Digital Twins for Part Acceptance in Advanced Manufacturing Applications with Regulatory Considerations
Regulated industries such as the nuclear industry have long been risk averse when certifying new parts and designs, a necessity given the possible implications and consequences of a part failure. These industries often default to a legacy approach, with established parts and known quantities. This legacy approach applies to how parts are manufactured as well. Subsequently, parts developed with unproven or still maturing manufacturing technologies face significant hurdles when vying for acceptance. Today' advanced manufacturing processes have fundamentally changed how parts can be designed and fabricated. Advancements in manufacturing technologies, sensor technologies, and inspection technologies, accompanied by advancements in digital technologies, have resulted in new paradigms in how parts are developed, procured, and accepted. Additive manufacturing processes exemplify these advancements. AM processes have created a disruption in how manufactured parts are evaluated, as the uncertainties of these processes have created general trepidation about their acceptance. As digital manufacturing processes, however, AM processes generate substantial amounts of data at each stage of their design to product transformation. This data can be used to create a digital twin of the manufactured part and thus address challenges associated with legacy requirements by leveraging a new paradigm in part acceptance. In this work, we review basic acceptance criteria for parts. We then characterize these criteria in the context of a part's functional requirements and its manufacturing process signatures. Observations from these characterizations are then related back to the AM design-to-product transformations, identifying correlations between legacy data sets and AM data sets. Finally, understanding digital twins provide a virtual status of a physical counterpart, we posit that a digital manufacturing process such as additive manufacturing could be a more risk averse option than traditionally manufactured parts, as the digital twin should be able to provide almost "on-demand" insight into the state of the part at any given point along its production process. A case study is presented to demonstrate how a digital twin may be used to provide better insight in an advanced manufacturing process than what is achievable with more traditional manufacturing processes.
Digital Twins for Part Acceptance in Advanced Manufacturing Applications with Regulatory Considerations, The 46th MPA Seminar, Stuttgart, DE, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933613
(Accessed February 27, 2024)