Methods for Mapping Empirical Data to Authoritative Definitions for Additive Manufacturing Part Validation

Published

November 21, 2023

Author(s)

Fahad Milaat, Paul Witherell, Ho Yeung, Martin Hardwick

Abstract

Traditionally, inspection and geometric dimensioning and tolerancing (GD&T) are deployed at the macroscale, where complete parts are tested to meet geometric and functional requirements. The additive manufacturing (AM) process is unique in that it is a digital process where the fabrication of the part at the macroscale is the result of a series of operations at micro and mesoscales. Subsequently any additively manufactured part is the aggregation of many points of localized fabrication, and these parts uniquely expose themselves to full volumetric inspection during part fabrication and postprocessing. While new methods have been developed for designers to communicate process definitions used for the fabrication of an AM part, methods to validate these specifications are lacking. This work will explore challenges in the validating against advanced part and process definitions. Leveraging the concepts of "authoritative product definition," "digital twin," and "time stepped commands," novel methods, built on a "zero dimension" information model, will be proposed to validate AM parts at the macroscale using mesoscale and microscale measurements and observations. Specifically, new data representations in the Standard for the Exchange of Product model data Numerical Control (STEP-NC) are proposed for discretizing AM geometry and process definitions to achieve point-level controls. Through the facilitation of traceable information in authoritative data models, AM process qualification and part acceptance could be streamlined, and reliable and referential data for Digital Twin frameworks and real-time controls could be realized.

Proceedings Title

Proceedings of the ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE2023

Conference Dates

August 20-23, 2023

Conference Location

Boston, MA, US

Conference Title

43rd Computers and Information in Engineering Conference (CIE)

Pub Type

Conferences

Download Paper

https://doi.org/10.1115/DETC2023-116710

Local Download

Keywords

data exchange, data/information modeling, GD&T/tolerance modeling, intelligent manufacturing

Citation

Milaat, F. , Witherell, P. , Yeung, H. and Hardwick, M. (2023), Methods for Mapping Empirical Data to Authoritative Definitions for Additive Manufacturing Part Validation, Proceedings of the ASME 2023 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE2023, Boston, MA, US, [online], https://doi.org/10.1115/DETC2023-116710, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936546 (Accessed April 27, 2024)