Cross Country Pipeline Risk-Based Failure Prediction Using Hybrid Fuzzy Rule and Grey Theory In FMEA – A Nigeria’s Pipeline System Case Study
Proceedings Publication Date
Shamsu Hassan
Shamsudeen Hassan, Prof. Jin Wang, Abdulbasi Muhammad
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The pipeline industry’s existing and new challenges require the identification of new and powerful techniques for performing a risk-based analysis of cross-country petroleum product pipeline systems. One of the traditional tools for carrying out pipeline failure prediction has been the Failure Mode and Effects Analysis (FMEA) technique due to its ease of application. However, a number of limitations have been identified with its application especially for cross-country pipelines in developing countries. Firstly, failure data is often not available or is unreliable, therefore identification of the risk priority numbers from the three failure factors of probability of failure, severity and detection relies on experts’ elicitation. Secondly, domain experts often provide diverse opinions and knowledge which could produce different assessment ranking and it is often difficult to harmonise that information due to multidisciplinary nature of the FMEA team. Thirdly, there is no systematic way of accounting for the relative importance of individual failure factors, with the risk of the assessment results not representing the true risk picture of the assessed system.

A proposed hybrid FMEA with Fuzzy Rule Base (FRB) and Grey System Theory (GST) technique overcomes these drawbacks, making the new approach more relevant to a petroleum product pipeline system in geographies with a paucity of, or unreliable, data.

The study utilises the fuzzy and grey theory to account for and integrate the experts’ diverse opinions and assign a relative weighting to each assessment factor; these are then used to determine the risk priority and rank the failure modes under different types of conditions.

The case study example, of a Nigeria’s petroleum product pipeline system 2B, used has shown its practical application which helps to improve the system’s failure prediction, the ranking of the components failure and their importance in decision making under uncertainty for cross-country pipeline integrity inspection and maintenance.

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