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As newer high performance polymers in mechanical properties become available for material extrusion-based additive manufacturing, determining infill parameter settings becomes more important to achieve both operational and mechanical performance of printed outputs. For the material extrusion of carbon fiber reinforced poly-ether-ether-ketone (CFR-PEEK), this study aims not only to identify the effects of infill parameters on both operational and mechanical performance but also to derive appropriate infill settings through a multicriteria decision-making process considering the conflicting effects.

A full-factorial experimental design to investigate the effects of two major infill parameters (i.e. infill pattern and density) on each performance measure (i.e. printing time, sample mass, energy consumption and maximum tensile load) is separately performed to derive the best infill settings for each measure. Focusing on energy consumption for operational performance and maximum tensile load for mechanical performance, the technique for order preference by similarity to ideal solution is further used to identify the most appropriate infill settings given relative preferences on the conflicting performance measures.

The results show that the honeycomb pattern type with 25% density is consistently identified as the best for the operational performance measures, while the triangular pattern with 100% density is the best for the mechanical performance measure. Moreover, it is suggested that certain ranges of preference weights on operational and mechanical performance can guide the best parameter settings for the overall material extrusion performance of CFR-PEEK.

The findings from this study can help practitioners selectively decide on infill parameters by considering both operational and mechanical aspects and their possible trade-offs.

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.

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.

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.

Material extrusion technology is considered to be an effective way to realize the accurate and integrated manufacturing of high-performance metal diamond tools with complex structures. The present work aims to report the G4 binder that can be used to create metal composite filament loading high concentrations of large diamond particles through comparative experiments.

The quality of filaments was evaluated by surface topography observation and porosity measurement. And the printability of filaments was further studied by the tensile test, rheological test, shear analysis and printing test.

The results show that the G4 binder exhibits the best capacity for loading diamonds among G1–G4. The L4 filament created with G4 has no defects such as pores, cracks and patterns on the surface and section, and has the lowest porosity, which is about 1/3 of the L1. Therefore, the diamond-containing composite filament based on G4 binder exhibits the best quality. On the other hand, the results of the tensile test of L5–L8 filaments reveal that as the diamond content increases from 10% to 30%, the tensile strength of the filament decreases by 29.52%, and the retention force coefficient decreases by 15.74%. This can be attributed to the formation of inefficient bonding areas of the clustered diamond particles inside the composite filament, which also leads to a weakening of the shear strength. Despite this, the results of the printing test show that the diamond-containing composite filament based on the G4 binder has reliable printability.

Therefore, the G4 binder is considered to solve the most critical first challenge in the development of diamond-containing filament.

Regardless of the materials used, additive manufacturing (AM) is one of the most popular emerging fabrication processes used for creating complex and intricate structural components. This study aims to investigate the effects of process parameters – namely, nozzle diameter, layer thickness and infill density on microstructure as well as the mechanical properties of 17–4 PH stainless steel specimens fabricated via material extrusion AM.

The experimental approach investigates the effects of printing parameters, including nozzle diameter, layer thickness and infill density, on surface roughness, physical and mechanical properties of the printed specimens. The tests were triplicated to ensure reproducibility of the experimental results.

The highest ultimate tensile strength, 795.26 MPa, was obtained on specimen that was fabricated with a 0.4 mm nozzle diameter, 0.14 mm layer thickness and 30% infill density. Furthermore, a 0.4 mm nozzle diameter also provided slightly better ductility. This came at the expense of surface finishing, as a 0.25 mm nozzle diameter exhibited better surface finishing over a 0.4 mm nozzle diameter. Infill density was shown to slightly influence the tensile properties, whereas layer thickness showed a significant effect on surface roughness. By contrast, hardness and ductility were independent of nozzle diameter, layer thickness and infill density.

This paper presents a comprehensive analysis relating to various input printing parameters on microstructural, physical and mechanical properties of additively manufactured 17–4 PH stainless steel to improve the printability and processability via AM.

The paper seeks to bridge the already familiar benefits of 3D printing (3DP) to the rehabilitation of cultural heritage, still based on the use of complex and expensive handcrafted techniques and scarce materials.

A compilation of different information on frequent anomalies in cultural heritage buildings and commonly used materials is conducted; subsequently, some innovative techniques used in the construction sector (3DP and 3D scanning) are addressed, as well as some case studies related to the rehabilitation of cultural heritage building elements, leading to a reflection on the opportunities and challenges of this application within these types of buildings.

The compilation of information summarised in the paper provided a clear reflection on the great potential of 3DP for cultural heritage rehabilitation, requiring the development of new mixtures (lime mortars, for example) compatible with the existing surface and, eventually, incorporating some residues that may improve interesting properties; the design of different extruders, compatible with the new mixtures developed and the articulation of 3D printers with the available mapping tools (photogrammetry and laser scanning) to reproduce the component as accurately as possible.

This paper sets the path for a new application of 3DP in construction, namely in the field of cultural heritage rehabilitation, by identifying some key opportunities, challenges and for designing the process flow associated with the different technologies involved.

Understanding the effect of process parameters on interfaces and interfacial bonding between two materials during multi-material additive manufacturing (MMAM) is crucial to the fabrication of high-quality and strong multi-material structures. The purpose of this paper is to conduct an experimental and statistical study to investigate the effect of process parameters of soft and hard materials on the flexural behavior of multi-material structures fabricated via material extrusion-based MMAM.

Sandwich beam samples composed of a soft core and hard shells are fabricated via MMAM under different printing conditions. A design of experiments is conducted to investigate the effect of the print speed and nozzle temperature on the flexural behavior of soft-hard sandwich beams. Analysis of variance and logistic regression analysis are used to analyze the significance of each process parameter. The interfacial morphology of the samples after the flexural tests is characterized. Thermal distributions during the MMAM process are captured to understand the effect of process parameters on the flexural behavior based on inter-bonding formation mechanisms.

Experimental results show that the soft-hard sandwich beams exhibited two different failure modes, including shell failure and interfacial failure. A transition of failure modes from interfacial failure to shell failure is observed as the nozzle temperatures increase. The samples that fail because of interfacial cracking exhibit a pure adhesive failure because of weak interfacial fracture properties. The samples that fail because of shell cracking exhibit a mixed adhesive and cohesive failure. The flexural strength and modulus are affected by the nozzle temperature for the hard material and the print speeds for both hard and soft materials significantly.

This paper first investigates the effect of process parameters for soft and hard materials on the flexural behavior of additively manufactured multi-material structures. Especially, the ranges of the selected process parameters are distinct, and the effect of all possible combinations of the process parameters on the flexural behavior is characterized through a full factorial design of experiments. The experimental results and conclusions of this paper provide guidance for future research on improving the interfacial bonding and understanding the failure mechanism of multi-material structures fabricated by MMAM.