Evaluation of risk levels in static mechanical equipment: a fuzzy expert system approach

Abstract

It is necessary to evaluate the risk levels in piping components of offshore production and process facilities (OP%PFs) to investigate potential failures. In an OP%PF, piping plays a vital role within the static mechanical equipment. Inspection planners make recommendations on the thickness measurement locations (TMLs) to be monitored based on: historical data, risk-based inspection (RBI) analysis results, plant inspection strategy guidance, etc. The inspection plans made by inexperienced inspection planners are of poor quality compared to an inspection plan made by an experienced inspection planner. Hence, to mitigate the problem, it is vital to develop expert systems to support inexperienced inspection planners and minimise suboptimal decisions. This manuscript illustrates the use of a fuzzy inference system (FIS) as an expert system for making optimal in-service inspection recommendations based on the current status and trends of TMLs. The proposed FIS enables the expertise of experienced inspection planners to be incorporated via membership functions (MFs) and a rule base, which will maintain the quality of an inspection programme at the intended level.