| About this Abstract |
| Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Symposium
|
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Presentation Title |
A Real-Time Monitoring Framework for Cooperative 3D Printing |
| Author(s) |
Cole Mensch, Anuj Swaminathan, Zhenghui Sha |
| On-Site Speaker (Planned) |
Anuj Swaminathan |
| Abstract Scope |
This paper presents a real-time process monitoring framework designed for cooperative 3D printing (C3DP), capable of detecting common errors that occur in FDM 3D printing and providing corrective feedback in a closed-loop system. C3DP is a primitive instance of swarm manufacturing (SM) that integrates swarm robotics and additive manufacturing to build large parts to overcome the scalability issues present in traditional 3D printing. Our prior work has established the C3DP framework, with steps such as geometric partitioning, scheduling, placement, and path planning. However, C3DP cannot achieve full autonomy unless its capabilities include live monitoring of the manufacturing environment and feedback-driven error correction. The proposed system utilizes various computer vision techniques, including object tracking, object classification, and image similarity comparisons, which are merged into a holistic decision-support system for real-time monitoring and closed-loop control of C3DP. We demonstrate its effectiveness by running multiple test prints with various combinations of built-in errors. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |