About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Presentation Title |
HDF5 Hierarchies for AM Digital Representations |
Author(s) |
Laetitia Monnier, Paul Witherell, Hyunwoong Ko, Vincenzo Ferrero, Sebti Foufou |
On-Site Speaker (Planned) |
Laetitia Monnier |
Abstract Scope |
Advancement in Additive Manufacturing (AM) technologies and data acquisition techniques have led to an increase in AM data generated. However, due to the large volume and the diversity of AM data available it is becoming challenging to efficiently store, analyze, and represent AM processes. HDF5 have the potential to allow an easy access to big data by offering a hierarchical data catalog. Thus, AM processes could be represented through a hierarchy based on the data analytic needs and directly link the corresponding AM data.
This paper investigates the use of data formats to represents big data and AM dataset. Existing AM ontologies and models are reviewed in order to effectively encapsulate AM information and incorporate the hierarchy into an HDF5 AM wrapper. Three hierarchies are proposed to represent specifics perspectives of AM processes: the digital twin of AM Product Lifecycle, the AM V model representation, and the material centric characteristics. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |