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PurposeA 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/approachInfrared (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. FindingsThe 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/valueThis 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. 

Current material extrusion systems can produce complex parts but lack instrumentation for observability and control. To investigate methods for observing the material extrusion process, a printer is instrumented to examine the dependency chain from the motor shaft torque to the infeed load and finally the melt pressure and temperature. The transient rheological and thermal behavior of the material extrusion process and the effect of volumetric flow rate, nozzle orifice diameter, and temperature setpoint on the pressure estimate from each point in the dependency chain are reported. The work also presents pressure predictions from COMSOL Multiphysics non-isothermal flow simulations and an analytical (Poiseuille) model. The pressure estimated by the motor shaft torque is greater than the downstream pressure estimated by the infeed load, which is greater than the downstream melt pressure in the hot end. In other words, both the torque sensor and the infeed load significantly overpredict the melt pressure. Significant variations in the pressures are also observed and explained. The findings demonstrate low and high frequency variation in the process, which can be attributed to gear eccentricity and teeth-to-filament engagement. The melt pressure variation is also observed to increase significantly at lower temperature set-points and higher flow rates, both of which reduce the melt temperature and thereby increase the viscosity. The increase in viscosity tends to reduce the viscous damping such that the variations in the filament infeed are transmitted through the hot end to the extrudate. 

Die-swell is a flow effect that occurs in polymer extrusion whereby the material experiences rapid stress and dimensional changes upon exiting the nozzle orifice. Material extrusion additive manufacturing is no exception, and this effect influences the final dimensions of the printed road and imparts residual stresses. Die-swell is measured via a custom test cell that uses optical and infrared cameras and an instrumented hot end with an infeed pressure load cell. The instrumented hot end is mounted onto a stationary extruder above a conveyor to simulate printhead translation at steady state conditions for a wide range of volumetric flow rates. Investigated factors for an acrylonitrile butadiene styrene (ABS) filament include volumetric flow rate (0.9 mm3/s to 10.0 mm3/s), hot end temperature setpoint (200–250 ◦C), and nozzle orifice diameter (0.25–0.60 mm). The die-swell increases as a function of the volumetric flow rate and shear stress but decreases as a function of the hot end temperature setpoint and nozzle orifice diameter. For modelling, an implementation of the Tanner model for die swell displays good agreement with experimental results. The model also demonstrates that the same proportionality constant, k_N1 , which relates first normal stress difference to shear stress, can be used for different nozzle orifice diameters with the same length to diameter ratios, and that kN1 increases as a function of hot end temperature setpoint as expected with the rheological concept of time temperature superposition. 

Dataset includes transient torque, infeed pressure, melt pressure, and melt temperature that were acquired by an instrumented hot end for material extrusion additive manufacturing of acrylonitrile butadiene styrene (ABS). Data were collected according to a design of experiments wherein the volumetric flow rate, temperature setpoint, and the nozzle orifice diameter were varied one factor at a time. 

Material extrusion additive manufacturing of polycarbonate, including tensile properties, cross-sectional microscopy, and fracture surfaces for single road width boxes printed with different print speeds, layer times, and extrusion temperatures. 

Compressibility and viscosity of polymer feedstock are critical to their volumetric flow rate, weld strength, and dimensional accuracy in material extrusion additive manufacturing. In this work, the compressibility and viscosity of an acrylonitrile butadiene styrene (ABS) material is characterized with an instrumented hot end design. Experiments are first performed with a blocked nozzle to characterize the compressibility behavior. The results closely emulate the pressure-volume-temperature (PVT) behavior of a characterized generic ABS. Experiments are then performed with an open nozzle over a range of volumetric flow rates and temperatures. The static pressure data is fit to power-law, Ellis, and Cross viscosity models and the dynamic melt pressure data is then used to jointly fit material constitutive models for compressibility and viscosity. The results suggest that the joint fitting substantially improves the fidelity relative to the separately characterized viscosity and compressibility. The implemented methods support material extrusion process simulation and control including real-time identification of process faults such as (1) limited melting capacity of the hot end, (2) skipping (grinding) of the extruder drive gears, (3) low initial nozzle temperature, (4) varying flow rates associated with the intermeshing gear tooth velocity profile, and (5) delays and reduced melt pressures due to drool prior to extrusion. The ability to monitor the printing process for faults in real time, such as that presented in this work, is critical to born qualified parts. Additionally, these approaches can be used to screen new materials and identify optimal processing conditions that avoid these process faults. 

The nozzle pressure was monitored in a fused filament fabrication process for the printing of high impact polystyrene. The contact pressure, defined as the pressure applied by the newly deposited layer onto the previous layer, is experimentally calculated as the difference between the pressure during printing and open discharge at the same volumetric flow rates. An analytical method for estimating the contact pressure, assuming one-dimensional steady isothermal flow, is derived for the Newtonian, power-law, and Cross model dependence of shear rates. A design of experiments was performed to characterize the contact pressure as a function of the road width, road height, and print speed. Statistical analysis of the results suggests that the contribution of the pressure driven flow is about twice that of the drag flow in determining contact pressure, which together describe about 60% of the variation in the observed contact pressure behavior. Modeling of the elastic and normal stresses at the nozzle orifice explains an additional 30% of the observed behavior, indicating that careful rheological modeling is required to successfully predict contact pressure.