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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.

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