Classification of Static Mechanical Equipment using a Fuzzy Inference System: A Case Study from an Offshore Installation
Volume 11, Number 1, January 2015 - Paper 6 - pp. 53-60
A.M.N.D.B. SENEVIRATNE and R.M. CHANDIMA RATNAYAKEDepartment of Mechanical and Structural Engineering and Materials Science, Faculty of Science and Technology, University of Stavanger, NORWAY
(Received on April 11, 2014, revised on August 09, and September 30, 2014)
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 sub-system 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.
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