AI Bibliography
AI Bibliography |
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Grieves, M., & Vickers, J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary perspectives on complex systems: New findings and approaches, 85–113. |
| Resource type: Journal Article BibTeX citation key: Grieves2017 View all bibliographic details  |
Categories: Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, Engineering, General, Mathematics Subcategories: Analytics, Big data, Decision making, Forecasting, Human factors engineering, Informatics, Simulations, Space Creators: Grieves, Vickers Publisher: Collection: Transdisciplinary perspectives on complex systems: New findings and approaches |
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| Abstract |
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Systems do not simply pop into existence. They progress through lifecycle phases of creation, production, operations, and disposal. The issues leading to undesirable and unpredicted emergent behavior are set in place during the phases of creation and production and realized during the operational phase, with many of those problematic issues due to human interaction. We propose that the idea of the Digital Twin, which links the physical system with its virtual equivalent can mitigate these problematic issues. We describe the Digital Twin concept and its development, show how it applies across the product lifecycle in defining and understanding system behavior, and define tests to evaluate how we are progressing. We discuss how the Digital Twin relates to Systems Engineering and how it can address the human interactions that lead to “normal accidents.” We address both Digital Twin obstacles and opportunities, such as system replication and front running. We finish with NASA’s current work with the Digital Twin.
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