About this Abstract |
Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
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Symposium
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2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
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Presentation Title |
Integrating Process Data in Motion for Additive Manufacturing Industrialization |
Author(s) |
Chen-Wei Yang, Alexander Kuan, Sheng-Yen Li, Yan Lu, Sebastien C. Philomin, Joshua Lubell, Haw-Ching Yang, Fan-Tien Cheng |
On-Site Speaker (Planned) |
Chen-Wei Yang |
Abstract Scope |
Researchers utilize in-process monitoring techniques to track Metal Additive Manufacturing (AM) stability. Real-time data analytics and control can significantly enhance final product quality. However, integrating high-speed, high-volume data poses challenges, especially processing multi-modality data for feedback control. Additionally, there is a demand to integrate AM systems with manufacturing operation management for scale-up adaptions.
We introduce the NIST AM Data Integration Testbench, aiming to establish an open platform empowering researchers to evaluate AM data integration methods, models, message exchange, and process control functionalities. The testbench equipped with in-situ monitoring emulators, enhances data flow efficiency through high-speed data streaming, automated metadata curation and big data archiving in cloud storage. It also features an edge-computing system for real-time data analysis and control. To facilitate AM industrialization, the testbench integrates a Manufacturing Execution System (MES). Leveraging this testbench for testing various data integration methods can advance AM technology. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |