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A digital twin (DT) is an interactive, real-time digital representation of a system or a service utilizing onboard sensor data and Internet of Things (IoT) technology to gain a better insight into the physical world. With the increasing complexity of systems and products across many sectors, there is an increasing demand for complex systems optimization. Digital twins vary in complexity and are used for managing the performance, health, and status of a physical system by virtualizing it. The creation of digital twins enabled by Modelbased Systems Engineering (MBSE) has aided in increasing system interconnectivity and simplifying the system optimization process. More specifically, the combination of MBSE languages, tools, and methods has served as a starting point in developing digital twins. This article discusses how MBSE has previously facilitated the development of digital twins across various domains, emphasizing both the benefits and disadvantages of adopting an MBSE enabled digital twin creation. Further, the article expands on how various levels of digital twins were generated via the use of MBSE. An MBSE enabled conceptual framework for developing digital twins is identified that can be used as a research testbed for developing digital twins and optimizing systems and system of systems. Keywords—MBSE, Digital Twin, Digital Shadow, Digital Model, SysML
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How the map becomes the territory: prediction, performativity and the process of taking digital twins for granted
Abstract A growing body of literature argues that digital models do not just help organizational leaders to predict the future. Models can inadvertently produce the very future they purport to describe. In this view,performativityis a side-effect of digital modeling. But digital twins turn such thinking on its head. Digital twins are digital models that are designed to be performative—changes in the model are supposed to produce corresponding changes in the world the model represents. This is what makes digital twins useful. But for decision-makers to act in ways that align the world outside the model with the predictions contained within, they must first believe that the model is a faithful representation. In other words, for a digital twin to become performative, it must first be taken-for-granted as “real”. In this paper, we explore the technological and organizational characteristics that are likely to shape the level of taken-for-grantedness of a digital twin.
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- Award ID(s):
- 2051896
- PAR ID:
- 10490857
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Journal of Organization Design
- Volume:
- 13
- Issue:
- 3
- ISSN:
- 2245-408X
- Format(s):
- Medium: X Size: p. 101-112
- Size(s):
- p. 101-112
- Sponsoring Org:
- National Science Foundation
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