dc.contributor.author | Singh, Maulshree | |
dc.contributor.author | Srivastava, Rupal | |
dc.contributor.author | Fuenmayor, Evert | |
dc.contributor.author | Kuts, Vladimir | |
dc.contributor.author | Qiao, Yuansong | |
dc.contributor.author | Murray, Niall | |
dc.contributor.author | Devine, Declan | |
dc.date.accessioned | 2022-08-29T09:11:07Z | |
dc.date.available | 2022-08-29T09:11:07Z | |
dc.date.copyright | 2022 | |
dc.date.issued | 2022-06-14 | |
dc.identifier.citation | Singh, M.; Srivastava, R.; Fuenmayor, E.; Kuts, V.; Qiao, Y.; Murray, N.; Devine, D. Applications of Digital Twin across Industries: A Review. Applied Sciences. 2022. 12. 5727. https://doi.org/10.3390/app12115727 | en_US |
dc.identifier.uri | http://research.thea.ie/handle/20.500.12065/4025 | |
dc.description.abstract | One of the most promising technologies that is driving digitalization in several industries is
Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What
differentiates DT from simulation and other digital or CAD models is the automatic bidirectional
exchange of data between digital and physical twins in real-time. The benefits of implementing DT in
any sector include reduced operational costs and time, increased productivity, better decision making,
improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow
exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have
become more intelligent, relaying on collection and storing incremental amounts of data. Connecting
that data effectively to DTs can open up many new opportunities and this paper explores different
industrial sectors where the implementation of DT is taking advantage of these opportunities and
how these opportunities are taking the industry forward. The paper covers the applications of DT in
13 different industries including the manufacturing, agriculture, education, construction, medicine,
and retail, along with the industrial use case in these industries/ | en_US |
dc.format | PDF | en_US |
dc.language.iso | eng | en_US |
dc.publisher | MDPI | en_US |
dc.relation.ispartof | Applied Sciences | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.subject | Digital Twin | en_US |
dc.subject | Industry 4.0 | en_US |
dc.subject | System optimization | en_US |
dc.subject | Predictive maintenance | en_US |
dc.title | Applications of Digital Twin across industries: a review | en_US |
dc.type | info:eu-repo/semantics/article | en_US |
dc.contributor.affiliation | Technological University of the Shannon Midlands Midwest | en_US |
dc.contributor.sponsor | The APC was funded by 692 Science Foundation Ireland | en_US |
dc.description.peerreview | yes | en_US |
dc.identifier.doi | 10.3390/app12115727 | en_US |
dc.identifier.eissn | 2076-3417 | |
dc.identifier.orcid | https://orcid.org/0000-0003-4788-1231 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-3127-4982 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-8982-7845 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-8134-8636 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-1543-1589 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-5919-0596 | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-1364-5583 | en_US |
dc.identifier.volume | 12 | en_US |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | en_US |
dc.subject.department | Materials Research Institute TUS:MM | en_US |
dc.type.version | info:eu-repo/semantics/publishedVersion | en_US |
dc.relation.projectid | 16/RC/3918 | en_US |