Classification of static mechanical equipment using a fuzzy inference system: A case study from an offshore installation

A recent audit of oil and gas (O&G) production and process facilities (P&PFs) functioning on the Norwegian Continental Shelf (NCS) revealed that inadequate classification of equipment tends to increase the probability of maintenance induced failures. Hence, to mitigate the problem, this manuscript suggests a fuzzy inference system (FIS) to further revise and fine-tune an existing static mechanical equipment classification which has been utilized for the inspection and maintenance of a North Sea P&PF. Such a revision and fine-tuning of the existing classification enables the equipment in a subsystem of a P&PF to be identified by its degradation mechanism and classified under common degradation groups (e.g., corrosion loops, erosion loops, etc.). A case study has been performed using condition monitoring data and historical in-service inspection data retrieved from the piping inspection database (PIDB) belonging to a P&PF located on the NCS.