(351e) Pressure-Based Process Monitoring of Direct-Ink Write Additive Manufacturing | AIChE

(351e) Pressure-Based Process Monitoring of Direct-Ink Write Additive Manufacturing


Reinholtz, D., Sandia National Laboratories
Leonard, J., Sandia National Laboratories
Tappan, A., Sandia National Laboratories
Cook, A., Sandia National Laboratories
Grillet, A. M., Sandia National Laboratories
Additive manufacturing allows for rapid prototyping, the creation of unique and complex geometries, the generation of less material waste, among many other benefits, when compared to traditional manufacturing. Direct-ink write is an extrusion-based additive manufacturing technique that enables the creation of custom-designed and reproducible hardware via extrusion of a paste or ink. Therefore, inherent changes in ink rheology and inhomogeneous ink formulation, due to insufficient mixing, variable pot-life, etc., can result in non-uniform extrusion and cause defects that are detrimental to the properties of the printed artifact. Additionally, inks containing a high particle loading and using particles with complex morphologies can contain trapped air or particle aggregates that cause undesirable clogging during extrusion, both of which can affect printed part properties and quality. The integration of pressure sensors on the extrusion apparatus can monitor the print process in situ by identifying changes in flow during printing. The goal of this work is to identify the viability and sensitivity of pressure-based process monitoring during extrusion to detect printing defects. Pressure is measured both at the top of the syringe barrel and just before the nozzle during extrusion of inks. To determine the sensitivity of the pressure measurement to aggregates in the ink, engineered defects in the form of 100-400 micron spherical polymer particles are added to DowSil SE1700 commercial printing ink resin. Pressure measurements over a range of extrusion conditions and engineered defect sizes as well as image analysis of the printed bead shape are used to determine sensitivity thresholds for the process monitoring.

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