Digital twin-driven vibration amplitude simulation for condition monitoring of axial blowers in blast furnace ironmaking

Xiao, Fu; Han, Junyi; Castle, Michael; Cao, Kuo

doi:10.1080/21642583.2022.2152400

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Dts Of Industrial Combustion Systems: Where Do We Stand?1

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2023

2024

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Cited by 2 publications

(1 citation statement)

References 34 publications

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“…Other attempts at developing DTs of industrial applications involve the development of a simplified physics-based model with a set of coefficients tuned with an optimization method, 61 building ROMs for specific variables of interest (e.g., emissions, vibrational data, …), and building estimators via regression algorithms for the system health states. 62 , 63 …”

Section: Dts Of Industrial Combustion Systems: Where Do We Stand?mentioning

confidence: 99%

Data-driven models and digital twins for sustainable combustion technologies

Parente,

Swaminathan

2024

iScience

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Section: Dts Of Industrial Combustion Systems: Where Do We Stand?mentioning

confidence: 99%

Data-driven models and digital twins for sustainable combustion technologies

Parente,

Swaminathan

2024

iScience

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Determinants of digital twin adoption in hospital operation management

Huang,

Ng,

2023

Urban Lifeline

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The hospital is one of the commercial buildings with the most complex and challenging operational management stage, and digital twin has been an important tool to improve the efficiency and quality of hospital operation management (HOM). As the largest developing country in the world, China has realized the potential of digital twin adoption in HOM, but the existing studies lack the systematic analysis of the determinants and the clarifying of their interrelationship. To fill these knowledge gaps, this paper employed Technology-Organization-Environment framework to sort out 12 determinants, and used DEMATEL-ISM method to analyze the interrelationships of determinants. The results showed that government policy was the determinant with the highest centrality degree and had the highest positive causality degree, while reliability was had lowest negative causality degree. User requirement was the only determinant at the root level, while the other three determinants under the environment dimension were at the deep and middle levels. The determinants under organizational dimension were located in the middle level and shallow level, and the determinants under technical dimension were all located in shallow level. Finally, three implications were put forward, including investigating user requirements for digital twin, leveraging support in the external environment and improving adoption readiness within the hospital. This study would not only enrich the academic framework in the field of HOM, but also provide the guidance for adopting digital twin in HOM in China and other similar economies around the world.

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Digital twin-driven vibration amplitude simulation for condition monitoring of axial blowers in blast furnace ironmaking

Cited by 2 publications

References 34 publications

Data-driven models and digital twins for sustainable combustion technologies

Data-driven models and digital twins for sustainable combustion technologies

Determinants of digital twin adoption in hospital operation management

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