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 |
AMUI: A Data-driven Additive Manufacturing User Interface for Process Optimization |
Author(s) |
Peter Pak, Chakradhar Guntuboina, Odinakachukwu Francis Ogoke, Achuth Chandrasekhar, Olabode Ajenifujah, Amir Barati Farimani |
On-Site Speaker (Planned) |
Odinakachukwu Francis Ogoke |
Abstract Scope |
Rapid prototyping in many additive manufacturing (AM) applications requires immediate, point-of-need access to the optimal process configurations for a specific build. Therefore, we introduce the Additive Manufacturing User Interface (AMUI), an intuitive end-to-end user interface for automatically optimizing process parameters for 3D printing with minimal requirements for user domain knowledge. It will enable individuals without prior technical expertise to upload 3D computer-aided-design models and determine the necessary processing conditions for their builds. Using surrogate models and analytical solutions, we automatically predict the optimal printing parameters for processes such as Laser Powder Bed Fusion (LPBF) and effectively mitigate potential sources of defects. Specifically, we leverage surrogate models of the temperature fields produced during AM processes in combination with physics-based simulations to create custom process maps for a specific build configuration. We also discuss extensions to other areas of the AM workflow enabled by the modular design of the interface. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |