This paper explains how half a billion hours of service data for pressure safety valves (PSVs) can be analysed and presented to allow optimisation of maintenance intervals and manage the inspection of PSVs. The large amount of data creates challenges, but also opportunities for an enhanced methodology expandable to other equipment types.

A methodology has been developed that uniquely combines qualitative and quantitative analysis. The latter ensures that the risk from PSV failure is determined and below set criteria. The drawback with this criterion alone would be that it is based on average data from a large set of PSVs and the average may not be applicable everywhere especially if failures are not random, but have an underlying, potentially unknown, cause. Therefore, each PSV is also qualitatively assessed. To bridge the gap between individual PSVs and "large sets", groups of PSVs are also identified in the methodology and data for them is collated and used within the whole group; the careful analysis required to define the groups, which must have similar properties, or performance, is described. This multi-layered assessment gains the most information possible from the data. The key part of the process is also to present this data for review and analysis, and this is achieved through a digital, cloud-based interactive dashboard.

The analysis has shown that maintenance intervals can be reduced significantly, but simultaneously risk reduced by concentrating effort on the worst-performing PSVs. Not least, a dashboard presentation of the risk-based inspection (RBI) showing the calculated inspection interval, changes to the intervals and failures allows a clear picture to be developed of PSV performance. Maintenance planning also becomes easier and information required for deferral assessments is available in seconds rather than hours. The analysis shows where poorer performance can occur, this is often applicable across different assets. The way in which the approach can be expanded to other equipment types will be described.

The novel approach in the assessment is the multi-layered combination of qualitative and quantitative analysis and the presentation of a large amount of data through the cloud to be used by maintenance teams, technical authorities and operators. It also shows the benefits of collecting half a billion service hours of data and that this need not be an onerous task.

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