There is a gap between the Integrity management systems used by companies to manage their assets and the needs of the CP engineer. Integrity management systems do not fully meet the needs of the engineer responsible for corrosion as they do not provide access and visualizations of all the data the engineer needs to make fast and informed decisions. There is also often no easy way to see the trends in the data, or easily access the relevant video and photographic data also recorded during the survey.
By integrating the corrosion data with a simulation model a “digital twin” of the structure can be created to make predictions of the present and future protection of all parts of the structure. For example the engineer can easily use the software to systematically monitor the differences between the model predictions and survey data to identify anomalies and give early identification of problems which will require action.
The aim of any digital transformation of integrity management and in particular corrosion control is the improvement of communication efficiency, planning efficiency and maintenance efficiency. Key issues are predictive maintenance and clarity of the information available so engineers can make informed decisions. Therefore it is not just a question of collecting more information but also the way that information is used and shared with the decision makers.
BEASY’s Corrosion Digital Twin Services & Software enables engineers to manage and visualise in 3D CP survey data and provide access to all the relevant information through a 3D visual interface to any member of the teams. The software gives the engineer the ability to visualize in 3D the historical and predicted future CP protection of the structure and the status of the anodes in the CP system. It also provides information on long term trends in the survey data.
The “Digital Twin” can also be used to improve the planning and effectiveness of surveys, enhance and optimise the value from CP surveys and predict future risks so that remedies can be properly planned and costly unplanned repairs avoided. In many cases the significance of anomalous data cannot be fully appreciated or identified without convenient access to the trends in the data or the “Digital Twin” prediction
General Applications and Benefits
Typical applications include:
- Use 3D visualisation and a Digital Twin to clearly understand CP survey data and evaluate trends using multiple surveys and simulation.
- Interactively visualise in 3D the location of survey measurements and all the corrosion relevant data:
- Survey potential and FG Data
- Materials & Coating Conditions
- Anodes & their consumption data
- Planning of surveys and to enhance and optimise the value from CP surveys.
- Reduce the time spent interpreting survey data by linking the survey reports, photographs, videos, simulation results to the 3D visualisation
- Identify discrepancies by comparing survey data with digital twin simulation results.
- Enhanced and optimised CP surveys by using modelling to interpret the information identify anomalies earlier and predict future trends. Development of an optimum inspection strategy based on budgetary restrictions and the “health” of the structure
- Corrosion degradation of structures is a relatively slow process and hence high risk problems do not show up in the short term. This corrosion worsens over time and, unfortunately, it’s often only visible at an advanced stage of damage. Use of integrated modelling and survey data can predict future risks so that remedies can be properly planned and costly unplanned repairs avoided
- Model predictions correlated with survey data provide the information to proactively balance the maintenance effort over the life of the asset. The aim being to “Plan and pay now rather than pay a lot more later”
- Development of an effective proactive corrosion management strategy which can enhance production and lead to increased profits.
- Reduction of the risk of costs that can be incurred because of ineffective planning
- Improvement of design practices to prevent corrosion
Request more information on: Corrosion Data Management