parts and surface quality of PLA FFF parts. Subsequently, an investigation of the tensile and the surface quality of PLA FFF specimens built-in X and Z-direction fabricated individually without and with vibrations utilized has been done. Furthermore, a theoretical model has been established to predict the tensile strength and plasticity of FFF parts fabricated without and with vibrations utilized based on classical laminated plate theory, with the anisotropic and laminated characteristics taken into consideration. Young's modulus model has been established based on the laminated plate theory and flexural vibration theoretical approaches of a plate for the PLA FFF parts manufactured without and with vibrations utilized respectively. Compared with the previous models this model provides the tensile strength and plasticity of FFF parts both manufactured without and with vibrations utilized. The results indicate that the predicted tensile strength and plasticity of the PLA FFF parts manufactured with vibrations utilized have a good consistency with the experimental ones, meanwhile, vibration utilization can significantly improve the surface quality of the PLA FFF samples manufactured in the Z-direction, and the scanning electron microscopy (SEM) analysis confirmed that vibration utilization can improve the forming quality of FFF manufactured parts.

Shore hardness of as-printed and dehydrated thermoplastic materials made using fused filament fabrication (FFF)

This article explores the Shore hardness (following ASTM D2240) of 10 common engineering plastics and chopped carbon fiber composites that have been processed using fused filament fabrication (FFF). The study was done in two parts, the first focusing on raw, as-printed specimens (typical use case for FFF parts) and the second looking at specimens that spent various lengths of time (4 h, 24 h, and 72 h) in a heated dehydration chamber. Extensive analyses of the collected data showed that dehydrating the samples had a statistically significant effect (based on 25 replications) in most cases, showing that the moisture content of tested FFF samples is an important factor in their characterization and use. For most of the materials, the hardness either plateaued or decreased after a certain dehydration time, suggesting that FFF parts are affected by both too much and too little moisture content. The study also included an extensive sensitivity analysis related to the required specimen thickness for valid hardness tests. In addition to providing useful new characterization data for the materials, the results of this study give design information that will be useful for material selection when using FFF as a manufacturing process.

Effects of infill orientation and percentage on the magnetoactive properties of 3D printed magnetic elastomer structures

This work investigates how the internal meso structure of fused filament fabrication parts influence the magnetoactive properties of printed magnetic elastomer structures. Elastomers were made by adding 40wt% magnetite (Fe3O4) to a thermoplastic polyurethane (TPU) matrix. Magnetoactive testing was used to investigate how varying the infill structure affected the mechanical response of the structures within an applied magnetic field. Different infill percentages (40%, 60%, and 100%) and infill orientations (0, 45, and 90 degrees) were tested to account for different mechanical stiffnesses and internal geometries. Each sample was magnetoactively tested with three transverse magnetic field orientations (front, back and top). The samples were placed between two electromagnets, and the angle of deflection was recorded as a function of applied field. The maximum angles of deflection for the testing setup were reached when using lower infill percentages and having infill oriented parallel to the long axis of the sample and transverse to the magnetic field. Transverse fields applied parallel to the print plane (front/back sample orientations) demonstrated the most magnetoaction due to easier alignment of the long side of the sample with the field. This coupled with the 0-degree infill orientation having less crosslinking constraining the bending stiffness led to greater deflection. The magnetic anisotropy of the infill structure likely also contributed to the large response from certain samples. It was concluded that for this fixed base material, it is more important to 3D print structures with lower stiffnesses than more net magnetic particulate (more infill) to achieve the most magnetoaction.

Fatigue experimental analysis and modelling of fused filament fabricated PLA specimens with variable process parameters

PurposeThe purpose of this study is twofold: firstly, to investigate the effect of the infill value and build orientation on the fatigue behaviour of polylactic acid (PLA) specimens made by fused filament fabrication (FFF), also known as fused deposition modelling; and secondly, to model the fatigue behaviour of PLA specimens made by FFF and similar additive manufactured parts.Design/methodology/approachA new methodology based on filament characterisation, infill measuring, axial fatigue testing and fatigue strength normalisation is proposed and implemented. Sixty fatigue FFF specimens made of PLA were fabricated and evaluated using variable infill percentage and build orientation. On the other hand, fatigue modelling is based on the normalised stress amplitude and the fatigue life in terms of number of cycles. In addition, a probabilistic model was developed to predict the fatigue strength and life of FFF components.FindingsThe infill percentage and build orientation have a great influence on the fatigue behaviour of FFF components. The larger the infill percentage, the greater the fatigue strength and life. Regarding the build orientation, the specimens in the up-right orientation showed a much smaller fatigue strength and life than the specimens in the flat and on-edge orientations. Regarding the fatigue behaviour modelling, the proposed Weibull model can predict with an acceptable reliability the stress-life performance of PLA-FFF components.Research limitations/implicationsThis study has been limited to axial fatigue loading conditions along three different build orientations and only one type of material.Practical implicationsThe results of this study are valuable to predict the fatigue behaviour of FFF parts that will work under variable loading conditions. The proposed model can help designers and manufacturer to reduce the need of experimental tests when designing and fabricating FFF components for fatigue conditions.Originality/valueA fatigue study based on a novel experimental methodology that considers the variation of the FFF process parameters, the measurement of the real infill value and the normalisation of the results to be comparable with other studies is proposed. Furthermore, a new fatigue model able to predict the stress-life fatigue behaviour of PLA-FFF components considering variable process parameters is also proposed.

Effect of 3D Printing Parameters on the Fatigue Properties of Parts Manufactured by Fused Filament Fabrication: A Review

The advancement in 3D printing techniques has raised the hope to use additively manufactured parts as final products in various industries. However, due to the layer-by-layer nature of AM parts, they are highly susceptible to failure when they are subjected to fatigue loading. This review provides a detailed account of the influence of 3D printing parameters on the fatigue properties of parts manufactured by fused filament fabrication (FFF). Existing standards for fatigue testing of polymers and their limitation for 3D-printed parts are discussed. In addition, the cyclic behaviour of polymers is reviewed, and the impact of 3D printing parameters on the mechanical behaviour of FFF parts under tensile, compressive, flexural, and bending fatigue is investigated according to the published results in the literature. Finally, a summary of the works undertaken and suggestions for future research are provided. The influence of 3D printing parameters on the fatigue performance of prints can be different from that seen in the case of static loading and strongly depends on the fatigue loading type. While cross-over infill patterns, higher infill density, and higher layer height favour achieving higher fatigue strength in all loading types, raster orientation is best to be aligned parallel to the tensile loads and perpendicular to the compressive, flexural, and bending forces. In the case of tensile and flexural loading, Y build orientation yields the best result. Finally, print velocity was found to be less significant compared to other parameters, implying that it can be set at high values for faster printing.

Experimental study on the effect of selected sterilization methods on mechanical properties of polylactide FFF specimens

PurposeBiodegradable polymers are widely used in personalized medical devices or scaffolds for tissue engineering. The manufacturing process should be finished with sterilization procedure. However, it is not clear how the different sterilization methods have an impact on the mechanical strength of the three-dimensional (3D)-printed parts, such as bone models or personalized mechanical devices. This paper aims to present the results of mechanical testing of polylactide-based bone models before and after sterilization.Design/methodology/approachPolylactide specimens prepared in fused filament fabrication technology were sterilized with different sterilization methods: ultraviolet (UV) and ethylene oxide. Mechanical properties were determined by testing tensile strength, Young’s modulus and toughness.FindingsThe tensile strength of material after sterilization was significantly higher after ethylene oxide sterilization compared to the UV sterilization, but in both sterilization methods, the specimens characterized lower tensile strength and Young’s modulus when compared to the control. In comparison of toughness results, there was no statistically significant differences. The findings are particularly significant in the perspective of using individual implants, bone grafts and dental guides.Originality/valueAlthough fused filament fabrication (FFF) 3D printing devices equipped with UV light sterilization options are available, experimental results of the effect of selected sterilization methods on the mechanical strength of additively manufactured parts have not been described. This paper completes the present state of the art on the problem of sterilization of FFF parts from biodegradable materials.

Eliminating voids and reducing mechanical anisotropy in fused filament fabrication parts by adjusting the filament extrusion rate

Fused filament fabrication (FFF) is one of the most common additive manufacturing (AM) processes due to its simplicity and low cost. However, weak interlayer interfaces, high porosity, and mechanical anisotropy limit FFF applications. This paper investigates the effects of an FFF process parameter, i.e., extrusion multiplier, on the structure and interlayer strength of FFF parts made from acrylonitrile butadiene styrene (ABS). Increasing the extrusion multiplier over its predefined standard value improved the tensile strength in the print direction (X-orientation) and build direction (Z-orientation) by up to 10% and 50%, respectively, resulting in entirely void-free parts with nearly isotropic strength. These improvements are explained via finite element analysis (FEA) and bonding mechanisms in FFF. Finally, the effects of extrusion rate on various AM features in a benchmark part are investigated. This study shows that mechanical anisotropy is not inherent to FFF and, despite the common belief, voids can be eliminated entirely in FFF parts. Complex isotropic parts can be made via FFF, opening new applications for this technology and allowing it to compete with other AM processes.

A data-driven framework to predict fused filament fabrication part properties using surrogate models and multi-objective optimisation

In additive manufacturing (AM), due to large number of process parameters and multiple responses of interest, it is hard for AM designers to attain optimal part performance without a systematic approach. In this research, a data-driven framework is proposed to achieve the desired AM part performance and quality by predicting part properties and optimising AM process parameters effectively and efficiently. The proposed framework encompasses efficient sampling of design space and establishing the initial experiment points. Based on established empirical data, surrogate models are used to characterise the influence of critical process parameters on responses on interest. Furthermore, process maps can be generated for enhancing understanding on the influence of process parameters on responses of interests and AM process characteristics. Subsequently, multi-objective optimisation coupled with a multi criteria decision-making technique is applied to determine an optimal design point, which maximises the identified responses of interest to meet the part functional requirements. A case study is used to validate the proposed framework for optimising an ULTEM™ 9085-fused filament fabrication part to meet its functional requirements of surface roughness and mechanical strength. From the case study, results indicate that the proposed approach is able to achieve good predictive results for responses of interest with a relatively small dataset. Furthermore, process maps generated from the surrogate model provide a visual representation of the influence between responses of interest and critical process parameters for FFF process, which traditionally requires multiple investigations to arrive at similar conclusions.