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Enabling FAIR Data in Additive Manufacturing to Accelerate Industrialization



Shengyen Li, Yan Lu, Kareem Aggour, Peter Coutts, Brennan Harris, Alex Kitt, Afina Lupulescu, Luke Mohr, Mike Vasquez


Additive manufacturing (AM) is an important enabler of Industry 4.0 but there are several hurdles that need to be overcome to fully realize the potential of AM. These challenges include the need for a data infrastructure to enable the scaling of the technologies as they mature, and data interoperability is critical to a sustainable and scalable data infrastructure. This paper outlines the need for a common data stack for an interoperable AM data infrastructure. At the foundation is a common data dictionary (CDD), which defines the critical technical vocabulary used by the AM community in logical buckets. On top of the CDD is a common data model (CDM), which defines the hierarchy of the terms in the CDD, enabling the data to be findable in a complex data system. The CDM empowers information integration and sharing throughout the lifecycles and value chains for different AM technologies. The comprehensiveness of the metadata defined in the CDM makes AM data reusable. To enable the exchange of data between different systems, common data exchange formats (CDEFs) transform the CDM into targeted data packages. Selected information and the design philosophy of the CDD, CDM, and CDEF are demonstrated with a sample use case to establish FAIR AM data to accelerate the development and adoption of AM technologies across alliances.
Advanced Manufacturing Series (NIST AMS) - 500-1
Report Number


additive manufacturing, data informatics


Li, S. , Lu, Y. , Aggour, K. , Coutts, P. , Harris, B. , Kitt, A. , Lupulescu, A. , Mohr, L. and Vasquez, M. (2023), Enabling FAIR Data in Additive Manufacturing to Accelerate Industrialization, Advanced Manufacturing Series (NIST AMS), National Institute of Standards and Technology, Gaithersburg, MD, [online],, (Accessed July 19, 2024)


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Created July 24, 2023