Optimising Control Engineering Tools Using Digital Twin Capabilities and Other Cyber-physical Metaverse Manufacturing System Components

dc.contributor.authorMourad, Nahia
dc.contributor.authorA. Alsattar, Hassan
dc.contributor.authorQahtan, Sarah
dc.contributor.authorZaidan, A.A.
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorMember, IEEE
dc.contributor.authorKumar Sangaiah, Arun
dc.contributor.authorMember, IEEE
dc.contributor.authorPedrycz, Witold
dc.contributor.authorFellow, Life
dc.date.accessioned2025-05-21T16:31:32Z
dc.date.available2025-05-21T16:31:32Z
dc.date.issued2024-02-21
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. et al. (2024) “Decisioning-Based Approach for Optimising Control Engineering Tools Using Digital Twin Capabilities and Other Cyber-Physical Metaverse Manufacturing System Components,” IEEE Transactions on Consumer Electronics, 70(1).
dc.identifier.doihttps://doi.org/10.1109/TCE.2023.3326047.
dc.identifier.issn0098-3063, 1558-4127
dc.identifier.urihttps://bspace.buid.ac.ae/handle/1234/3087
dc.language.isoen_US
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Transactions on Consumer Electronicsv70 n1 (202402): 3212-3221
dc.subjectCyber-physical metaverse manufacturing system components , control engineering tool , digital twin , multiple criteria decision-making
dc.titleOptimising Control Engineering Tools Using Digital Twin Capabilities and Other Cyber-physical Metaverse Manufacturing System Components
dc.typeArticle

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