Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/61724
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shafiq, Syed Imran | en |
dc.contributor.author | Sanin, Cesar | en |
dc.contributor.author | Szczerbicki, Edward | en |
dc.date.accessioned | 2024-07-19T09:23:35Z | - |
dc.date.available | 2024-07-19T09:23:35Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Cybernetics and Systems, 55(3), p. 719-729 | en |
dc.identifier.issn | 1087-6553 | en |
dc.identifier.issn | 0196-9722 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/61724 | - |
dc.description.abstract | <p>Digital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts used in conventional manufacturing. It will empower manufacturers to leverage DT for real-time decision-making, control, and prediction for efficient production. An application scenario of Decisional-DNA based anomaly detection for conventional manufacturing tools is demonstrated as a case study to explain the architecture.</p> | en |
dc.language | en | en |
dc.publisher | Taylor & Francis Inc | en |
dc.relation.ispartof | Cybernetics and Systems | en |
dc.title | Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1080/01969722.2022.2162742 | en |
local.contributor.firstname | Syed Imran | en |
local.contributor.firstname | Cesar | en |
local.contributor.firstname | Edward | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | cmaldon3@une.edu.au | en |
local.output.category | C1 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United States of America | en |
local.format.startpage | 719 | en |
local.format.endpage | 729 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 55 | en |
local.identifier.issue | 3 | en |
local.contributor.lastname | Shafiq | en |
local.contributor.lastname | Sanin | en |
local.contributor.lastname | Szczerbicki | en |
dc.identifier.staff | une-id:cmaldon3 | en |
local.profile.orcid | 0000-0001-8515-417X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/61724 | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.search.author | Shafiq, Syed Imran | en |
local.search.author | Sanin, Cesar | en |
local.search.author | Szczerbicki, Edward | en |
local.uneassociation | No | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.published | 2024 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/e98edb26-ea62-4975-bc79-bc69f5cbed82 | en |
local.subject.for2020 | 4602 Artificial intelligence | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.date.moved | 2024-07-22 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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