Risk assessment of railway transportation systems using timed fault trees

Peng, Z., Lu, Y. , Miller, A. , Johnson, C. and Zhao, T. (2016) Risk assessment of railway transportation systems using timed fault trees. Quality and Reliability Engineering International, 32(1), pp. 181-194. (doi: 10.1002/qre.1738)

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Safety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent, and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed fault trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide how much time have been left at least to eliminate the root failure to prevent accidents. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system, and principles and rules of TFTs. We demonstrate the applicability of our framework by a case study on a simple railway transportation system.

Item Type:Articles
Keywords:fault tree analysis, railway transportation systems, risks, risk assessment, timed fault trees.
Glasgow Author(s) Enlighten ID:Johnson, Professor Chris and Miller, Professor Alice and Lu, Mr Yu
Authors: Peng, Z., Lu, Y., Miller, A., Johnson, C., and Zhao, T.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Quality and Reliability Engineering International
ISSN (Online):1099-1638
Published Online:14 October 2014

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
594881EATS: ETCS Advance Testing SystemChristopher JohnsonEuropean Commission (EC)314219 EATSCOM - COMPUTING SCIENCE