3D printing is a revolutionary technique able to create parts and components that are not possible with conventional techniques such as machining and that are not suitable for large scale molding due to the time and investment required. 3D printing can be performed in many ways, however one of the most common processes is forming a part by stacking 2D layers to create the desired geometry. In the Fused Filament Fabrication (FFF) method, which was the focus of this work, this typically consists of a polymer material being extruded melting the layers of the to be produced together.
Typically this FFF method faces a trade-off in terms of the speed at which is being printed and the precision at which the deposition process occurs, due to the open loop control of the extrusion process. Typically only filament feed rate and hot-end/nozzle temperature are being regulated, with user calibration being the determining factor of the rate of over- or under-extrusion. The movement of the material depositing print-head is also often open loop, and filament consistency, environmental conditions and component wear state are often unknowns affecting the extrusion consistency. Therefore the ability to have a manner of real time monitoring of the process would greatly improve the consistency and quality of FFF 3D printed parts and components.
Our work introduces conductively doped filaments to provide a real-time way to perform direct measurement of the fusion and extrusion process of deposited layers. This is achieved by measuring the electrical impedance between the printbed and extruding nozzle, deriving a tomographic description of the print as a resistive network resulting from the printed layers. The addition of a predictive model for the expected print impedance then allows for identification of part construction issues, which can then be adapted to result in real time defect characterisation with the options of correction or print abortion in the case of failed prints.