Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/61748
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DC Field | Value | Language |
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dc.contributor.author | Shafiq, Syed Imran | en |
dc.contributor.author | Sanin, Cesar | en |
dc.contributor.author | Szczerbicki, Edward | en |
dc.date.accessioned | 2024-07-22T10:35:22Z | - |
dc.date.available | 2024-07-22T10:35:22Z | - |
dc.date.issued | 2022-07 | - |
dc.identifier.citation | Cybernetics and Systems, 53(5), p. 510-519 | en |
dc.identifier.issn | 1087-6553 | en |
dc.identifier.issn | 0196-9722 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/61748 | - |
dc.description.abstract | <p>The entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance in Industry 4.0 framework is demonstrated. The concept of VEO is used for the Tool and Equipment Monitoring, while for the Plants Operations Monitoring and Quality Monitoring, VEP and VEF are employed. Query extraction feature of DDNA is exploited for Adaptive Control. This study shows that Machine Efficiency (ME) can be monitored along with analysis of machine KPI’s like breakdown time, setting time, and other losses. Moreover, reports can be generated efficiency-wise, breakdown-wise, operator-wise. The data of these reports is used to predict and make future decisions related to machine maintenance.</p> | en |
dc.language | en | en |
dc.publisher | Taylor & Francis Inc | en |
dc.relation.ispartof | Cybernetics and Systems | en |
dc.title | Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1080/01969722.2021.2018549 | 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 | 510 | en |
local.format.endpage | 519 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 53 | en |
local.identifier.issue | 5 | 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:1959.11/61748 | en |
local.date.onlineversion | 2021-12-22 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework | 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.available | 2021 | en |
local.year.published | 2022 | en |
local.fileurl.closedpublished | https://rune.une.edu.au/web/retrieve/939af2d7-8e8c-45ef-9029-59b44e3947be | 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 | 2024-07-26 | en |
Appears in Collections: | Journal Article School of Science and Technology |
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