Another factor related to the database is the maintenance vessel mobilisation time, which could be a significant contributor to system downtime. It is assumed that the mobilisation history in the database is representative, but this assumption may be challenged as it is difficult to determine the correct mobilisation times for the relevant items from the available data.
By using FMECA, criticality assessments are carried out assuming that only one failure event or failure mode occurs at the time. It is assumed that all the other items are working perfectly. None of the other items are then in a failure mode, are waiting for maintenance or have hidden failures. However, real life may very well be different.
It is also assumed that failures are immediately detected when they occur. However, this assumption may not hold in practice for the valves as failures of these may be hidden due to redundancies. Some valve failures may be detectable only by function testing or the appearance of a second failure of another item within the redundant system.
The flowline is regularly pigged by use of a smart pig that monitors flowline inside parameters, for example the inner diameter and temperature. The reliability and accuracy of this smart pig is not assessed by the FMECA, nor is the assumption that pigging prevents blockage. These assumptions may lead us to ignore failure modes concerning flowline blockage.
The last two uncertainty factors are related; they address the assumptions that the items installed are adequately tested and inspected prior to production start up and that production is inside the design criteria and requirements/recommendations, e.g. design pressure and sand concentration limits.