Search results

This paper aims to investigate the feasibility of supportless printing of lattice structures by metal fused filament fabrication (MF³) of Ti-6Al-4V. Additionally, an empirical method was presented for the estimation of extrudate deflection in unsupported regions of lattice cells for different geometric configurations.

Metal-polymer feedstock with a solids-loading of 59 Vol.% compounded and extruded into a filament was used for three-dimensional printing of lattice structures. A unit cell was used as a starting point, which was then extended to multi-stacked lattice structures. Feasible MF³ processing conditions were identified to fabricate defect-free lattice structures. The effects of lattice geometry parameters on part deflection and relative density were investigated at the unit cell level. Computational simulations were used to predict the part quality and results were verified by experimental printing. Finally, using the identified processing and geometry parameters, multi-stacked lattice structures were successfully printed and sintered.

Lattice geometry required considerable changes in MF³ printing parameters as compared to printing bulk parts. Lattice cell dimensions showed a considerable effect on dimensional variations and relative density due to varying aspect ratios. The experimental printing of lattice showed large deflection/sagging in unsupported regions due to gravity, whereas simulation was unable to estimate such deflection. Hence, an analytical model was presented to estimate extrudate deflections and verified with experimental results. Lack of diffusion between beads was observed in the bottom facing surface of unsupported geometry of sintered unit cells as an effect of extrudate sagging in the green part stage. This study proves that MF³ can fabricate fully dense Ti-6Al-4V lattice structures that appear to be a promising candidate for applications where mechanical performance, light-weighting and design customization are required.

Supportless printing of lattice structures having tiny cross-sectional areas and unsupported geometries is highly challenging for an extrusion-based additive manufacturing (AM) process. This study investigated the AM of Ti-6Al-4V supportless lattice structures using the MF³ process for the first time.

Recently, the constrained surface projection stereolithography (SL) technology is gaining wider attention and has been widely used in the 3D printing industry. In constrained surface projection SL systems, the separation of a newly cured layer from the constrained surface is a historical technical barrier. It greatly limits printable size, process reliability and print speed. Moreover, over-large separation force leads to adhesion failures in manufacturing processes, causing broken constrained surface and part defects. Against this background, this paper investigates the formation of separation forces and various factors that affect the separation process in constrained surface projection SL systems.

A bottom-up projection SL testbed, integrated with an in-situ separation force measurement unit, is developed for experimental study. Separation forces under various manufacturing process settings and constrained surface conditions are measured in situ. Additionally, physical models are constructed by considering the liquid resin filling process. Experiments are conducted to investigate influences of manufacturing process settings, constrained surface condition and print geometry on separation forces.

Separation forces increase linearly with the separation speed. The deformation and the oxygen inhibition layer near the constrained surface greatly reduce separation forces. The printing area, area/perimeter ratio and the degree of porousness of print geometries have a combined effect on determining separation forces.

This paper studied factors that influence separation force in constrained surface SL processes. Constrained surface conditions including oxygen inhibition layer thickness, deformation and oxygen permeation capability were investigated, and their influences on separation forces were revealed. Moreover, geometric factors of printing layers that are significant on determining separation forces have been identified and quantified. This study on separation forces provides a solid base for future work on adaptive control of constrained surface projection SL processes.

This study aims to design a novel strategy to avoid thermal defects in three-dimensional (3D) printing processes. A combination of subroutines and utility routines allows for in situ variations of the key process parameters (KPP) in the thermal simulation and produces by post-processing the output an updated machine code for enhanced quality of the printed part in a single iteration.

The input data for the thermal simulation were obtained by characterising an acrylonitrile butadiene styrene filament and calibrating an Ultimaker S5 printer. Abaqus subroutines were used to accurately simulate the continuous deposition of molten material. A utility routine extracted the nodal temperatures during simulation and detected regions that were prone to overheating. We developed a method, enabling the introduction of variable process parameters in the thermal simulation and validated it by printing several test geometries.

The results of the thermal simulation indicate that decreasing the print speed enhances the amount of heat dissipated to the environment. Therefore, it is an efficient way to avoid overheating of the printed geometry. The validation geometries showed improvements when adapting the print speed.

This approach is the first to demonstrate the potential of variable process parameters using implemented routines in the thermal process simulation. Here, the focus is on predicting and avoiding thermal hotspots. However, more potential can be obtained by enabling the prediction and adaptation of KPP to ensure mechanical performance. This would be an alternative way to tackle the cost- and time-inefficient post-processing of 3D-printed parts.

This paper aims to develop experimentally validated numerical models to accurately characterize the cross-sectional geometry of the deposited beads in a fused filament fabrication (FFF) process under various process conditions.

The presented numerical model is investigated under various fidelity with varying computational complexity. To this end, comparisons between the Newtonian, non-newtonian, isothermal and non-isothermal computational models are presented for the extrusion of polylactic acid material in an FFF process. The computational model is validated through an experimental study on an off-the-shelf FFF printer. Microscope images of experimentally printed FFF bead cross-sections corresponding to various printing conditions are digitally processed for the validation. In the experimental study, common practical printing conditions for an FFF process are tested, and the results are compared to the numerical model.

Microscope image analyses of the cross-sectional geometries of deposited beads show that the numerical model provides a precise characterization of the cross-sectional geometry under varying process parameters in terms of the cross-section outline, bead height and width. The results show that the nozzle-to-table distance has a great effect on the bead shape when compared to the extrusion rate at a given nozzle-to-table distance. Comparison of the various computational models show that the non-Newtonian isothermal model provides the best tradeoff between computational complexity and model accuracy.

The authors provide detailed computational models, including the extruder nozzle geometry for cases ranging from Newtonian isothermal models to non-Newtonian non-isothermal models with experimental validation. The validation study is conducted for practical process parameters that are commonly used in FFF in practice and show that the computational models provide an accurate depiction of the true process outputs. As the developed models can accurately predict process outputs, they can be used in further applications for process planning and parameter tuning.

This study aims at compensating for sintering deformation of components manufactured by metal binder jetting (MBJ) technology.

In the present research, numerical simulations are used to predict sintering deformation. Subsequently, an algorithm is developed to counteract the deformations, and the compensated deformations are morphed into a CAD model for printing. Several test cases are designed, compensated and manufactured to evaluate the accuracy of the compensation calculations. A consistent accuracy measurement method is developed for both green and sintered parts. The final sintered parts are compared with the desired final shape, and the accuracy of the model is discussed. Furthermore, the effect of initial assumptions in the calculations, including green part densities, and green part dimensions on the final dimensional accuracy are studied.

The proposed computational framework can compensate for the sintering deformations with acceptable accuracy, especially in the directions, for which the used material model has been calibrated. The precise assumption of green part density values is important for the accuracy of compensation calculations. For achieving tighter dimensional accuracy, green part dimensions should be incorporated into the computational framework.

Several studies have already predicted sintering deformations using numerical methods for MBJ parts. However, very little research has been dedicated to the compensation of sintering deformations with numerical simulations, and to the best of the best of the authors' knowledge, no previous work has studied the effect of green part properties on dimensional accuracy of compensation calculations. This paper introduces a method to omit or minimize the trial-and-error experiments and leads to the manufacturing of dimensionally accurate geometries.

Mechanical anisotropy associated with material extrusion additive manufacturing (AM) complicates the design of complex structures. This study aims to focus on investigating the effects of design choices offered by material extrusion AM – namely, the choice of infill pattern – on the structural performance and optimality of a given optimized topology. Elucidation of these effects provides evidence that using design tools that incorporate anisotropic behavior is necessary for designing truly optimal structures for manufacturing via AM.

A benchmark topology optimization (TO) problem was solved for compliance minimization of a thick beam in three-point bending and the resulting geometry was printed using fused filament fabrication. The optimized geometry was printed using a variety of infill patterns and the strength, stiffness and failure behavior were analyzed and compared. The bending tests were accompanied by corresponding elastic finite element analyzes (FEA) in ABAQUS. The FEA used the material properties obtained during tensile and shear testing to define orthotropic composite plies and simulate individual printed layers in the physical specimens.

Experiments showed that stiffness varied by as much as 22% and failure load varied by as much as 426% between structures printed with different infill patterns. The observed failure modes were also highly dependent on infill patterns with failure propagating along with printed interfaces for all infill patterns that were consistent between layers. Elastic FEA using orthotropic composite plies was found to accurately predict the stiffness of printed structures, but a simple maximum stress failure criterion was not sufficient to predict strength. Despite this, FE stress contours proved beneficial in identifying the locations of failure in printed structures.

This study quantifies the effects of infill patterns in printed structures using a classic TO geometry. The results presented to establish a benchmark that can be used to guide the development of emerging manufacturing-oriented TO protocols that incorporate directionally-dependent, process-specific material properties.

The purpose of this paper is to understand the relationship between defect properties and the tool path used for generating additively manufactured parts. The correlation between processing strategy and porosity architecture is one of the key aspects for a precise understanding of defect formation and possibilities for defect reduction.

The authors present a new combined geometry, processing path and porosity analysis procedure based on the use of x-ray computed micro tomography image data and numerical control programming code. The procedure allows for a covisualisation of the track of the respective processing head with the three-dimensional microstructure data.

The presented method yields statistical results about defect distribution and morphologies introduced by the respective process characteristics in parts. The functionality of the proposed procedure is demonstrated on an aluminum (AlSi10Mg) and a polylactide test sample to show the additional insight found for both additive manufacturing processes and the resulting microstructural properties.

The novelty of this paper is the analysis of the porosity with respect to the underlying additive process zone and the sample geometry.

Fused Filament Fabrication (FFF) is one of the growing technologies in additive manufacturing, that can be used in a number of applications. In this method, process parameters can be customized and their simultaneous variation has conflicting impacts on various properties of printed parts such as dimensional accuracy (DA) and surface finish. These properties could be improved by optimizing the values of these parameters.

In this paper, four process parameters, namely, print speed, build orientation, raster width, and layer height which are referred to as “input variables” were investigated. The conflicting influence of their simultaneous variations on the DA of printed parts was investigated and predicated. To achieve this goal, a hybrid Genetic Algorithm – Artificial Neural Network (GA-ANN) model, was developed in C#.net, and three geometries, namely, U-shape, cube and cylinder were selected. To investigate the DA of printed parts, samples were printed with a central through hole. Design of Experiments (DoE), specifically the Rotational Central Composite Design method was adopted to establish the number of parts to be printed (30 for each selected geometry) and also the value of each input process parameter. The dimensions of printed parts were accurately measured by a shadowgraph and were used as an input data set for the training phase of the developed ANN to predict the behavior of process parameters. Then the predicted values were used as input to the Desirability Function tool which resulted in a mathematical model that optimizes the input process variables for selected geometries. The mean square error of 0.0528 was achieved, which is indicative of the accuracy of the developed model.

The results showed that print speed is the most dominant input variable compared to others, and by increasing its value, considerable variations resulted in DA. The inaccuracy increased, especially with parts of circular cross section. In addition, if there is no need to print parts in vertical position, the build orientation should be set at 0° to achieve the highest DA. Finally, optimized values of raster width and layer height improved the DA especially when the print speed was set at a high value.

By using ANN, it is possible to investigate the impact of simultaneous variations of FFF machines’ input process parameters on the DA of printed parts. By their optimization, parts of highly accurate dimensions could be printed. These findings will be of significant value to those industries that need to produce parts of high DA on FFF machines.

The purpose of this study is to increasing the gauge factor, reducing the hysteresis error and improving the stability over cyclic deformations of a conductive polylactic acid (CPLA)-based 3D-printed strain sensor by modifying the sensing element geometry.

Five different configurations, namely, linear, serpentine, square, triangular and trapezoidal, of CPLA sensing elements are printed on the thermoplastic polyurethane substrate material individually. The resistance change ratio of the printed sensors, when loaded to a predefined percentage of the maximum strain values over multiple cycles, is recorded. Finally, the thickness of substrate and CPLA and the included angle of the triangular strain sensor are evaluated for their influences on the sensitivity.

The triangular configuration yields the least hysteresis error with high accuracy over repeated loading conditions, because of its uniform stress distribution, whereas the conventional linear configuration produces the maximum sensitivity with low accuracy. The thickness of the substrate and sensing element has more influence over the included angle, in enhancing the sensitivity of the triangular configuration. The sensitivity of the triangular configuration exceeds the linear configuration when printed at ideal sensor dimensional values.

The 3D printing parameters are kept constant for all the configurations; rather it can be varied for improving the performance of the sensor. Furthermore, the influences of stretching rate and nozzle temperature of the sensing material are not considered in this work.

The sensitivity and accuracy of CPLA-based strain sensor are evaluated for modification in its geometry, and the performance metrics are enhanced using the regression modelling.

The purpose of this study is to produce a low-cost sheet metal forming mold made from the low melting point Bi58Sn42 (bismuth) alloy by using an open-source desktop-type material extrusion additive manufacturing system and to evaluate the performance of the additively manufactured mold for low volume sheet metal forming. Thus, it was aimed to develop a fast and inexpensive die tooling methodology for low-volume batch production.

Initially, the three-dimensional printing experiments were performed to produce the sheet metal forming mold. The encountered problems during the performed three-dimensional printing experiments were analyzed. Accordingly, both tunings in process parameters (extrusion temperature, extrusion multiplier, printing speed, infill percentage, etc.) and customizations on the extruder head of the available material extrusion additive manufacturing system were made to print the Bi58Sn42 alloy properly. Subsequently, the performance of the additively manufactured mold was evaluated according to the dimensional change that occurred on it during the performed pressing operations.

Results showed that the additively manufactured mold was rigid enough and proved to have sufficient strength in sheet metal forming operations for low-volume production.

Alternative mold production was carried out using open-source material extrusion system for low volume sheet metal part production. Thus, cost effective solution was presented for agile manufacturing.