Predicting mechanical properties of material extrusion additive manufacturing-fabricated structures with limited information

Peterson, Amy M.; Kazmer, David O.

doi:10.1038/s41598-022-19053-3

Cited by 5 publications

(3 citation statements)

References 42 publications

(71 reference statements)

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“… 31 . Extensive research has been done to investigate and optimize these pre-processing parameters to improve the mechanical properties of MEX parts 32 – 36 . Kumar et al 37 made significant improvements in addressing challenges in MEX.…”

Section: Introductionmentioning

confidence: 99%

Ironing process optimization for enhanced properties in material extrusion technology using Box–Behnken Design

Alzyod,

Ficzere

2024

Sci Rep

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Material Extrusion (MEX) technology, a prominent process in the field of additive manufacturing (AM), has witnessed significant growth in recent years. The continuous quest for enhanced material properties and refined surface quality has led to the exploration of post-processing techniques. In this study, we delve into the ironing process as a vital processing step, focusing on the optimization of its parameters through the application of Design of Experiments (DoE), specifically the Box–Behnken Design (BBD). Through a systematic examination of ironing process parameters, we identified optimal conditions that resulted in a substantial reduction in surface roughness (Ra) by approximately 69%. Moreover, the integration of optimized ironing process parameters led to remarkable improvements in mechanical properties. For instance, the Ultimate Tensile Strength (UTS) saw a substantial improvement of approximately 29%, while the compressive strength (CS) showed an increase of about 25%. The flexural strength (FS) witnessed a notable enhancement of around 35%, and the impact strength (IS) experienced a significant boost of about 162%. The introduction of ironing minimizes voids, enhances layer bonding, and reduces surface irregularities, resulting in components that not only exhibit exceptional mechanical performance but also possess refined aesthetics. This research sheds light on the transformative potential of precision experimentation, post-processing techniques, and statistical methodologies in advancing Material Extrusion technology. The findings offer practical implications for industries requiring high-performance components with structural integrity and aesthetic appeal.

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Section: Introductionmentioning

confidence: 99%

Ironing process optimization for enhanced properties in material extrusion technology using Box–Behnken Design

Alzyod,

Ficzere

2024

Sci Rep

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“…Because of the variability in the process and final part properties due to thermal gradients, researchers have modeled the heat transfer within the MatEx process (Pourali and Peterson, 2019; Xia et al , 2018; Nahar and Gurrala, 2022; Driezen and Herrmann, 2022; Duarte et al , 2021) and implemented models to predict the strength of the welds within the process (Coogan and Kazmer, 2020; Peterson and Kazmer, 2022). As part of those efforts, researchers have investigated modeling of the melt temperature within the MatEx hot end (Trofimov et al , 2022; Xia et al , 2018; Osswald et al , 2018; Moretti et al , 2021; Prajapati et al , 2018; Van Waeleghem et al , 2022; Serdeczny et al , 2020b; Kattinger et al , 2022; Go et al , 2017; Mazzei Capote et al , 2021; Luo et al , 2020; Serdeczny et al , 2022).…”

Section: Introductionmentioning

confidence: 99%

Steady melting in material extrusion additive manufacturing

Colon,

Kazmer,

Peterson

et al. 2023

RPJ

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Purpose A main cause of defects within material extrusion (MatEx) additive manufacturing is the nonisothermal condition in the hot end, which causes inconsistent extrusion and polymer welding. This paper aims to validate a custom hot end design intended to heat the thermoplastic to form a melt prior to the nozzle and to reduce variability in melt temperature. A full 3D temperature verification methodology for hot ends is also presented. Design/methodology/approach Infrared (IR) thermography of steady-state extrusion for varying volumetric flow rates, hot end temperature setpoints and nozzle orifice diameters provides data for model validation. A finite-element model is used to predict the temperature of the extrudate. Model tuning demonstrates the effects of different model assumptions on the simulated melt temperature. Findings The experimental results show that the measured temperature and variance are functions of volumetric flow rate, temperature setpoint and the nozzle orifice diameter. Convection to the surrounding air is a primary heat transfer mechanism. The custom hot end brings the melt to its setpoint temperature prior to entering the nozzle. Originality/value This work provides a full set of steady-state IR thermography data for various parameter settings. It also provides insight into the performance of a custom hot end designed to improve the robustness of melting in MatEx. Finally, it proposes a strategy for modeling such systems that incorporates the metal components and the air around the system.

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“…Based on current understanding, the thermoplastic material extrusion's system performance is strongly affected by the melting capacity of the hot ends available [16][17][18], the slicing parameters used to generate the G-code for printing [19], a lack of observability and control [20], and the transient behavior of the thermoplastic in the hot end and its deposition [21]. It is critical that researchers investigate these areas, since they affect the properties of the nal part [22,23], and their prediction [23], and the accuracy of the part's dimensions to the user's design [24].…”

Section: Introductionmentioning

confidence: 99%

Transient modeling of material extrusion by system identification

Colon,

Kazmer,

Peterson

2023

Preprint

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Material extrusion is popular for its low barriers to entry and the flexibility it gives designers relative to traditional manufacturing techniques. Material extrusion is a transient process with a high frequency of starts, stops, and accelerations. This work presents transient data collected by an instrumented printhead and models the data by way of system identification. First-order and second-order control system models are proposed. The work also includes principal component analysis to determine which model coefficients correlate with the main effect, models the first-order model coefficients as a function of the experimental factors by regression, and predicts the apparent viscosity using a fitted static gain and known parameters. Flow rate, hot end temperature, nozzle diameter, and acceleration are the factors selected for the experiment. Each of these factors influences the steady state pressure, except for acceleration. The system identification models predict the melt pressure’s transient behavior well, with standard errors less than 4% of the mean melt pressure. Statistical analysis of the first-order model coefficients verifies that the static gain and time constant are statistically significant responses of the factors. The modeled apparent viscosity follows rheological expectations, showing the trends typically seen for viscosity as a function of shear rate.

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Predicting mechanical properties of material extrusion additive manufacturing-fabricated structures with limited information

Cited by 5 publications

References 42 publications

Ironing process optimization for enhanced properties in material extrusion technology using Box–Behnken Design

Ironing process optimization for enhanced properties in material extrusion technology using Box–Behnken Design

Steady melting in material extrusion additive manufacturing

Transient modeling of material extrusion by system identification

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