Printing Parameters Research Articles

Machine learning enabled 3D printing parameter settings for desired mechanical properties

ABSTRACT Additive manufacturing facilitates the production of parts with tailored mechanical properties, yet achieving specific stress–strain responses remains a significant challenge due to the intricate relationship between printing parameters and material behaviour. This study introduces a novel approach utilising long short-term memory (LSTM) models to predict parameter configurations for material extrusion additive manufacturing (MEX) parts, aiming to meet specific stress–strain requirements. The proposed framework transforms raw tensile test data for LSTM compatibility, yielding a coefficient of determination of 0.8648 and a mean square error of 0.1348 in inverse prediction tasks. Additionally, validation with new data resulted in an error percentage below 2%. Our approach enables the efficient design of customised parts with accurate mechanical properties, reducing the need for extensive experimentation and allowing adaptation to various additive manufacturing processes.

Parametric analysis of 3D printing parameters on stiffness and hysteresis characteristics of pediatric prosthetic foot coupon samples

Background: This research paper presents a comprehensive parametric study that investigates the influence of various 3D printing parameters on the mechanical properties of a pediatric prosthetic keel using coupon samples. Objective: To analyze how 3D printing parameters impact upon on 2 crucial mechanical properties: stiffness and hysteresis. Methods: Key 3D printing parameters including the amount of continuous carbon fiber layers, fiber distribution, and matrix fill pattern, are systematically varied, and mechanically tested through compression to analyze the results. Results: The results demonstrate the substantial impact that printing parameters have on the mechanical characteristics of 3D-printed pediatric prosthetic feet. Notably, the selection of these parameters for the prosthetic keel plays a pivotal role in shaping the overall performance and functionality of the prosthetic foot, emphasizing the need for precise parameter optimization in pediatric prosthetic design, if 3D printing is the manufacturing process. Conclusions: The findings of this study contribute to a better understanding of the manufacturing process for pediatric prosthetic feet via 3D printing and offer valuable insights for optimizing their design. By identifying the ideal combination of 3D printing parameters that yield the desired stiffness and minimize hysteresis, we aim to enhance the performance and comfort of pediatric prosthetic devices, ultimately improving the quality of life for young users.

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.

Micro-thin hydrogel coating integrated in 3D printing for spatiotemporal delivery of bioactive small molecules

Three-dimensional (3D) printing incorporated with controlled delivery is an effective tool for complex tissue regeneration. Here, we explored a new strategy for spatiotemporal delivery of bioactive cues by establishing a precise-controlled micro-thin coating of hydrogel carriers on 3D-printed scaffolds. We optimized the printing parameters for three hydrogel carriers, fibrin cross-linked with genipin, methacrylate hyaluronic acid, and multidomain peptides, resulting in homogenous micro-coating on desired locations in 3D printed polycaprolactone microfibers at each layer. Using the optimized multi-head printing technique, we successfully established spatial-controlled micro-thin coating of hydrogel layers containing profibrogenic small molecules (SMs), Oxotremorine M and PPBP maleate, and a chondrogenic cue, Kartogenin. The delivered SMs showed sustained releases up to 28 d and guided regional differentiation of mesenchymal stem cells, thus leading to fibrous and cartilaginous tissue matrix formation at designated scaffold regionsin vitroandin vivo. Our micro-coating of hydrogel carriers may serve as an efficient approach to achieve spatiotemporal delivery of various bioactive cues through 3D printed scaffolds for engineering complex tissues.

Experimental Investigations of the Influence of Spent Coffee Grounds Content on PLA Based Composite for 3D Printing

Nowadays Fused Deposition Modeling, a widely utilized additive manufacturing technology, is significantly transforming as modern production processes. Beyond basic uses to it role in sustainability, Fused Deposition Modeling offers processing potential for implanting circular economy by reducing virgin materials consumption and enhance the integration of waste food for sustainable 3D printing. This research paper investigated the production of new composite materials based on spent coffee grounds. In addition, PLA and SCG at various contents (0, 3, 5, 10, and 15 wt%) were dried and premixed, then processed into PLA/SCG composite pellets using twin-screw extrusion. These pellets were successfully converted into filaments and subsequently used for 3D printing. The effect of spent coffee grounds in PLA composites was investigated via physical and mechanical analysis of 3D printed samples. Regarding density measurements, results revealed that adding up to 5 wt% of spent coffee grounds increased the density while further additions led to a decrease which due to the printing parameters such as extrusion temperature and nozzle diameter. Considering the mechanical properties, the Young’s modulus increased once the spent coffee grounds content reached 3 wt% and then decreased. In the other hand, there was no enhancement in tensile strength and elongation at break which corroborating with density measurements. This mainly contributed to the changes in mechanical properties caused by printing parameters. This study demonstrates that coffee waste can be used as a filler in environmentally friendly composites for 3D printing, with a maximum SCG content of 15 wt%. This approach not only promotes the reuse of coffee waste but also reduces the cost of traditional PLA filaments.

Experimental study on buildability and mechanical properties of 3D printing cob

The application of 3D printing technology to earth buildings conforms to the development concept of low carbon, green and intelligent construction. The key issue lies in the development of earth material with both favorable buildability and sufficient mechanical properties. In this study, the printing parameters of mixture for 3D printing with different water contents were optimized. The optimum water content of 3D printing cob was determined based on the buildability. The result shows that when the flow spreading diameter is between 140 mm and 160 mm, 3D printing cob has good buildability performance. The optimum water content is 24.6 %. In addition, anisotropic performance was analyzed by compressive strength tests from three orthogonal directions. In particular, according to the test results of single printing limit height and yield stress, the buildability of 3D printing cob wall was analyzed. The building strategy of the printing divided into multiple times was obtained.

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.

A new granule extrusion-based for 3D printing of POE: studying the effect of printing parameters on mechanical properties with “response surface methodology”

A new granule extrusion-based for 3D printing of POE: studying the effect of printing parameters on mechanical properties with “response surface methodology”

Accuracy, Marginal, and Internal Fit of Additively Manufactured Provisional Restorations and Prostheses Printed at Different Orientations.

This systematic review aimed to assess the impact of printing orientation on the accuracy and properties of additively manufactured provisional restorations. A systematic literature search databases (PubMed, Scopus, Web of Science, and Cochrane) were conducted in July 2024 without language restrictions. The included studies were evaluated using the modified CONSORT checklist, and the effect measures and synthetic methods were employed to assess the accuracy of resin provisional restorations printed at various orientations. The web search resulted in 8228 records, and 15 records were ultimately included in the analysis. The printing orientation of provisional restorations has an impact on various factors such as the internal and marginal gap, trueness, precision, and accuracy. To achieve optimal results, it is recommended to utilize printing orientations of 180°, 150°, and 210°, as they showed lower marginal and internal gaps and higher accuracy. Caution should be exercised during the virtual positioning of supporting pillars, as this may also influence the overall accuracy. Horizontally and slightly tilted orientations have demonstrated superior accuracy. To achieve optimal results, factors such as printing layer thickness, printing technology, materials, and supportive pillars should be taken into consideration, besides the printing orientations. The selection of the optimum printing parameters overall printing orientations, layer thickness, and supportive pillar position can generate prosthetic and restorative dental parts with a long survival rate, saving time and effort by avoiding fracture, loss of retention, and consequent clinical complications.

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.

Optimization of hydrogel extrusion printing process parameters based on numerical simulation

The printing quality of biological scaffold is not only affected by the fluidity of bio-ink but also by the printing process parameters, such as the size of the needle, printing height, extrusion speed, and printing speed. Therefore, optimizing the printing process parameters can further improve the molding quality of the biological scaffold. In this study, the printing and deposition process of sodium alginate hydrogel was modeled and analyzed based on the Herschel–Bulkley model by the finite element simulation method. The orthogonal experiment method, control variable method, and response surface method were used to design experiments, and the influences of different printing process parameters on the hydrogel deposition process were investigated. Finally, the optimal combination of printing process parameters was obtained by taking the molding degree and offset of the hydrogel line as optimization objectives. The results show that the strength relationship of the factors affecting the molding degree of the hydrogel line is as follows: printing height > needle diameter > printing speed > extrusion speed, and the strength relationship of the factors affecting the printing offset is as follows: printing height > needle diameter > extrusion speed > printing speed. The optimal combination of printing process parameters is d = 0.34 mm, H = 0.51 mm, v1 = 10 mm/s, and v2 = 7.91 mm/s. Compared with the printing experiment results of the hydrogel line molding degree under the optimal process parameters, the error range is within −11.55%–1.27%, which further demonstrates the reliability of the optimization method of hydrogel extrusion printing process parameters based on numerical simulation and response surface method.

Toward 3D printability prediction for thermoplastic polymer nanocomposites: Insights from extrusion printing of PLA-based systems

The development of new thermoplastic-based nanocomposites for, as well as using, 3D printing requires extensive experimental testing. One typically goes through many failed, or otherwise sub-optimal, iterations before finding acceptable solutions (e.g. compositions, 3D printing parameters). It is desirable to reduce the number of such iterations as well as exclude failed experiments that often require laborious disassembly and cleaning of the 3D printer. This issue could be addressed if we were able to understand, and ultimately predict ahead of experiments if a given material can be 3D printed successfully. Herein, we report on our investigations into forecasting the printing and resultant properties of polymer nanocomposites while encompassing both material properties and printing parameters, enabling the model to generalize across various thermoplastics and additives. To do so, nanocomposites of two different commercially available bio-based PLAs with varying concentrations of nanoclay (NC) and graphene nanoplatelets (GNP) were prepared using a twin-screw extruder. The thermal and rheological properties of the nanocomposites were analyzed. These materials were printed at varying temperature and flow using a pellet printer. The quality of the printing was evaluated by measuring weight fluctuation, internal diameter of cylindrical specimen, and surface uniformity. The interactions between material properties and printing parameters are complex but captured effectively by a machine learning model, specifically we demonstrate such a predictive model to forecast printability and, printing quality utilizing a Random Forest algorithm. Printability was predicted by developing a classification model with constraints based on the weight fluctuation (ΔW) of the printed sample w.r.t. the optimal print; defining “not printable” for −1.0≤ΔW<−0.8 and “printable” for ΔW≥−0.8. The classification model for predicting printability, performed well with an accuracy of 92.8% and identified flow index and complex viscosity, contributing 52% to the model’s importance. Another model to predict ΔW of the only on successful prints also showed strong performance, emphasizing the importance of viscoelastic properties, thermal stability, and printing temperature. For diameter change (ΔDi), the Random Forest model identified flow consistency index, complex viscosity, and thermal stability as influential parameters, with crystallization enthalpy gaining increased importance, reflecting its role in crystallization and shrinkage. In contrast, the surface roughness average (RA) model had lower performance, yet revealed remarkable insights regarding the feature importance with crystallization enthalpy and complex viscosity being most significant.

3D printing of cordierite glass-ceramics

Compared to traditional ceramic materials, glass-ceramics can also exhibit superior properties and are now widely used in cutting-edge national defense industries technology, aerospace, electronics, construction, and other fields. In this study, it is for the first time reported that novel photopolymerization 3D printable slurries using cordierite glass ceramic powder were prepared. The effects of slurry properties and printing process parameters on the warpage of the printed samples were studied. Cordierite glass-ceramic parts fabricated using photopolymerization 3D printing and heat treatment processes were studied to evaluate the effects of sintering parameters on the properties of the samples. The obtained additively manufactured cordierite glass-ceramics exhibit excellent microstructural and mechanical properties, with a maximum bending strength of 181 MPa, an increase of 95.66 % compared to that of the previously reported 3D printed cordierite ceramics. The underlying mechanisms of the glass and ceramic phase characteristics influence the density and the mechanical properties during and after the courses of sintering were also investigated and unveiled in detail. This study provides a viable method for manufacturing complex-shaped cordierite glass-ceramic components using 3D printing.

Effect of printing parameters and triply periodic minimal surfaces on electromagnetic shielding efficiency of polyvinylidene fluoride graphene nanocomposites

Electromagnetic interference (EMI) shielding is vital in safeguarding electronic devices from the harmful effects of external electromagnetic signals, a critical factor in ensuring the reliability and functionality of these systems. EMI, originating from a myriad of sources, can range from causing temporary disruptions to catastrophic system failures and potentially harmful consequences. This study delves into the EMI shielding capabilities of 3D printed Polyvinylidene Fluoride (PVDF)-graphene Triply Periodic Minimal Surface (TPMS) structures, fabricated using Material Extrusion (ME) process. The focus on TPMS structures stems from their unique geometrical configurations, offering promising potentials in enhancing EMI shielding effectiveness. Four distinct TPMS topologies—gyroid, Neovius, diamond, and I-WP were explored, with each demonstrating varying degrees of shielding effectiveness. 3D printed solid samples showed an average specific shielding effectiveness (SSE) of 13dB cm3/g, and Neovius triply periodic minimal surface (TPMS) structure exhibited an average SSE of 94dB cm3/g. Absolute shielding effectiveness (SSE/t) for solid samples and Neovius TPMS structure is around 66dB cm2/g and 62.5dB cm2/g respectively. Among the tested samples, those with a Neovius topology emerged as particularly promising, exhibiting high EMI shielding effectiveness suitable for commercial applications. Furthermore, the study investigates the impact of several design and printing parameters, including relative density/infill percentage, print orientation, and the size of unit cells, on total shielding effectiveness (SET). Results revealed SET variations ranging between 25dB and 75dB, suggesting that tuning the SET of these samples is feasible by adjusting these parameters. The study's findings, highlighting a strong correlation between SET and frequency influenced by unique geometrical characteristics and frequency-dependent interactions, underscore the potential of architected PVDF-graphene TPMS structures in EMI shielding applications. This opens new avenues for research and development in this field, paving the way for more advanced and effective EMI shielding solutions.

High-throughput in-situ mechanical evaluation and parameter optimization for 3D printing of continuous carbon fiber composites

The mechanical properties of carbon fiber reinforced thermoplastic (CFRTP) molded parts produced by thermal fusion lamination 3D printing vary with printing conditions. This study assesses the influence of the 3D printing parameters on the mechanical properties of resulting CFRTP products through parameter evaluation testing. An in-situ three-point bending test mechanism was developed to enhance the efficiency of these tests, allowing the same 3D printer to handle all processes from printing multiple CFRTP specimens simultaneously to conducting a bending test, reducing manual handling time to about one minute. Using this modified 3D printer, 700 specimens with varying printing conditions were produced, and their flexural strength was measured semi-automatically. Results revealed that the flexural strength of the 3D-printed CFRTP object varied with nozzle temperature, printing pitch, and stacking pitch, but not with printing speed. Machine learning was then employed to predict the maximum flexural strength and determine optimal printing parameters using the collected data as training data.

Additive manufacturing of oriented chopped carbon fiber reinforced mullite refractory via extrusion-based technique- Effects of slurry rheological behavior and 3D printing parameters

Additive manufacturing of oriented chopped carbon fiber reinforced mullite refractory via extrusion-based technique- Effects of slurry rheological behavior and 3D printing parameters

Impact of Graphene Nanoparticles on DLP-Printed Parts' Mechanical Behavior

Digital Light Processing (DLP) is one of the most promising techniques among the additive manufacturing (AM) technologies for polymer resin. The polymer parts produced through this technique demonstrate a diverse range of characteristics that can be specifically designed for various fields of application. Specific attributes can be attained by utilizing polymer composites composed of multiple materials in numerous ratios. This research delves into evaluating and comparing different properties, including microstructure, surface texture, and mechanical behavior, of resin-based polymer composites fabricated using the DLP 3D printing technology. To achieve this, specimens have been printed using photopolymer resin as the base material, with varying percentages of graphene nanoparticles added to the resin. Tensile tests and particle analysis based on optical microscope images validate that optimizing parameters, especially the energy setting of the printer, significantly impact the printed samples' strength, surface texture, layering, and microstructure. The findings indicate that at a specific percentage of graphene, such as 0.5%, there is an increase in tensile strength by 38.1%, Young’s modulus by 54.7%, and Yield strength by 11.2%, accompanied by an improved surface roughness. A graphene concentration of 0.75% results in diminished tensile strength, yield strength, and Young’s modulus. The significance of fine-tuning printing parameters to achieve desired properties in resin-based polymer composites manufactured via 3D printing is highlighted.

Automated repair of asphalt pavement cracks and potholes utilizing 3D printing and LiDAR scanning

This study introduces a method for automatic repair of asphalt pavement cracks and potholes using 3D printing and LiDAR scanning. A scanning method was developed to accurately detect and represent cracks and potholes in a 3D model. To address the limitations of LiDAR scanning, such as missing data points caused by the irregular shapes of cracks and potholes, the screened Poisson method was applied to reconstruct the missing data points. These models were validated through both theoretical calculations and sand test. In addition, the research focuses on optimizing key 3D printing parameters, such as printing temperature and printing speed, to enhance performance of crack repair throughout semi-circular bending test. Direct tensile strength test was employed to assess the impact of waste materials (e.g., rubber tire powder and waste glass) on the bond strength of filled sample. The results indicated a volume difference of 2–5 % between the scanning method and the sand test method, demonstrating high accuracy in detecting and reconstructing 3D cracks/potholes. Binders modified with 10 % rubber tire powder, or 20 % waste glass exhibited the highest tensile strength of 212 kPa and 207 kPa, respectively. However, using more than 30 % waste materials is not recommended due to a significant reduction in bond strength compared to conventional binders. An optimal 3D printing speed of 180 mm/min and a temperature of 117 °C are recommended for use in 3D printing in laboratory conditions. It was also noted that higher printing speeds decrease indirect tensile strength, highlighting the importance of balanced parameter settings.

Advancements in Biofiller-Reinforced PLA Composites for 3D Printing: A Review

Additive manufacturing is key in realizing highly complex and high-performance composite materials. Among all the various kinds of functionality that could be added to a composite component, continuous fiber-reinforced composites have been drawing much attention because of their attractive combination of properties. The comprehensive spectrum of knowledge that ranges from the basics concerned with structure, morphology, synthesis, physical, and chemical properties finally reaches to this analytical study of advanced composites. Most generally, such a composite is structured on a thermoplastic or thermoset polymer matrix that embeds the load-carrying reinforcing fibers; probably best known are carbon, glass, and aramid fibers. These composites, which involve fibers continuously reinforcing, have high strength relative to their weight. They are also anisotropic, meaning they have qualities that vary from one direction to another – something which might be customisable for specific load cases. They warp and shrink less during their life in an outside environment than conventionally made bioplastics due to a fact that short fibers can provide reinforcement to them. This 3-D printing object is manufactured by special additive manufacture technology during the manufacturing process after compounding and extruding the fiber-reinforced composite filament. The final properties of 3D printed parts could be tailorable through changing variables such a fiber type, fiber length, volume fraction, polymer matrix material, orientation of fibers, and printing process parameters. These continuous fiber-reinforced 3D printed composites could achieve tensile strengths up to one GPa, have stiffness values reaching even a rating of countless Gpa, and have ad thicknesses in the range from about 1.4–1.8 g/cm³. This finding could be applied in basically all major industries, from aerospace and the automotive industry to sports gear. Such conclusions from the analysis may be useful in the selection of appropriate materials and techniques while even guiding the development of new applications with respect to such advanced composite materials.

Interaction between material and process parameters during 3D concrete extrusion process

Extrusion of cement-based materials in additive manufacturing is influenced by a complex interaction of various material and process parameters. This study aims to investigate the impact of rheological properties and printing parameters on the extrudability of cement-based materials as well as the interaction between rheological properties of print materials and extrusion speed, as a key printing process parameter. 20 different print materials with diverse rheological properties were extruded at 10 different extrusion speeds. The effect of material parameters (i.e. rheological properties) and process parameters (i.e., extrusion speed) and their interaction during the extrusion process were evaluated using filament continuity, conformity and consistency. At a constant printing speed, a higher yield stress adversely impacted filament continuity in mixtures with a yield stress of over 260 Pa, whereas viscosity showed minimal influence on filament quality within the tested range of the rheological properties. The results of this study highlighted a significant correlation between material and process parameters and that adapting process parameters to variations in material properties is crucial for meeting printing criteria. The filament consistency of the mixtures with high yield stress was more sensitive to change in the extrusion speed than that of mixtures with low yield stress. An opposite trend, however, was observed for filament conformity where low yield stress mixtures showed a higher sensitivity to the extrusion speed. A procedure was suggested and applied to determine the optimum extrusion speed. Optimal extrusion speeds enabled printing mixtures with a broader spectrum of rheological properties with an acceptable visual quality, filament conformity and consistency requirements. With extrusion speed adjustment, the extrudability window was expanded from dynamic yield stress of 108–126 Pa to 108–263 Pa and plastic viscosity of 8.2–12.3 Pa.s to 5.1–16.4 Pa.s.