Material Extrusion Additive Manufacturing

The sustainability of additive manufacturing (AM) has attracted attention nowadays, with different aspects needed to be considered. A key effort in this direction is the replacement of fossil fuel–originating polymers with biologically derived polymers. To achieve this, biologically derived polymers should exhibit a performance similar to that of commonly used polymers. Bacterially produced pure polyhydroxyalkanoate (PHA) was recently proposed by filament vendors for material extrusion (MEX) AM. Despite extensive research on the utilization of PHA in polymeric blends, the literature on the printability metrics of pure PHA is limited. At the same time, it has a high potential as an alternative to common petrochemical polymers. In this study, the impact of the main generic settings on the mechanical response of pure bio-sourced PHA in MEX AM was investigated. Four critical 3D printing parameters (print speed, layer height, nozzle temperature, and strand width) were evaluated using a robust design to optimize the tensile and impact metrics. Regression modeling was performed, and predictive equations were compiled and verified using validation testing. The quality of the samples was evaluated using electron microscopy. The analysis proved the importance of layer thickness in the tensile score, whereas nozzle temperature was found to be the most influential setting for impact loading. An increase of approximately 20% can be achieved by selecting appropriate 3D printing settings in the tensile test, whereas the impact strength can be radically improved by up to 550%.Graphical

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes

Among all the additive manufacturing (AM) technologies, the material extrusion-based AM is the most popular, and widely used for prototyping, rapid tooling, and direct part production in the current scenario. In material extrusion AM (MEAM), a solid form of material is converted to a semi-molten form and extruded out of a nozzle to deposit in a layer-by-layer manner. Nowadays MEAM three-dimensional (3D) printers are very popular among different application sectors. This motivates us to develop various commercial as well as open-source entry-level 3D printers such as the development of filament extruder 3D printers, pellet extruder 3D printer, or a combination of both. However, to develop or operate these printers, preliminary knowledge of various extrusion parameters is required to obtain the desired quality in the fabricated parts. Therefore, an initial attempt has been made to provide information related to various extrusion parameters such as definition, working range, and the effect of these parameters on performance measured. The impact of process parameters on the performance of either filament extrusion AM or pellet/granules extrusion AM has only been investigated in the studies available in the literature. However, this study provides a comprehensive review of the effects of process parameters on performance measurements for both types of extrusion-based AM processes. In this research work, along with a detailed review of previous works, a study of various process parameters, modeling, and methodology has been provided. The statistical modeling approach, histogram normal plots have been provided along with mean, standard deviation, and percentage to decide the optimum process parameters based on data available in the existing literature.

Shrinkage evaluation and geometric accuracy assessment on 17–4 PH samples made by material extrusion additive manufacturing

Development of an architecture-property model for triply periodic minimal surface structures and validation using material extrusion additive manufacturing with polyetheretherketone (PEEK)

Graphene is emerging as an excellent material choice for high-performance electrical and electrochemical devices such as humidity sensors. The rapid technological evolution in additive manufacturing (AM) enables freedom to design and process multiple materials for scalable fabrication of sensors. Herein, we introduce a hybrid AM approach to fabricate a graphene-based humidity sensor and study its sensing performance. A powder-bed binder-jetting AM technique is used to build a porous 3D-structure of thermally reduced graphene oxide as the humidity sensing element. In parallel, a material extrusion AM approach is used to make a silicone-based hollow cube as the housing of the graphene structure. The AM fabricated sensor shows high sensitivity when tested in the relative humidity (RH) range of 6.4–97.3% with a rapid response time of 7 s at 45% RH due to the open porous structure formed by the binder-jetting approach. Sensing performance was investigated at low and medium RH in the temperature range of 25–80 °C and the device demonstrated a negligible temperature dependence. The presented graphene-based humidity sensor also shows good repeatability in RH measurements.

Characterization of mechanical properties and fracture mode of additively manufactured carbon fiber and glass fiber reinforced thermoplastics

Digital manufacturing techniques, such as computer numerically controlled (CNC) machining and additive manufacturing (AM), have greatly increased the design space available to engineers with respect to both geometry and materials. Obviously, certain geometries cannot be realized by anything other than a layer-by-layer AM process, and certain materials can only be formed using traditional subtractive approaches, leaving designers with little choice. However, for the wide array of structures that could be realized in a variety of different ways, the choice of manufacturing process is just another faction in the overall design process. Planar lattice structures have complex repeating geometric features which are best designed using computer aided design (CAD) tools, and these structures can easily be manufactured using a variety of different digital manufacturing processes. For this study a set of planar lattice structures were designed and fabricated from acrylonitrile butadiene styrene (ABS) plastic using both a CNC milling machine and a material extrusion AM machine. All test lattices were then loaded in tension to failure to determine their mechanical performance. The determined properties were then compared to analytical predictions from the literature, and an analysis of the impact of a chosen manufacturing process was performed. The results obtained show good agreement with publish models for lattice performance, and additionally suggest that the choice of manufacturing process has a measurable effect on the mechanical performance of the resulting structures for this specific material and geometry combination, but it is important to note that this study is just an example of how to mitigate the uncertainties associated with the freedoms offered by advanced manufacturing processes, and more work in needed in this important area of study.

A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Purpose Fibre-reinforced polymers offer enhanced in-plane mechanical properties in material extrusion (MEX) additive manufacturing, expanding its applicability. However, fibres have minimal impact on the mechanical properties in the build direction, limiting the industrial applications of MEX. This study aims to propose a novel method using a customised toolpath to enhance the interlayer mechanical properties of carbon fibre-reinforced nylon 6 (CF-PA6) structures in an easily accessible manner, requiring no hardware modifications. Design/methodology/approach The customised toolpath discretises the continuous bead into sub-sections and implements periodic vertical toolhead movement during fabrication. Three bead width configurations of MEX-fabricated CF-PA6 specimens were investigated using microscopy, thermal analysis and mechanical performance assessment. Findings In all configurations, the customised toolpath outperformed the conventional toolpath, showing significant increases in ultimate tensile strength (238%–513%), failure strain (70%–349%) and modulus (71%–164%). The main factors contributing to these improvements were found to be redistribution of fibre orientation and thermal effects. In addition, the enhancements became more pronounced as the print width increased. Originality/value This novel fabrication method improves the interlayer mechanical properties of CF-PA6 through software modifications alone. To the best of the authors’ knowledge, this approach has not been demonstrated on fibre-reinforced materials and may enable printing of high-performance polymers on less capable MEX printers.

For the last few decades, the rapid growth of Additive Manufacturing (AM) technologies has been seeable. It is expected to keep maturing continuously due to its advantages compared to conventional manufacturing technologies: flexibility, reliability, energy consumption, and material efficiency. This research article addresses the development and production of a stapler using the Material Extrusion AM process. It is intended to show the development steps to redesign an everyday stapler, into an added-value tool, from the selection and fixture of the CAD model and generative design through Fusion 360 to its optimization on nTopology, simulation, and plot of the part in Eiger.

Acrylonitrile styrene acrylate (ASA) is increasingly popular among traditional engineering polymers for material extrusion (MEX) additive manufacturing (AM). Satisfactory printability and engineering metrics and excellent stability in hard environmental conditions explain this status. To achieve the highest possible performance levels, the optimization of the generic printing control settings is critical. This paper focuses on delivering enhanced mechanical and morphological characteristics when printing with ASA. To meet these goals, an L25 orthogonal robust design was compiled and executed, enabling the simultaneous assessment of six (6) control parameters, i.e., the strand width (SW), infill orientation (angle) (AINF), layer thickness (TL), printing speed (PS), nozzle temperature (TN), and bed temperature (TB). A massive experimental course with two hundred and ninety specimens was engaged to deliver response metrics, such as tensile ultimate strength (σBT), tensile yield strength (σBY), tensile modulus of elasticity (ET), flexural strength (σBF), and flexural modulus of elasticity (EF). Three modeling methods were applied to compare their efficacy in these loading scenarios: the Reduced Quadratic Regression Model (RQRM), Linear Regression Model (LRM), and Quadratic Regression Model (QRM). RQRM and QRM achieved similar prediction accuracies, whereas LRM yielded poorer predictive results than the other methods. Confirmation runs validated the validity of the compiled prediction functions, thereby making them suitable for direct industrial use. The most influential parameter was the AINF. The optimized 3D printing settings improved all mechanical performance metrics by more than 40%, while the flexural strength was improved by more than 60%.

Local characterization of stainless steel 17-4PH produced by material extrusion additive manufacturing: Influence of the post-treatment

Scalable, flexible and resilient parallelization of fused filament fabrication: Breaking endemic tradeoffs in material extrusion additive manufacturing