A Fuzzy Markov Model for Risk and Reliability Prediction of Engineering Systems: A Case Study of a Subsea Wellhead Connector

Nan Pang,Feng Yin,Peilin Liu,Lei Zhou,Xiangyu Wang,Feihong Yun,Liquan Wang,Peng Jia

doi:10.3390/app10196902

Nan Pang, Feng Yin + Show 6 more

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https://doi.org/10.3390/app10196902

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Abstract

In production environments, failure data of a complex system are difficult to obtain due to the high cost of experiments; furthermore, using a single model to analyze risk, reliability, availability and uncertainty is a big challenge. Based on the fault tree, fuzzy comprehensive evaluation and Markov method, this paper proposed a fuzzy Markov method that takes the full advantages of the three methods and makes the analysis of risk, reliability, availability and uncertainty all in one. This method uses the fault tree and fuzzy theory to preprocess the input failure data to improve the reliability of the input failure data, and then input the preprocessed failure data into the Markov model; after that iterate and adjust the model when uncertainty events occur, until the data of all events have been processed by the model and the updated model obtained, which best reflects the system state. The wellhead connector of a subsea production system was used as a case study to demonstrate the above method. The obtained reliability index (mean time to failure) of the connector is basically consistent with the failure statistical data from the offshore and onshore reliability database, which verified the accuracy of the proposed method.

Highlights

Many engineering systems have such characters as high technology, high investment and high risk
There are many risk and reliability assessment methods, but the fuzzy Markov method proposed in this paper can solve the problems that other methods cannot solve
Aiming at the problems that the failure of engineering system is difficult to predict and the accurate statistics are lack, this paper presented the fuzzy Markov method integrating the fault tree analysis, fuzzy comprehensive evaluation and the Markov model

Summary

Introduction

Many engineering systems have such characters as high technology, high investment and high risk. The complex system is enormously affected by the internal and external loads, such as vibration, fatigue, temperature and human operation factors, even subjected to various hazards including natural disasters, terrorist and criminal acts [1,2,3]. Sci. 2020, 10, 6902 it will cause a series of problems such as transport accidents, explosions, casualties, fires and chemical and biological emission. Equipment storing inflammable and explosive materials such as chemical fuels, aviation equipment that is extremely hazardous in the event of an accident, and facilities that transport oil and gas energy have negative effects on environment, economy, society and life if an accident happened. Good judgments should be made on the risk, reliability, availability and uncertainty of such facilities

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