VOLCO: A predictive model for 3D printed microarchitecture
journal contributionposted on 22.05.2018, 11:56 by Andy GleadallAndy Gleadall, Ian A. Ashcroft, Joel Segal
Material extrusion additive manufacturing is widely used for porous scaffolds in which polymer filaments are extruded in the form of log-pile structures. These structures are typically designed with the assumption that filaments have a continuous cylindrical profile. However, as a filament is extruded, it interacts with previously printed filaments (e.g. on lower 3D printed layers) and its geometry varies from the cylindrical form. No models currently exist that can predict this critical variation, which impacts filament geometry, pore size and mechanical properties. Therefore, expensive time-consuming trial-and-error approaches to scaffold design are currently necessary. Multiphysics models for material extrusion are extremely computationally-demanding and not feasible for the size-scales involved in scaffold structures. This paper presents a new computationally-efficient method, called the VOLume COnserving model for 3D printing (VOLCO). The VOLCO model simulates material extrusion during manufacturing and generates a voxelised 3D-geometry-model of the predicted microarchitecture. The extrusion-deposition process is simulated in 3D as a filament that elongates in the direction that the print-head travels. For each simulation step in the model, a set volume of new material is simulated at the end of the filament. When previously 3D printed filaments obstruct the deposition of this new material, it is deposited into the nearest neighbouring voxels according to a minimum distance criterion. This leads to filament spreading and widening. Experimental validation demonstrates the ability of VOLCO to simulate the geometry of 3D printed filaments. In addition, finite element analysis (FEA) simulations utilising 3D-geometry-models generated by VOLCO demonstrate its value and applicability for predicting mechanical properties. The presented method enables structures to be validated and optimised prior to manufacture. Potential future adaptations of the model and integration into 3D printing software are discussed.
The research leading to these results has received funding from the EPSRC [grant number EP/H028277/1] in the EPSRC Centre for Innovative Manufacturing in Regenerative Medicine.
- Mechanical, Electrical and Manufacturing Engineering