TOWARDS AN INTEGRATED DATA SCHEMA DESIGN FOR ADDITIVE MANUFACTURING: CONCEPTUAL MODELING
Yan Lu, Sangsu Choi, Paul W. Witherell
Large amounts of data are generated, exchanged, and used during an additive manufacturing (AM) build. While the AM data from a single build is essential for establishing part traceability, when methodically collected, the full processing history of thousands of components can be mined to advance our understanding of AM processes. Hence, this full body of data must be captured, stored, and well-managed for easy query and analysis. An innovative, AM-specific data model is necessary for the establishment of a comprehensive AM information management system. This paper presents our work towards designing a complete and integrated data model for AM processes, named Additive Manufacturing Integrated Data Model (AMIDM). In initiating the development of AMIDM, we define the scope and specify the requirements of such a data model. Information created and exchanged in the AM process chain is identified based on an AM process activity diagram. After a review of existing AM data exchange standards, the gaps and challenges of developing a common AM data model are identified. Finally, we came up with a conceptual design of AMIDM based on a well-defined product lifecycle management (PLM) data modeling method called PPR (product, process, and resource). The proposed AM model, AMIDM, has a core scheme composed of product, process, and resource entities. The process entities play critical roles in transforming product input into product output using assigned resources such as equipment, material, personnel, and software tools. The proposed model has been applied to an information system design for experimental data management. An XML (eXtensible Markup Language) schema is presented in the paper to demonstrate the effectiveness of the conceptual model.
August 2-5, 2015
35th Computers and Information in Engineering Conference (CIE)