About this Abstract |
| Meeting |
2025 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2025)
|
| Symposium
|
2025 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2025)
|
| Presentation Title |
Scalable and Data-Driven Control Strategy for Layer Thickness Consistency in Directed Energy Deposition |
| Author(s) |
Sung-Heng Wu, Ranjit Joy, Harshit Agarwal, Sriram Praneeth Isanaka, Frank Liou |
| On-Site Speaker (Planned) |
Sung-Heng Wu |
| Abstract Scope |
Directed energy deposition (DED) offers advantages such as high deposition rates, material flexibility, and repair and add-on capabilities compared to other additive manufacturing processes. However, the complexity of thermal distributions, influenced by process parameters and multiple variables, often leads to defects and dimensional inaccuracies during deposition. This research proposes a scalable and data-driven control strategy to improve geometric dimensional accuracy. Two thermal cameras are employed to collect comprehensive thermal information — including melt pool, mushy zone, and the deposit — to analyze the relationship between layer height and thermal distribution and to establish a scalable process window. Data-driven and proportional-integral-derivative (PID) strategies are leveraged in the feedback control stage to maintain constant layer thickness. Comparative analysis demonstrates that the proposed strategy significantly improves layer thickness consistency. |
| Proceedings Inclusion? |
Planned: Post-meeting proceedings |