About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Symposium
|
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Presentation Title |
Intellectual Property Protection in Distributed Intelligent Additive Manufacturing via Surrogate STL Generation and G-code Reconstruction |
| Author(s) |
Syed Ziaul Bin Bashar, Jesus Diaz, Anusha Vangala, Roopa Vishwanathan, Chaitanya Mahajan, Satyajayant Misra |
| On-Site Speaker (Planned) |
Syed Ziaul Bin Bashar |
| Abstract Scope |
This paper presents a lightweight framework for Distributed Intelligent Additive Manufacturing (DIAM) to reduce the risks associated with STL file sharing across distributed print environments while preserving manufacturability. Instead of transmitting the original design, the owner generates a protected surrogate STL by inserting a controllable number of artificial layers along the build direction using a Trimesh-based preprocessing pipeline. The modified STL is then encrypted and sent to the service provider for slicing. After slicing, a companion execution module processes the generated G-code, identifies the inserted layer regions, removes the artificial layers, and reconstructs the final production toolpath for printing. In this workflow, the original STL is never disclosed outside the owner’s environment. Experimental results show that the method preserves printability while reducing direct access to the native design. Although partial reverse reconstruction from the final toolpath remains possible, the recovered geometry loses fine-detail fidelity relative to the original STL model. |
| Proceedings Inclusion? |
Undecided |