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The purpose of this study is to determine the material extrusion (MEX) printability envelope of a new kind of low-viscosity powder-binder feedstocks using rheological properties.

Formulation of 13 feedstocks (variation of solid loading 60–67 Vol.% and thickening agent proportion 3–15 Vol.%) that were characterized and printed at different temperatures.

Three rheological models were successfully used to define the viscosity envelope, producing stable and defect-free printing. At a shear deformation rate experienced by the feedstock in the nozzle ranging from 100 to 300 s^–1, it was confirmed that metal injection molding (MIM) feedstocks exhibiting a low viscosity between 100 and 150 Pa s could be printed using an extrusion temperature as low as 85 °C.

MEX can be used in synergy with MIM to accelerate mold development for a new injected part or simply as a replacement for MIM when the cost of the mold becomes too high for very small production volumes.

Correlation between the rheological properties of this new generation of low-viscosity feedstocks and MEX printability has been demonstrated for the first time.

Extrusion width, the width of printed filaments, affects multiple critical aspects in mechanical properties in material extrusion additive manufacturing: filament geometry, interlayer load-bearing bonded area and fibre orientation for fibre-reinforced composites. However, this study aims to understand the effects of extrusion width on 3D printed composites, which has never been studied systematically.

Four polymers with and without short-fibre reinforcement were 3D printed into single-filament-wide specimens. Tensile properties, mechanical anisotropy and fracture mechanisms were evaluated along the direction of extruded filaments (F) and normal to the interlayer bond (Z). Extrusion width, nozzle temperature and layer height were studied separately via single-variable control. The extrusion width was controlled by adjusting polymer flow in the manufacturing procedure (gcode), where optimisation can be achieved with software/structure design as opposed to hardware.

Increasing extrusion width caused a transition from brittle to ductile fracture, and greatly reduced directional anisotropy for strength and ductility. For all short fibre composites, increasing width led to an increase in strain-at-break and decreased strength and stiffness in the F direction. In the Z direction, increasing width led to increased strength and strain-at-break, and stiffness decreased for less ductile materials but increased for more ductile materials.

The transformable fracture reveals the important role of extrusion width in processing-structure-property correlation. This study reveals a new direction for future research and industrial practice in controlling anisotropy in additive manufacturing. Increasing extrusion width may be the simplest way to reduce anisotropy while improving printing time and quality in additive manufacturing.

This study aims to develop sweet chestnut incorporated corn-based extrudates by the optimization of process conditions.

The independent process variables for extrusion (blend ratio, barrel temperature, screw speed and feed moisture) were investigated to govern their impact on reliant variables, namely, bulk density, specific mechanical energy, water absorption index, water solubility index, color and hardness. Product and system responses were significantly (p < 0.05) affected by the independent variables. Experimental design with quadratic models experienced a high coefficient of determination (R² = 0.99).

Numerical optimization for the development of extrudates resulted in optimum conditions having corn flour: sweet chestnut flour (80:20), barrel temperature (120°C), screw speed (340 rpm) and feed moisture (12%). Fat, moisture and protein contents of the developed extrudates using optimum conditions were significantly (p < 0.05) lower compared to raw materials – corn and sweet chestnut. The packaging of extrudates in aluminum laminates revealed shelf stability of three months at room temperature without deterioration of quality.

Nutritionally rich sweet chestnut extruded products would be an exclusive option to already existing snacks in the market and can facilitate a new sphere in extruded product sector.

This paper aims to understand the effect of extrusion conditions on the degree of foaming of polylactic acid (PLA) during three-dimensional (3D) printing. It was also targeted to optimize the slicing parameters for 3D printing and to study how the properties of printed parts are influenced by the extrusion conditions.

This study used a commercially available PLA filament that undergoes chemical foaming. An extrusion 3D printer was used to produce individual extrudates and print samples that were characterized using an optical microscope, scanning electron microscope and custom in-house apparatuses.

The degree of foaming of the extrudates was found to strongly depend on the extrusion temperature and the material feed speed. Higher temperatures significantly increased the number of nucleation sites for the blowing agent as well as the growth rate of micropores. Also, as the material feed speed increased, the micropores were allowed to grow bigger which resulted in higher degrees of foaming. It was also found that, as the degree of foaming increased, the porous parts printed with optimized slicing parameters were lightweight and thermally less conductive.

This study fills the gap in literature where it examines the foaming behavior of individual extrudates as they are extruded. By doing so, this work distinguishes the effect of extrusion conditions from the effect of slicing parameters on the foaming behavior which enhances the understanding of extrusion of chemically foamed PLA.

The purpose of this article was to highlight the various methods of extrusion technologies for encapsulation of bioactive components (BACs).

BACs provide numerous health-care benefits; however, downsides, including a strong effect of organoleptic properties by reason of the bitterness and acridity of a few components, and also a short shelf-life, limit their application in food. The food industry is still demanding complicated qualities from food ingredients, which were often impossible to obtain without encapsulation such as stability, delayed release, thermal protection and an acceptable sensory profile. Various techniques such as melt injection extrusion, hot-melt extrusion, electrostatic extrusion, co-extrusion and particles from gas-saturated solutions, could be used for maintaining these characteristics.

Extrusion technology has been well used for encapsulation of bioactive chemicals in an effort to avoid their numerous downsides and to boost their use in food. The count of BACs that could be encapsulated has risen owing to the extrusion technology just as form of encapsulation. Extrusion technique also aids in the devaluation of the fragment size of encapsulated BACs, allowing for greater application in the food business.

The study reported that encapsulating BACs makes them more stable in both the product itself and in the gastrointestinal tract, so using encapsulated BACs would result in a product with stronger preventive properties.

Fused Filament Fabrication (FFF) is an extrusion-based manufacturing process using fused thermoplastics. Despite its low cost, the FFF is not extensively used in high-value industrial sectors mainly due to parts' anisotropy (related to the deposition strategy) and residual stresses (caused by successive heating cycles). Thus, this study aims to investigate the process improvement and the optimization of the printed parts.

In this work, a meshless technique – the Radial Point Interpolation Method (RPIM) – is used to numerically simulate the viscoplastic extrusion process – the initial phase of the FFF. Unlike the FEM, in meshless methods, there is no pre-established relationship between the nodes so the nodal mesh will not face mesh distortions and the discretization can easily be modified by adding or removing nodes from the initial nodal mesh. The accuracy of the obtained results highlights the importance of using meshless techniques in this field.

Meshless methods show particular relevance in this topic since the nodes can be distributed to match the layer-by-layer growing condition of the printing process.

Using the flow formulation combined with the heat transfer formulation presented here for the first time within an in-house RPIM code, an algorithm is proposed, implemented and validated for benchmark examples.

Material extrusion is one of the most commonly used approaches within the additive manufacturing processes available. Despite its popularity and related technical advancements, process reliability and quality assurance remain only partially solved. In particular, the surface roughness caused by this process is a key concern. To solve this constraint, experimental plans have been exploited to optimize surface roughness in recent years. However, the latter empirical trial and error process is extremely time- and resource consuming. Thus, this study aims to avoid using large experimental programs to optimize surface roughness in material extrusion.

This research provides an in-depth analysis of the effect of several printing parameters: layer height, printing temperature, printing speed and wall thickness. The proposed data-driven predictive modeling approach takes advantage of Machine Learning (ML) models to automatically predict surface roughness based on the data gathered from the literature and the experimental data generated for testing.

Using ten-fold cross-validation of data gathered from the literature, the proposed ML solution attains a 0.93 correlation with a mean absolute percentage error of 13%. When testing with our own data, the correlation diminishes to 0.79 and the mean absolute percentage error reduces to 8%. Thus, the solution for predicting surface roughness in extrusion-based printing offers competitive results regarding the variability of the analyzed factors.

There are limitations in obtaining large volumes of reliable data, and the variability of the material extrusion process is relatively high.

Although ML is not a novel methodology in additive manufacturing, the use of published data from multiple sources has barely been exploited to train predictive models. As available manufacturing data continue to increase on a daily basis, the ability to learn from these large volumes of data is critical in future manufacturing and science. Specifically, the power of ML helps model surface roughness with limited experimental tests.

This paper aims to address the development and implementation of “AltPrint,” a slicing algorithm based on a new filling process planning from a variation in the deposited material geometry. AltPrint enables changes in the extruded material flow toward local variations in stiffness. The technical feasibility evaluation was conducted experimentally by fused filament fabrication (FFF) process of snap-fit subjected to a mechanical cyclical test.

The methodology is based on the estimation of the parameter E from the mathematical relationships among the variation of the material in the material flow, nozzle geometry and extrusion parameters. Calibration, validation and analysis of the printed specimens were divided into two moments, of which the first refers to the material responses (flexural and dynamic mechanical analysis) and the second involves the analysis of the printed components with localized flow properties (for estimating the response to cyclic loading). Finite element analysis assisted in the comparison of two snap-fit geometries, one traditional and one generated by AltPrint. Finally, three examples of compliant mechanisms were developed to demonstrate the potential of the algorithm in the generation of functional prototypes.

The contribution of AltPrint is the variable fill width integrated with the slicing software that varies the print parameters in different regions of the object. The alternative extrusion method based on material rate variation was conceived as an “open software” available in GitHub platform, hence, open manufacturing with initial focus on desktop 3D printer based on FFF. The slicing method provides deposited variable-width segments in an organized and replicable filling strategy, resulting in mechanical properties variations in specific regions of a part. It was implemented and evaluated experimentally and indicated potential applications in parts manufactured by the additive process based on extrusion, which requires local flexibilities.

This paper presents a new alternative method for application in an open additive manufacturing context, specifically for additive extrusion techniques that enable local variations in the material flow. Its potential for manufacturing functional parts, which require flexibility due to cyclic loading, was demonstrated by fabrication and experimental evaluations of parts made in acrylonitrile butadiene styrene filament. The changes proposed by AltPrint enable geometric modifications in the response of the printed parts. The proposed slicing and filling control of parameters is inserted in a context of design for additive manufacturing and shows great potential in the area of product design.

The purpose of this study was to fabricate silicone products that had different hardnesses and moduli, thus partially addressing the limitations of homogeneous materials whose deformation depends on altered structure or dimensions, and to provide new dimensions for the design of silicone soft structures.

A soft material three-dimensional printing platform with a dual-channel printing capability was designed and built. Using the material extrusion method, material screening was first performed using single-channel printing, followed by dual-channel-regulated printing experiments on products having different hardness and modulus values.

The proportion of additives has an effect on the accuracy of the printed product. Material screening revealed that Sylgard 527 and SE 1700 could be printed without additives. The hardness and mechanical properties of products are related to the percentage in their composition of hard and soft materials. The hardness of the products could be adjusted from 26A to 42A and the Young’s modulus from 0.875 to 2.378 Mpa.

Existing silicone products molded by casting or printing are mostly composed of a single material, whose uniform hardness and modulus cannot meet the demand for differentiated deformation in the structure. The existing multihardness silicone material printing method has the problems of long material mixing time and slow hardness switching and complicated multi-extrusion head switching. In this study, a simple, low-cost and responsive material extrusion-based hardness programmable preparation method for silicone materials is proposed.

In pursuit of affordable and nutrient-rich food alternatives, the symbiotic culture of bacteria and yeast (SCOBY) emerged as a selected food ink for 3D printing. The purpose of this paper is to harness SCOBY’s potential to create cost-effective and nourishing food options using the innovative technique of 3D printing.

This work presents a comparative analysis of the printability of SCOBY with blends of wheat flour, with a focus on the optimization of process variables such as printing composition, nozzle height, nozzle diameter, printing speed, extrusion motor speed and extrusion rate. Extensive research was carried out to explore the diverse physical, mechanical and rheological properties of food ink.

Among the ratios tested, SCOBY, with SCOBY:wheat flour ratio at 1:0.33 exhibited the highest precision and layer definition when 3D printed at 50 and 60 mm/s printing speeds, 180 rpm motor speed and 0.8 mm nozzle with a 0.005 cm³/s extrusion rate, with minimum alteration in colour.

Food layered manufacturing (FLM) is a novel concept that uses a specialized printer to fabricate edible objects by layering edible materials, such as chocolate, confectionaries and pureed fruits and vegetables. FLM is a disruptive technology that enables the creation of personalized and texture-tailored foods, incorporating desired nutritional values and food quality, using a variety of ingredients and additions. This research highlights the potential of SCOBY as a viable material for 3D food printing applications.