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Advanced Inspection
Applications- NII as replacement of IVI
- Pressure Vessels
- Pipelines
- Pipework
- Structures
- Subsea
- Heat Exchangers and Tubing
- Turbines
- Data Science
- Equipment integrity and reliability
- Robotic Tank Inspection
- Internal Inspection of Caissons
Data Science
As in many other areas, as technology is advancing, there is an increasing amount of quantitative data available by which to support decisions on asset integrity. The availability of additional data does not in itself lead to an improved understanding of asset condition and potential future condition. Further analysis is required in order to extract value from the data and to ensure the results reliably drive decisions on risk management while maximising efficiency. The principles of “Big Data” are increasingly relevant in integrity management and this trend will continue as inspection and monitoring technologies provide increasing volumes of information. As a consequence Data Science methods, in particular statistical analysis are playing an increasing role in integrity management.
Sonomatic is recognised as the industry leader in the development and application of statistical analysis of inspection data in support of integrity management. Our methods of analysis have been developed to maximise the value of inspection data, such that integrity decisions are based on the best possible knowledge of equipment condition and an understanding of any uncertainties related to inspection. We continue to develop innovative new approaches to data analysis and probabilistic assessments, making sure the benefits of advances in inspection and monitoring technologies are fully realised in practice.
- Statistical analysis of inspection data
- Statistical analysis for sampling inspections
- NII as replacement of IVI
- Pipework Inspection Assessment and Planning
- Pipeline integrity assessment
- Probabilistic integrity assessment
- Inspection planning and evaluation for unpiggable pipelines
- Assessment of ILI tool measurement errors
- Evaluation of inspection performance achieved
