Towards a Human-Centric Digital Twin for Human–Machine Collaboration:A Review on Enabling Technologies and Methods

Abstract

With the intent to further increase production efficiency while making human the centre of the processes, human-centric manufacturing focuses on concepts such as digital twins and human–machine collaboration. This paper presents enabling technologies and methods to facilitate the creation of human-centric applications powered by digital twins, also from the perspective of Industry 5.0. It analyses and reviews the state of relevant information resources about digital twins for human–machine applications with an emphasis on the human perspective, but also on their collaborated relationship and the possibilities of their applications. Finally, it presents the results of the review and expected future works of research in this area.

Publication DOI: https://doi.org/10.3390/s24072232
Divisions: College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
Funding Information: This work was supported by the Slovak Scientific Grant Agency by the project EDge- Enabled intelligeNt systems (EDEN), project number VEGA 1/0480/22
Additional Information: Publisher Copyright: © 2024 by the authors.
Uncontrolled Keywords: Commerce,Humans,Industry,Intention,Technology,human-centric,digital twin,human–machine collaboration,Industry 5.0,enabling technologies and methods,Analytical Chemistry,Information Systems,Instrumentation,Atomic and Molecular Physics, and Optics,Electrical and Electronic Engineering,Biochemistry
Publication ISSN: 1424-8220
Last Modified: 19 Jun 2024 07:23
Date Deposited: 04 Apr 2024 09:12
Full Text Link:
Related URLs: https://www.mdp ... -8220/24/7/2232 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Review article
Published Date: 2024-03-30
Published Online Date: 2024-03-30
Accepted Date: 2024-03-28
Authors: Krupáš, Maroš
Kajati, Erik
Liu, Chao (ORCID Profile 0000-0001-7261-3832)
Zolotova, Iveta

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