Digital Twin for Predictive Corrosion Management towards Smarter Infrastructures

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Title
Digital Twin for Predictive Corrosion Management towards Smarter Infrastructures

CoPED ID
7d0759ee-eaa8-4f06-986b-41bb084222ed

Status
Closed


Value
£365,230

Start Date
Dec. 1, 2018

End Date
Nov. 30, 2019

Description

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CorrosionRADAR Ltd (CR) and Sonomatic Ltd proposes a digital twin technology for predictive corrosion management of structures. Monitoring and predicting the corrosion and, specially, Corrosion Under Insulation (CUI), which can potentially cause catastrophic failures and/or major downtime for many sectors, are the main focus of the project consortium. CR technology strives to be a global leader in remote sensing technologies and advanced analytics systems for smart infrastructures. Most of the current practices of corrosion detection use a reactive approach, manual non-destructive techniques and risk management based on very limited data. CorrosionRADAR has developed a suite of IIOT (Industrial Internet of Things) enabled sensors which could detect and locate both moisture and corrosion under insulation. This proposal aims to extend sensor capability to include temperature measurement. A predictive digital twin of the structure will be created for CUI management. Prediction model, with machine learning capability, will be through a combination of knowledge base of field CUI data, analytical and data base from extensive laboratory testing. Digital twin allows the asset manager to visualise the state of structure and carry out what if analysis for future corrosion trajectory. Success of this project will pave the way for data driven predictive maintenance, reducing maintenance cost without compromising on the safety of people, assets and environment. This will also lead to reducing downtime and can equally be applied to many sectors such as oil & gas, renewables, food processing units, chemical and thermal power plants and nuclear.

Corrosion Radar Limited LEAD_ORG
Corrosion Radar Limited PARTICIPANT_ORG
Sonomatic Limited PARTICIPANT_ORG

Subjects by relevance
  1. Remote sensing
  2. Forecasts
  3. Digital technology
  4. Risk management
  5. Corrosion
  6. Internet of things
  7. Digital television
  8. Machine learning
  9. Measurement
  10. Information management

Extracted key phrases
  1. Digital Twin
  2. Predictive Corrosion Management
  3. CorrosionRADAR Ltd
  4. Digital twin technology
  5. Predictive digital twin
  6. Smarter Infrastructures
  7. Sonomatic Ltd
  8. Field CUI datum
  9. Future corrosion trajectory
  10. Datum base
  11. Corrosion detection
  12. CUI management
  13. Remote sensing technology
  14. Limited datum
  15. Extensive laboratory testing

Related Pages

UKRI project entry

UK Project Locations