Process optimization of large scale robot based polymer 3D printing

Purpose and goal

The ultimate goal of the project was to determine temperature history, and use it as a guideline to optimize printing path for minimum printing failure, and also to predict deformation and residual stress in large-scale additive manufacturing. Due to limited computational resources available in this project, we just managed to model a single layer deposition, and verify temperature predictions with experimental measurement. As an initial step, the project findings shed light on the main challenges that must be addressed in more thorough simulations.

Expected results and effects

The project provides a foundation for future developments in simulation of large-scale robotic based 3D printing. As a pioneer study, it recognizes the main challenges ahead in transient computational fluid dynamics (CFD) simulations of large-scale 3D printing, including thermal interaction of successive layers, adaptive remeshing scheme, contact modeling settings, etc. To be able to simulate large-scale complex 3D engineering components more realistically, further improvement in the presented process will be of great importance.

Planned approach and implementation

In this project, we tried to use a commercially available CFD software, ANSYS Polyflow, for process simulation of the large-scale additive manufacturing. The goal was to predict temperature history during melt deposition of a complex three-dimensional structure. For this purpose, we used a power-law viscosity model to simulate the polymer melt rheological behaviour. However, the approach followed was merely able to generate simple models of single layer deposition in two dimensions. More computational resources are required to further extend the model.