Evidence map›Paper›PMID 40968904›Full record

ArticleSensors (Basel, Switzerland)2025

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

Christopher Lee Colaw, Garrett Madison, Bill Tseng, Grayson Michael Griser, Gage Truelson, Adam Gallo, Yildirim Hurmuzlu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Christopher Lee ColawDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.ORCID 0009-0006-5631-1299
Garrett MadisonDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.
Bill TsengDepartment of Industrial, Manufacturing and Systems Engineering, The University of Texas, El Paso, TX 79968, USA.ORCID 0000-0002-3903-529X
Grayson Michael GriserDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.
Gage TruelsonDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.
Adam GalloDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.
Yildirim HurmuzluDepartment of Mechanical Engineering, Southern Methodist University, Dallas, TX 75205, USA.ORCID 0000-0002-8593-4587

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AviationAlgorithmsArtificial IntelligenceHumansQuality ControlVirtual Realityartificial intelligencedetectionHuman Digital Twinhuman feedbacksecurity cameravirtual environmentvirtual reality

Identifiers

PMID40968904
PMCPMC12158248

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.