Large-scale additive manufacturing with pellet feedstock is an industrial manufacturing process that has enabled printing parts in the scale of multiple meters and at material deposition rates of up to 150 kg/hour. This process has been successfully demonstrated in applications including tooling for autoclave composite manufacturing, double-sided tooling for composites compression molding, multi-story high monuments, and non-structural vehicle components. However, the multiple phenomena developed during the printing process can lead to residual stresses, warpage, or delamination that can result in expensive print failures. Further, print failures may not be evident until multiple hours into the printing process, or even until after a print is completed. Phenomena including anisotropic flow, shrinkage, heat transfer, viscoelasticity, polymer crystallization (semi- crystalline polymers), and fusion bonding, develop simultaneously during the printing process. Hence, enabling first-time right printing through validated predictive simulation tools is paramount to enhance the confidence in this technology. This results in shorter times to develop and produce parts and significant reductions in costs due to reduced, or eliminated, failed prints.
This work presents experimental validation of simulation predictions for temperature and deformation carried out with a physics-based simulation workflow called ADDITIVE3D. This workflow captures the phenomena mentioned above and involves material and machine cards to capture the specific behavior of different fiber-reinforced polymers and the uniqueness of additive manufacturing systems, respectively. Predictions made with ADDITIVE3D for temperature and deformation were in great agreement with the experimental measurements.
Learning Objectives:
- Understand the uses of the ADDITIVE3D simulation technology in their current and future manufacturing workflow
- Have the connections at both Techmer PM and Purdue CMSC to enable further dialogue and integration of these new materials and simulation into their operations.
- Understand the benefit of more efficient workflow in LFAM through discussion of case studies and benefits realized in previous successful projects.
