A scalable digital platform for the use of digital twins in additive manufacturing

Scime, Luke R.; Singh, Alka R.; Paquit, Vincent C.

doi:10.1016/j.mfglet.2021.05.007

A scalable digital platform for the use of digital twins in additive manufacturing

Journal Article · Fri Jun 18 00:00:00 EDT 2021 · Manufacturing Letters

DOI:https://doi.org/10.1016/j.mfglet.2021.05.007· OSTI ID:1846544

^[1]; Singh, Alka R. ^[1]; ^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

We report that while Additive Manufacturing promises to reshape the manufacturing landscape, challenges related to part, and process qualification hinder its widespread adoption. The Instance-Qualified approach seeks to qualify individual parts, even for processes with high variability, by leveraging the concept of a digital twin. This work proposes a scalable cyberphysical infrastructure to enable the construction and use of such digital twins. This work also introduces the concept of an Augmented Intelligence Relay, which allows Artificial Intelligence algorithms to predict component performance for a given application even when it is impractical to perform a large number of physical tests.

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1846544

Alternate ID(s):: OSTI ID: 1846049

Journal Information:: Manufacturing Letters, Journal Name: Manufacturing Letters Journal Issue: N/A Vol. 31; ISSN 2213-8463

Publisher:: Society of Manufacturing Engineers, ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Related Subjects

36 MATERIALS SCIENCE
additive manufacturing
artificial intelligence
cyberphysical infrastructure
digital twins
instance-qualified

A scalable digital platform for the use of digital twins in additive manufacturing

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