Search results

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 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.

Material extrusion additive manufacturing, also known as fused deposition modeling, is a manufacturing technique in which objects are built by depositing molten materials layer-by-layer through a nozzle. The use and application of this technique has risen dramatically over the past decade. This paper aims to first, report on the production and characterization of a shape memory polymer material filament that was manufactured to print shape memory polymer objects using material extrusion additive manufacturing. Additionally, it aims to investigate and outline the effects of major printing parameters, such as print orientation and infill percentage, on the elastic and mechanical properties of printed shape memory polymer samples.

Infill percentage was tested at three levels, 50, 75 and 100 per cent, while print orientation was tested at four different angles with respect to the longitudinal axis of the specimens at 0°, 30°, 60° and 90°. The properties examined were elastic modulus, ultimate tensile strength and maximum strain.

Results showed that print angle and infill percentage do have a significant impact on the manufactured test samples.

Findings can significantly influence the tailored design and manufacturing of smart structures using shape memory polymer and material extrusion additive manufacturing.

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 study presents a method for fabricating multi-material objects using a hybrid additive and subtractive approach. By hybridizing the material composition in addition to the fabrication process, functional requirements can be met more effectively than through homogenous material parts produced using a single manufacturing process. Development of multi-material objects consisting of dissimilar materials that have been hampered by a lack of a structural interface compatible with in-envelope hybrid additive and subtractive manufacturing.

This research presents a novel method for producing multi-material components through in-envelope hybrid additive and subtractive manufacturing. This study attempts to address the absence of a metal-polymer interface by integrating polymer additive manufacturing into a five-axis mill. The ability of the polymer additive system to reproduce overhang geometries is assessed with different levels of cooling. The relationship between structural performance, cooling and material flow rate is evaluated for the deposited carbon fiber reinforced acrylonitrile butadiene styrene.

A mechanically interlocking root structure is developed to form an interface between a machined aluminum region and a polymer region of an object. The tensile strength of the metal-polymer object is measured and found to be on the same order of magnitude as the bulk three-dimensional printed polymer.

By targeting the material properties to the local functional requirements within a part and taking advantage of both additive and subtractive manufacturing processes, this study will enable broader design options and optimization of performance metrics.

This paper aims to present a survey concerning the accuracy of thermoplastic polymeric parts fabricated by additive manufacturing (AM). Based on the scientific literature, the aim is to provide an updated map of trends and gaps in this relevant research field. Several technologies and investigation methods are examined, thus giving an overview and analysis of the growing body of research.

Permutations of keywords, which concern materials, technologies and the accuracy of thermoplastic polymeric parts fabricated by AM, are used for a systematic search in peer-review databases. The selected articles are screened and ranked to identify those that are more relevant. A bibliometric analysis is performed based on investigated materials and applied technologies of published papers. Finally, each paper is categorised and discussed by considering the implemented research methods.

The interest in the accuracy of additively manufactured thermoplastics is increasing. The principal sources of inaccuracies are those shrinkages occurring during part solidification. The analysis of the research methods shows a predominance of empirical approaches. Due to the experimental context, those achievements have consequently limited applicability. Analytical and numerical models, which generally require huge computational costs when applied to complex products, are also numerous and are investigated in detail. Several articles deal with artificial intelligence tools and are gaining more and more attention.

The cross-technology survey on the accuracy issue highlights the common critical aspects of thermoplastics transformed by AM. An updated map of the recent research literature is achieved. The analysis shows the advantages and limitations of different research methods in this field, providing an overview of research trends and gaps.

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.

3D printing techniques such as material extrusion based additive manufacturing provide a promising and cost effective manufacturing technique. However, the main challenges in industrial applications remain with the quality assurance of mass produced parts. The purpose of this study is to investigate the effect of compression moulding as a rapid consolidation method for 3D printed composites, with an aim to reduce voids and defects and thus improving quality assurance of printed parts.

To develop an understanding of the inherent voids in 3D parts and the influence on mechanical properties, material extrusion additively manufactured (MEX) parts were post consolidated by using compression moulding at elevated temperature.

This study comparatively investigates the influence of carbon fibre length, undergoing process induced scission during filament extrusion and IM and its impact on void content and mechanical properties. It was found that the post consolidation significantly reduced the voids and the mechanical properties were significantly improved compared to the nonconsolidated material extrusion additively manufactured parts, reaching values similar to those of the IM parts.

Adaptation of extrusion-based additive manufacturing with hybridisation of reliable compression moulding technology transcends into series production of highly adaptive end user applications, such as drones, advanced sports prosthetics, competitive cycling and more.

This paper adds to the current understanding of 3D printing and provides a step towards quality assurance for mass production.

The purpose of this paper is to review research studies on process optimisation and machine development that lead to the enhancement of final products in various aspects of the fused deposition modelling (FDM) process.

An overview of the literature, focussing on process parameters, machine developments and material characterisations. This study investigates recent research studies that studied FDM capabilities in printing a vast range of materials from thermoplastics to metal alloys.

FDM is one of the most common techniques in additive manufacturing (AM) processes. Many parameters in this technology have effects on three-dimensional printed products. Therefore, it is necessary to obtain the optimum elements, for example, build orientation, layer thickness, nozzle diameter, infill pattern and bed temperature. By selecting a proper variable range of parameters, the layers adhere strongly and building end-use products of high quality are achievable. A vast range of materials and their properties from polymers to composite-based polymers are presented. Novel techniques to print metal alloys and composites are examined to increase the productivity of the FDM process. Additionally, defects such as shrinkage and warpage are discussed to eliminate the system’s limitations and improve the quality of final products. Multi-axis and mobile machines brought enhancements throughout the process to eliminate obstacles such as staircase defects in the conventional FDM process. In brief, recent developments were identified and a summary of major improvements was discussed in this study for future research.

This paper is an overview that provides information about research and developments in FDM. This review focusses on process optimisation and obstacles in printing polymers, composites, geopolymers and novel materials. Therefore, machine characteristics were examined to find out the accessibility of printing novel materials for different applications.

This study aims to investigate the material extrusion additive manufacturing (MEAM) deposition parameters for creating viable 3-D printed polyvinylidene fluoride (PVDF) structures with a balanced mix of mechanical and electrical properties.

Different combinations of deposition conditions are tested, and the influence of these parameters on the final dimensional accuracy, semi-crystalline phase microstructure and effective mechanical strength of MEAM homopolymer PVDF printed parts is experimentally assessed. Considering printed part integrity, appearance, print time and dimensional accuracy, MEAM parameters for PVDF are suggested.

A range of viable printing parameters for MEAM fabricated PVDF Kynar 740 objects of different heights and in-plane length dimensions was determined. For PVDF structures printed under the suggested conditions, the mechanical response and the microstructure development related to Piezoelectric response are reported.

This research first reports on a range of parameters that have been confirmed to facilitate effective MEAM printing of 3-D PVDF objects, presents effects of the individual parameters and gives the mechanical and microstructure properties of PVDF structures fabricated under the suggested deposition conditions.