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dc.contributor.authorLussier, Jonathan
dc.contributor.authorHua, Edward Y.
dc.contributor.authorLedford, Allison
dc.contributor.authorThomas, Dale
dc.contributor.authorVan Bossuyt, Douglas L.
dc.contributor.authorWooley, Ana
dc.date.accessioned2026-08-23T07:52:51Z
dc.date.available2026-08-23T07:52:51Z
dc.date.copyright2025/12/01
dc.date.issued2025
dc.identifier.issn1530-9827
dc.identifier.otherjcise-25-1247.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4315751
dc.description.abstractAbstract. In recent years, the digital twin (DT) technology has become the subject of significant excitement as its potential to revolutionize many different industries has become clear. However, excitement around DT has led to an eagerness to label many models, simulations, and control systems (CSs) as DTs when they do not meet the strict definition of a DT. We posit that this mislabeling is partly due to the lack of a clear consensus on what is and is not a DT. In order to clarify the differences between DT and CS, this article reviews a number of current DT definitions for practical applicability, develops a refined definition, provides a method of differentiating between DTs and CSs, and presents use case studies to demonstrate the effectiveness of the method.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleDifferentiating Between Digital Twins and Control Systems for Complex Systems
dc.typeJournal Paper
dc.journal.volume25
dc.journal.issue12
dc.journal.titleJournal of Computing and Information Science in Engineering
dc.identifier.doi10.1115/1.4070329
dc.journal.fristpage17
dc.journal.lastpage25
dc.page9
dc.treeJournal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue:012
dc.contenttypeFulltext


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