Methodology for Enablement of Human Digital Twins for Quality Assurance in the Aerospace Manufacturing Domain

This paper will examine a methodology to enable the usage of Human Digital Twins (HDTs) for Quality Assurance in the aerospace manufacturing domain. Common-place hardware and infrastructure, including cloud-based facility security cameras, cloud-based commercial virtual environments, a virtual reali...

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Bibliographic Details
Main Authors: Christopher Lee Colaw, Garrett Madison, Bill Tseng, Grayson Michael Griser, Gage Truelson, Adam Gallo, Yildirim Hurmuzlu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/11/3362
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Summary:This paper will examine a methodology to enable the usage of Human Digital Twins (HDTs) for Quality Assurance in the aerospace manufacturing domain. Common-place hardware and infrastructure, including cloud-based facility security cameras, cloud-based commercial virtual environments, a virtual reality (VR) headset, and artificial intelligence (AI) detection algorithms, have been connected via application programming interfaces (API) to enable a 24-h surveillance and feedback capability for a representative aerospace manufacturing cell. Human operators who perform defined manufacturing assembly operations in real life in the cell can utilize this methodology to digitize their performance and provide objective evidence of conformity and safety messaging for their human-centric manufacturing operation in real time. The digitization of real human-centric performance using this methodology creates the foundation for a HDT. This paper will present the application of HDTs in a manner that can easily be scaled across manufacturing operations while utilizing technologies that are already commonly inserted into existing manufacturing operations, which facilitates the exploration of HDT concepts without the need for expensive capital purchases and emerging technologies.
ISSN:1424-8220