Fused Filament Fabrication Machine Research Articles

AutoML-driven diagnostics of the feeder motor in fused filament fabrication machines from direct current signals

AbstractPart defects in additive manufacturing are more frequent compared to machining or molding. Failures can go unnoticed for hours, wasting resources and extending process cycle times. This paper describes a Machine Learning based method for automated sensing of onset failure in additive manufacturing machinery. Investigations are conducted on a Fused Filament Fabrication (FFF) 3D printer, and the same methods are then applied to a digital light processing 3D printer. The investigation focuses on signal-based analysis, specifically passive sensing of stepper motors relating DC current measurements to the torque on a stepper, as opposed to any active acoustic interrogation of the part. Passive methods are used to characterize the loading on a feeder stepper in an FFF machine, forming a model that can identify early signs of filament-based failure with 85.65% 10-fold cross-validation accuracy. Efforts show filament breakage can be detected minutes before material runout would cause a defect, allowing ample time to pause, correct, or control the print. The machine learning pipeline was not naively conceived but optimized through automated machine learning.

Adhesion Testing Device for 3D Printed Objects on Diverse Printing Bed Materials: Design and Evaluation

The persistent challenge of adhesion in Fused Filament Fabrication (FFF) technology is deeply rooted in the mechanical and chemical properties of utilized materials, necessitating the exploration of potential resolutions. This involves adjustments targeting the interplay of printing parameters, the mechanical fortification of print beds, and the integration of more adhesive materials, resonating across user levels, from enthusiasts to complex industrial configurations. An in-depth investigation is outlined in this paper, detailing the plan for a systematically designed device. Engineered for FFF device installation, the device facilitates the detachment of printed models, while precisely recording the detachment process, capturing the maximum force, and its progression over time. The primary objective is fabricating a comprehensive measurement apparatus, created for adhesion assessment. The device is adaptable across diverse FFF machines and print bed typologies, conforming to pre-defined conditions, with key features including compactness, facile manipulability, and capacity for recurrent measurements. This pursuit involves evaluating adhesion levels in prints made from diverse materials on varying print bed compositions, aiming to establish a comprehensive database. This repository facilitates judicious material and bed type selection, emphasizing maximal compatibility. Emphasis is placed on operating within a thermally stable context, a pivotal prerequisite for consistent and reproducible results.

THE EFFECT OF DIFFERENT SLICING SOFTWARE ON THE MANUFACTURING PERFORMANCE OF 3D PRINTED PARTS

Plastic 3D printing is currently in-trend for producing custom parts and products with intricate geometry. Fused Filament Fabrication (FFF) is one of the preferred technologies, as it requires a simple operation with affordable equipment setup. Previous studies have achieved many breakthroughs in using FFF. To successfully produce parts using the FFF machine, a slicing software is required to provide instructions to the machine. Currently, numerous slicing software are available in the market that can be integrated to the FFF machine. Each slicing software has a slightly different performance compared with others. Therefore, careful consideration should be taken when choosing the most suitable slicing software for the machine in use. In this work, three slicing software, namely, Ultimaker Cura 4.8.0, Cura 2.7.0, and PrusaSlicer have been chosen to investigate their effect on the manufacturing performance of 3D printed parts. The parameters for evaluating manufacturing performance were accuracy of the slicing software in predicting printing time, the dimensional accuracy of the printed parts, and the surface roughness of the printed parts. The effect of printing speed was also investigated at three levels, which were at 20, 40, and 60 mm/s. In this work, the 3D Espresso F220 machine was used. The geometry of the printed parts followed the ASTM D638 Type I geometry using polylactic acid (PLA) filament material. The results showed that Ultimaker Cura 4.8.0 can produce the best results, if the priority of the producer is to use a software with high accuracy in printing time prediction and better surface quality. However, if the priority of the process is to produce small dimensional errors (close tolerance to designed geometry), the characteristics of the dimension (length, width, or thickness) need to be identified. Ultimaker Cura 4.8.0 produced small errors when the critical dimension was width, but Cura 2.7.0 was good for length dimension, while PrusaSlicer was good for thickness dimension. The results also showed that printing speed can affect the time of completion of the printed parts and the surface quality. The lowest printing speed was able to produce parts with better surface quality; however, printing time can become longer.

Filament extrusion state monitoring in fused filament fabrication using Bhattacharyya distance and K-nearest neighbor

Fused filament fabrication (FFF) is one of the most popular techniques of additive manufacturing. However, product quality issues still limit the further application of FFF technology. Filament extrusion state has a great influence on the quality of FFF fabricated products, since both under-extrusion and over-extrusion can lead to the deterioration of product quality. Therefore, monitoring the filament extrusion states is vital and essential. This paper aims to monitor the filament extrusion state by acoustic emission (AE). To achieve this goal, experiments are conducted on a desktop FFF machine, where the states of under-extrusion and over-extrusion are induced by different extrusion speeds. Original AE signals are collected during the experiments. Confronted with the challenge posed by the susceptibility of AE signals to noise during the complex extrusion process and different conditions, one calculates the statistical distribution of the features defined on the raw AE signals, without the need for noise reduction steps. The k-nearest neighbor algorithm is then adopted to identify the different extrusion states, where the Bhattacharyya distance is employed to measure the distances or similarities of the calculated distributions. The findings demonstrate the successful identification of various extrusion states induced by different extrusion speeds through the presented method. The outcomes of this study pave the way for the development of an affordable in-situ FFF monitoring system with comprehensive capabilities.

Fused filament fabrication of Nylon beyond the glass transition temperature in a thermally-insulated machine

Fused filament fabrication (FFF) is a popular additive manufacturing process by extruding the molten thermoplastic from a nozzle to build an object layer-by-layer. Nylon is an engineering plastic that has good mechanical and chemical properties for assistive devices such as orthoses and prostheses (O&P). Nylon has been successfully applied in FFF of custom O&P. Based on the low glass transition temperature around 50-70℃ of Nylon, an idea to thermally-insulate the build chamber of an FFF machine to raise the temperature in the build volume to above Nylon’s glass transition temperature without additional heating is proposed. Without extensive active heating and cooling, such thermally-insulated FFF machines may achieve cost-effective FFF of custom O&P for practical use. This paper studies this FFF machine concept for FFF of dog bone specimens. The chamber of the FFF machine was thermally insulated. COMSOL Multiphysics® simulation software was adopted to predict the chamber’s temperature level and verified by experimental measurements with eight thermocouples. The effectiveness of the method was validated by the tensile test and microscopic observation of the printed tensile specimens. The strength of the FFF printed tensile specimens with thermally insulated chamber was 26.4% higher than that of the specimens printed at room temperature and close to the annealed FFF specimens. A better interlayer connection was also observed in the specimens FFF printed with the proposed method.

Structural stability of Polylactide rope drums with a hybrid Gyroid-spokes infill structure, manufactured through fused filament fabrication

Additive manufacturing (AM) offers greater design freedom than conventional manufacturing processes. AM allows for components with complex infill structures of e. g. triply periodic-minimal surfaces (TPMS) that lead to significant weight reduction. Nevertheless, AM is mainly used in specialised engineering branches such as aerospace and medical engineering. This is due to high system cost and the high energy costs of the machines used, which utilise selective laser sintering (SLS), laser powder bed fusion (LPBF), or stereolithography (SLA). Fused filament fabrication (FFF) can offer cheaper and more energy-efficient machines. A series of tensile tests with FFF rope drum bodies made from polylactide (PLA) aims to investigate the stability of FFF machine elements. The test specimens possess a novel, hybrid infill structure comprised of straight spokes and a TPMS-gyroid surface. Compared to previous investigations, the specific breaking force – relative to the test specimens’ weight – increased by up to 159%. Whereas the infill density affects tensile strength as well as deformation, the infill distribution between the TPMS and spokes part of said hybrid structure affects especially the deformation behaviour. The results show that FFF machine elements such as the tested drum bodies have a realistic perspective for use in future products with regard to static strength.

In situ process monitoring using acoustic emission and laser scanning techniques based on machine learning models

Fused Filament Fabrication (FFF) is a widely used additive manufacturing method for obtaining prototypes with complex structures. On the other hand, Commercial FFF machines have limits on process dependability and product quality. Numerous parameters can impact the printing process's accuracy and stability. This study created a real-time monitoring system based on acoustic emission (AE) and laser scanning technology to monitor the warpage defect in fabricated parts throughout the printing process. The AE signal generated during the printing process indicates variations in vibration caused by changes in the part's internal tension. It is capable of precisely displaying real-time part characteristics. After amplifying and filtering the AE signal, the frequency and time domain characteristics are retrieved and trained in the machine learning model. Laser scanning depth image data could be utilized to quantify the dimensional changes of the part. After noise reduction and processing, the point cloud data collected by the laser scanner can represent the specific percentage of warpage. The experimental results demonstrate that the machine learning models trained by AE sensory data can accurately identify if warpage of various sizes is formed with great accuracy in real time. This study examines the support vector machine, naïve bayes classifier, and decision tree data-driven machine learning models.

An Investigation in Tone Characteristics of 3D Printed Ukulele Sound Chambers

Musical instruments, and in turn their respective sounds, have changed and developed over time with advents and advances in various manufacturing methods and technologies. In order to effectively interpret the causes of different experimental sound nuances, it becomes important to investigate them metrically in light of precedent sounds. As 3D printing technology emerges into the arena of musical instrument development, so does the need for a thorough understanding of present tools and empirical acoustic groundwork for future endeavors. For the scope of this research, three different filament types (ABS, PLA, and HIPS) were used to print soprano ukulele style resonating chambers using a TAZ 6 fused filament fabrication machine. Normalized sound samples were compared to Makanu soprano ukulele baseline using three tone metrics, drawing from MATLAB Fast Fourier transform and spectrogram functionality. The selected metrics of fullness, sustain and strength demonstrated definitive, early progress toward better understanding sound characteristics of 3D printed string instruments.

Filament Transport Control for Enhancing Mechanical Properties of Parts Realised by Fused Filament Fabrication.

The fused filament fabrication (FFF) process is widely used for producing prototypes and functional parts for diverse applications. While FFF is particularly attractive due to its cost-effectiveness, on the other hand, the fabricated parts have limitations in terms of large manufacturing time and reduced mechanical properties. The latter is strongly influenced by the fabrication process parameters, which affect the interlayer bonding and the adhesion between consecutive layers. Several works presented in the literature analysed the correlation between mechanical properties and process parameters. It was demonstrated that an increase in the fabrication feed rate causes slippage between filament and the feeding system, which leads to a decrease in the extruded material flow, and thus in part density. This work aims to investigate how the limitation of the slippage phenomenon affects the mechanical properties of parts fabricated using the FFF process. A prototype machine, equipped with a closed-loop control system on filament transport, was used to fabricate samples for tensile tests and dynamical mechanical analysis. Samples fabricated enabling the filament transport control showed an increase both in ultimate tensile strength and elongation at break for those fabricated with disabled control, whilst a decrease in stiffness was observed. In addition, the results showed that the use of a filament transport control system on a FFF machine increases the possibility of fabricating high value-added parts.

Characterization of power demand and energy consumption for fused filament fabrication using CFR-PEEK

PurposeThis study aims to model power demand and energy consumption of fused filament fabrication (FFF) for carbon fiber-reinforced polyether-ether-ketone (CFR-PEEK) based on a material addition rate (MAR), which is affected by process parameter changes in an FFF machine. Moreover, a virtual additive manufacturing (AM) plant handling multiple FFF machines and part designs is simulated to compare the energy and production dynamics of operational strategies that treat part orders differently based on their inherent MAR.Design/methodology/approachA full-factorial design of experiments considering major FFF parameters (i.e., layer thickness and printing speed) is planned to fabricate CFR-PEEK samples for each process parameter combination. Then, the MAR of each process parameter combination is calculated to derive regression models for average power demand and total energy consumption. Furthermore, a discrete-event simulation model for a virtual AM system of aircraft parts is built to analyze changes in power demand and energy consumption along with order lead time and production volume under three operational strategies (i.e., higher MAR first-out, first-in-first-out, and lower MAR first-out).FindingsThe MAR of FFF for CFR-PEEK plays a key role in energy dynamics in which a decrease in energy consumption dominates over an increase in power demand as the MAR increases. Furthermore, preferentially processing parts with a higher MAR in the AM system is the most beneficial strategy in both energy consumption and productivity.Originality/valueThe findings from this study show that the energy performance of CFR-PEEK applications in FFF should be understood with the MAR of an AM system because the impact of AM complexity on energy performance can be operationally controlled by managing the MAR of part orders for the entire AM system.

Mica filled polyetherketoneketones for material extrusion 3D printing

Polyetherketoneketone (PEKK) has superior physical properties to most available thermoplastics compatible with material extrusion-based 3D printing. The performance of fused filament fabrication (FFF) compatible PEKK has been detailed primarily as a function of varying the isomer ratios composing the co-polymer structure. PEKK composite or blend development for AM has received limited attention, yet this strategy is attractive for further performance tailoring and to address challenges associated, for example, with shrinkage upon crystallization. Here, we report the integration of three grades of mica platelets into PEKK at 10% and 30% mass loadings to generate an array of filament feedstocks that were used to print objects with a simple FFF machine. The effects of mica coating chemistry on the compatibility with PEKK and resulting properties are described. Mica fillers have only subtle influence on the FFF relevant melt rheological properties inherent to PEKK. Pigment micas at high loadings reduce the melting temperature of PEKK without shifting its glass transition temperature or inducing undesirable crystallization during processing. The printed composites were effectively cold crystallized post-printing similarly to unfilled PEKK resulting in increased dimensional stabilities. All micas, when used as fillers in low and high relative PEKK crystallinities, increased the tensile modulus of parts in correlation to the loading. The microstructural features of a printed composite were compared to unfilled PEKK by use of high-resolution helical micro-computed tomography. Practically, pigment micas can confer a wide range of rich colors to 3D-printed PEKK.

Closed-Loop Filament Feed Control in Fused Filament Fabrication.

Fused filament fabrication (FFF) is an additive manufacturing process where a thermoplastic polymeric material, provided in the form of a filament, is extruded to create layers. Achieving a consistent flow of the extruded material is key to ensure quality of the final part. Extrudate flow depends on many factors; among these, the rate at which the filament is fed into the extruder. In a conventional FFF machine, filament transport is achieved through the use of a drive gear. However, slippage between the gear and the filament may occur, leading to reduced transport and the consequent local decrease of extrudate flow rate, which in turn leads to a series of imperfections in the fabricated part due to underextrusion, including reduced density. In this work, we propose a closed-loop control system to ensure the correct filament transport to the extruder. The system works through the comparison between the nominal transport of the filament and the actual filament transport measured using an encoder. The measured value is used to correct the filament feed rate in real time, ensuring a material flow close to the nominal one, regardless of the other process parameters. In this work, an instrumented FFF machine prototype was used to investigate the performance of the approach. For validation, parts were realized using different process parameters, while enabling and disabling the closed-loop control system. Results showed that the relative filament transport error decreased from up to 9% to below 0.25% and a density increase up to ∼10% regardless of the process parameters, as well as the reduction of interlayer and intralayer voids, as highlighted through cross-sectional imaging of realized samples. A reduction of defects on realized parts was observed, especially at higher fabrication feed rates.

Measurement, characterisation and influence of the air temperature above the build plate in fused filament fabrication

• Air temperature above a heated horizontal plate exponentially decreases with a characteristic decaying constant l c . • Near environment strongly affects the part cooling when printing at high resolutions (low layer thickness). • Closed chamber raises the far environment temperature, hence delaying the part cooling and are specifically beneficial for large scale printing. Heated build plates are common yet essential components in many additive manufacturing (AM) machines. However, their influence on the air temperature above and the subsequent impact on the AM process are barely discussed. This article proposes a simple model for the air temperature above the plate T a ( z ) , which exponentially decays from the plate temperature to the far environment temperature by a characteristic dimension l c in the range of 2–9 mm. The model has been empirically validated for three fused filament fabrication (FFF) machines, including open and closed systems, small and large build chambers. Temperature simulations in printed parts suggest that T a ( z ) plays a critical role when printing at low layer thicknesses, such as 300 µm. Besides, adding an enclosure to FFF machines can significantly raise the far environment temperature inside the chamber, delaying the part cooling. However, its effect is noticeable for the portion above 10 mm only.

Heat Transfer-Based Non-isothermal Healing Model for the Interfacial Bonding Strength of Fused Filament Fabricated Polyetheretherketone.

Fused Filament Fabrication (FFF) as an Additive Manufacturing (AM) method for Polyetheretherketone (PEEK) has established a promising future for medical applications so far, however interlayer delamination as a failure mechanism for FFF implants has raised critical concerns. A one-dimensional (1D) heat transfer model (HTM) was developed to compute the layer and interlayer temperatures by considering the nature of 3D printing for FFF PEEK builds. The HTM was then coupled with a non-isothermal healing model to predict the interlayer strength through thickness of a FFF PEEK part. We then conducted a parametric study of the primary temperature effects of the FFF system, including the print bed, nozzle, and chamber temperatures, on layer healing. The heat transfer component of the model for the FFF PEEK layer healing assessment was validated separately. An idealized PEEK cube design (10x10x10 mm3) was used for model development and 3D printed in commercially available industrial and medical FFF machines. During the printing and cooling processes of FFF, thermal videos were recorded in both printers using a calibrated infrared camera. Thermal images were then processed to obtain time-dependent layer temperature profiles of FFF PEEK prints. Both the theoretical model and experiments confirmed that the upper layers in reference to the print bed exhibited higher temperatures, thus higher healing degrees than the lower layers. Increasing the print bed temperature increased the healing of the layers allowing more layers to heal 100%. The nozzle temperature showed the most significant effect on the layer healing, and under certain nozzle temperature, none of the layers healed adequately. Although environment temperature had less impact on the lower layers closer to the print bed, 100% healed layer number increased when the chamber temperature increased. The model predictions were in good agreement with the experimental data, particularly for the mid-part of FFF PEEK cubes printed in both FFF machines.

Optimization of build orientation in FFF using response surface methodology and posterior-based method

Purpose The advancement of additive manufacturing technologies has resulted in producing parts of high quality and reduced manufacturing time. This paper aims to achieve a simultaneous optimal solution for build time and surface roughness as the output data and also to find the best values for the input data consisting of build orientation, extrusion width, layer thickness, infill percentage and raster angle. Design/methodology/approach For this purpose, the effects of process parameters on the response variables were investigated by the design of experiments approach to develop empirical models using response surface methodology. The experimental parts of this research were conducted using an inexpensive and locally assembled fused filament fabrication (FFF) machine. A total of 50 runs for 4 different geometries, namely, cylinder, prism, 3DBenchy and twist gear vase, were performed using the rotatable central composite design, and each process parameters were investigated in two levels to develop empirical models. Also, a novel optimization method, namely, the posterior-based method, was accomplished to find the best values for the response variables. Findings The results demonstrated that not only the build orientation and layer thickness have notable effects on both response variables but also build time is dependent on extrusion width and infill percentage. Low infill percentage and high extrusion width resulted in increasing build time. By reducing layer thickness and infill percentage while increasing extrusion width, parts of high-quality surface finish and reduced built time were produced. Optimum process parameters were found to be of build direction of 0°, extrusion width of 0.61 mm, layer thickness of 0.22 mm, infill percentage of 20% and raster angle of 0°. Originality/value Through the developed empirical models and by minimizing build orientation and layer thickness, and also considerations for process parameters, parts of high-quality surface finish and reduced built time could be produced on FFF machines. To compensate for increased build time because of reduction in layer thickness, extrusion width and infill percentage must have their maximum and minimum value, respectively.

In-process simulation of the extrusion to support optimisation and real-time monitoring in fused filament fabrication

A simulation model is presented in this work, capable to predict temperature and velocity of the extrudate as well as the compressive force acting on the filament in a fused filament fabrication (FFF) machine operating with a Bowden extruder. The simulation model is developed for future incorporation into a larger on-machine apparatus designed for process monitoring and adaptive control and destined to the fabrication of high value-added parts. The simulation model captures mechanical aspects of the extruder (including slippage at the drive gear, filament compression into the hot end), as well as temperature and pressure changes within the extrusion chamber, where the filament is liquefied and transformed into the extrudate. The model is implemented so that it can react to changes in the part program as it is being executed, offering predictions on the extrusion process that can be compared with sensor measurements. The simulation model is implemented in prototype form and calibrated on a multi-sensor FFF machine working with a PLA filament within a range of predefined operating conditions (heating temperatures and print feed rates). Load cells, high-speed optical imaging and infra-red thermal imaging of the extrudate mounted on the FFF machine are used to verify the predictions of the simulation model.

Melt extrusion and additive manufacturing of a thermosetting polyimide

Abstract Additive manufacturing offers the ability to fabricate complex structures without the need for expensive tooling which is very attractive for manufacturing of structural composites. One limitation of additive manufacturing technologies hindering their adoption in high-performance structural composites is the lack of compatible high operating temperature thermosetting resins with robust thermo-oxidative stability. To address this limitation, a reactive melt extruded thermosetting polyimide filament was printed via fused filament fabrication (FFF). A crosslink chemistry has been designed with slow reaction kinetics at the printing temperature which allows printing in a similar manner to engineering thermoplastic filaments. A cure cycle for the as-printed uncrosslinked articles was developed to achieve full cure without loss of shape. The glass transition temperature of the fully cured resin is 250 °C. Comparing longitudinal and transverse tensile strengths of printed and cured coupons showed highly anisotropic behavior. Transverse and through-thickness properties for both uncured and cured printed coupons were nearly identical. The average measured tensile strength of printed and fully cured material was 86 MPa; 73% of fully cured compression molded strength. These results demonstrate the ability to 3D print high performance thermosets without changing commercially available FFF machines.

Development of a cylindrical coordinate-based fused filament fabrication machine with multiple print heads

Fused filament fabrication (FFF) is an additive manufacturing (AM) process that is intended to build three-dimensional objects through selective deposition of melted material layer-by-layer along a pre-determined path. In the last few years, the utilization of the FFF technology has grown at a high pace and today its use has become widespread in several applications. In the light of the premises, this work emerges as a technology push effort to develop an innovative FFF machine where cylindrical coordinate-based print motion is combined with multiple print heads. The proposed FFF machine was conceived and designed guided by appropriate methodologies concerning product development, assembly, servicing, and design for AM. Furthermore, as a proof of concept, a physical prototype was produced gathering traditional manufacturing processes with AM. The physical prototype was validated with speed, temperature, and deposition tests. The presented FFF machine presents higher manufacturing versatility due to the possibility of processing different materials (in the same part and in all printing area) with an increased production rate, that enables printing up to three parts simultaneously.

Development of polyetherimide composites for use as 3D printed thermal protection material

As additive manufacturing (AM) increasingly gains commercial and academic interest, government agencies, such as NASA Johnson Space Center, seek to produce thermal protection systems using AM methods, such as fused filament fabrication (FFF). The purpose of this study is to develop a suitable polyetherimide (ULTEM™ 1010) nanocomposite with enhanced ablation and thermal properties while maintaining compatibility with commercially available FFF machines. Eleven formulations were compounded using the twin-screw extruder with varying amounts of nanoclay, glass bubbles, and flame-retardant additives. All formulations were characterized via multiple instruments to be down-selected to four candidates for aerothermal testing. After discovering specific characteristics of some formulations, aerothermal test models were 3D printed for four formulations. Enhanced thermal properties among the composite formulations were demonstrated. Aerothermal testing also displayed promising results. In addition to experimental data, microstructural analyses were performed.

Thermal and geometry impacts on the structure and mechanical properties of part produced by polymer additive manufacturing

AbstractA relatively new additive manufacturing machine called Freeformer was employed as an alternative to common Fused Filament Fabrication (FFF) machines. While FFF machines are fed with expensive and few commercially available filament feedstock, Freeformer is fed with cheap and common polymer pellets. In this study, more than 400 dumbbells made of Acrylonitrile Butadiene Styrene (ABS) were processed varying many processing conditions to evaluate their impacts on the structure and so on, the mechanical properties of 3D parts. Among processing parameter, nozzle temperature, manufacturing chamber temperature, discharge parameters, filling density, raster geometry, slicing distance, number of contour lines, processing speed, filling raster‐contour lines overlap, and processing angles were studied. Images obtained with a scanning electron microscope and 3D part density estimations reveal strong changes on the 3D part structure as a function of the processing parameters so that tensile tests exhibit high variations between the 3D part mechanical properties.