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

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3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)53-60
Number of pages8
JournalInternational Journal of Performability Engineering
Volume11
Issue number1
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Keywords

  • Equipment groups
  • Fuzzy inference system
  • In-service inspection
  • Inspection planning
  • Maintenance
  • Mechanical equipment classification

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