Decisioning-based approach for optimising control engineering tools using digital twin capabilities and other cyber-physical metaverse manufacturing system components

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dc.authorscopusidWitold Pedrycz / 56854903200
dc.authorwosidWitold Pedrycz / FPE-7309-2022
dc.contributor.authorMourad, Nahia
dc.contributor.authorAlsattar, Hassan A.
dc.contributor.authorQahtan, Sarah
dc.contributor.authorZaidan, Aws Alaa
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorSangaiah, Arun Kumar
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2025-04-18T10:38:37Z
dc.date.available2025-04-18T10:38:37Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThe optimisation of control engineering tools based on digital twin capabilities and other cyber-physical metaverse manufacturing system (CPMMS) components are crucial for the successful performance. This study proposes a model for optimising control engineering tools using digital twin capabilities and other CPMMS components to solve the open issues. The main contributions and novelty aspects of the methodological process are outlined as follows: Formulated and developed is a decision matrix based on a utility procedure for 10 control engineering tools with digital twin capabilities and other three CPMMS components (Programmable-Logic-Controller and Human-Machine-Interface, Internet of Things connectivity and cybersecurity features). This matrix accounts for the uncertainty associated with tool assessment and transformation evaluation issue; formulated and develop an integrating fuzzy weighted with zero-inconsistency-interval-valued spherical fuzzy rough sets (IvSFRS-FWZIC) and combined compromise solution (CoCoSo) methods. The IvSFRS-FWZIC method is utilised to assign importance degrees to the digital twin capabilities and other CPMMS components. The applicability and robustness of the proposed approach are validated and evaluated through conducting sensitivity, correlation, and comparative analyses. The proposed approach can assist managers in analysing and selecting the most suitable tool for developing CPMMS.
dc.identifier.citationMourad, N., Alsattar, H. A., Qahtan, S., Zaidan, A. A., Deveci, M., Sangaiah, A. K., & Pedrycz, W. (2023). Optimising Control Engineering Tools Using Digital Twin Capabilities and Other Cyber-physical Metaverse Manufacturing System Components. IEEE Transactions on Consumer Electronics.
dc.identifier.doi10.1109/TCE.2023.3326047
dc.identifier.endpage3221
dc.identifier.issn0098-3063
dc.identifier.issn1558-4127
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85176323150
dc.identifier.scopusqualityQ1
dc.identifier.startpage3212
dc.identifier.urihttp://dx.doi.org/10.1109/TCE.2023.3326047
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7158
dc.identifier.volume70
dc.identifier.wosWOS:001244815200313
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorPedrycz, Witold
dc.institutionauthoridWitold Pedrycz / 0000-0002-9335-9930
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartofIEEE transactions on consumer electronics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectDigital Twins
dc.subjectControl Engineering
dc.subjectMetaverse
dc.subjectManufacturing Systems
dc.subjectInternet of Things
dc.subjectCollaboration
dc.subjectOptimization
dc.subjectCyber-Physical Metaverse Manufacturing System Components
dc.subjectControl Engineering Tool
dc.subjectDigital Twin
dc.subjectMultiple Criteria Decision-Making
dc.titleDecisioning-based approach for optimising control engineering tools using digital twin capabilities and other cyber-physical metaverse manufacturing system components
dc.typeArticle

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