Application of fuzzy fault tree analysis for evaluation of railway safety risks: An evaluation of root causes for passenger train derailment

Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit

Volumn 226, Issue 1, 2012, Pages 14-25

  Jafarian, E ^a   Rezvani, M A ^a  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

Author keywords

Fault tree analysis; Fuzzy importance measures; Fuzzy logic; Passenger train derailment; Railway safety risks

Indexed keywords

BEST CHOICE; CONVENTIONAL APPROACH; CUT-SET; DEFUZZIFICATION METHOD; DEFUZZIFICATIONS; ENGINEERING APPLICATIONS; FAULT-TREES; FUZZY APPROACH; FUZZY ENVIRONMENTS; FUZZY FAULT TREE ANALYSIS; FUZZY IMPORTANCE MEASURES; IMPORTANCE MEASURE; LEVEL SET; PASSENGER TRAIN; POINT VALUE; RAILWAY SAFETY; ROOT CAUSE; TIME-DEPENDENT VARIABLES; TOP EVENT PROBABILITY; WEIGHTED AVERAGING;

FUZZY LOGIC; RAILROAD TRANSPORTATION; RANDOM VARIABLES;

FAULT TREE ANALYSIS;

EID: 84858307649     PISSN: 09544097     EISSN: 20413017     Source Type: Journal    
DOI: 10.1177/0954409711403678     Document Type: Conference Paper

References (34)

1. Bateman, T. S. and Crant, J. M. The proactive component of organizational-behaviour: A measure and correlate. J. Organ. Behav., 1993, 14(2), 103-118.
2. Vincoli, J. Basic guide to system safety, 2nd edn, 2006 (John Wiley and Sons, Hoboken, New Jersey).
3. Ericson, C. Hazard analysis techniques for system safety, 2005 (John Wiley and Sons, Hoboken, New Jersey).
4. Limnios, N. Fault trees (control systems, robotics and manufacturing series), 2007 (ISTE Ltd, London).
5. Huang, H. Z. Posbist fault tree analysis of coherent systems. Reliab. Eng. Syst. Saf., 2004, 84, 141-148.
6. Wu, C. Fuzzy reliability estimation using Bayesian approach. Comput. Ind. Engng, 2004, 46, 467-493.
7. Yuhua, D. and Datao, Y. Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis. J. Loss Prev. Process Ind., 2005, 18, 83-88.
8. Misra, B. and Weber, G. A new method for fuzzy fault tree analysis. Microelectron. Reliab., 1989, 29(2), 195-216.
9. Tanaka, H., Fan, L. T., and Lai, F. S. Fault-tree analysis by fuzzy probability. IEEE Trans. Reliab., 1983, 32(5), 453-457.
10. Zadeh, L. A. Fuzzy sets. Inf. Control, 1965, 8, 338-353.
11. Pedrycz, W. and Gomide, F. An introduction to fuzzy sets: Analysis and design complex adaptive systems, 1998 (MIT Press, Cambridge).
12. Soman, K. P. and Misra, K. B. Fuzzy fault tree analysis using resolution identity. Int. J. Fuzzy Math., 1993, 1, 193-212.
13. Zadeh, L. A. Similarity relations and fuzzy orderings. Inf. Sci., 1971, 3, 177-200.
14. Chen, G. and Fan, T. T. Introduction to fuzzy sets, fuzzy logic, and fuzzy control systems, 2001 (CRC Press, Baco Raton).
15. Wang, X., Ruan, D., and Kerre, E. E. Mathematics of fuzziness -basic issues, 2009 (Springer, Heidelberg).
16. Huang, D., Chen, T., and Wang, M. J. A fuzzy set approach for event tree analysis. Fuzzy Sets Syst., 2001, 118, 153-165.
17. Nasibov, E. N., Baskan, O., and Mert, A. A learning algorithm for level sets weights in weighted levelbased averaging method. Fuzzy Optim. Decis. Making, 2005, 4, 279-291. (Pubitemid 41456247)
18. Nasibov, E. N. and Mert, A. On methods of defuzzification of parametrically represented fuzzy numbers. Autom. Control Comput. Sci., 2007, 41(5), 265-273. (Pubitemid 350172375)
19. Nasibov, E. N. and Shikhlinskaya, R. Y. Adjustment of the parameters of WABL-aggregation for locating the centre of gravity of a polynomial-type fuzzy number. Autom. Control Comput. Sci., 2003, 37(6), 34-42. (Pubitemid 39327217)
20. Stapelberg, R. F. Handbook of reliability, availability, maintainability and safety in engineering design, 2009 (Springer, Lnodon).
21. Vesely, W., Stamatelatos, M., Dugan, J., Fragola, J., Minarick III, J., and Railsback, J. Fault tree handbook with Aerospace Applications, 2002 (NASA, Washington), version 1.1, Office of Safety and Mission Assurance.
22. Vesely, W. E., Davis, T. C., Denning, R. S., and Saltos, N. Measures of risk importance and their applications, NUREG/CR-3385, 1983 (US Nuclear Regulatory Commission, USA).
23. Cheok, M. C., Parry, G. W., and Sherry, R. R. Use of importance measures in risk-informed regulatory applications. Reliab.EngngSyst. Saf., 1998,60, 213-226. (Pubitemid 128393093)
24. Liang, G. S. and Wang, M. J. J. Fuzzy fault tree analysis using failure possibility. Microelectron. Reliab., 1993, 33, 583-597.
25. Suresh, P. V., Babar, A. K., and Venkat Raj, V. Uncertainty in fault tree analysis: A fuzzy approach. Fuzzy Sets Syst., 1996, 83, 135-141. (Pubitemid 126667497)
26. Zhang, X. and Liu, P. Method for aggregating triangular fuzzy intuitionist fuzzy information and its application to decision making. Baltic J. Sustainability, 2010, 16(2), 280-290.
27. Dong, W. M. and Wang, F. S. Fuzzy weighted averages and implementation of the extension principle. Fuzzy Sets Syst., 1987, 21, 183-199.
28. Onisawa, T. An approach to human reliability in man-machine systems using error possibility. Fuzzy Sets Syst., 1988, 27, 87-103. (Pubitemid 18653043)
29. Onisawa, T. A representation of human reliability using fuzzy concepts. Inf. Sci., 1988, 45, 153-173.
30. The statistical accident/incident bulletin, Persian calendar year 1384, The office of transportation safety and protection, Iranian Railways, 2006.
31. The statistical accident/incident bulletin, Persian calendar year 1385, The office of transportation safety and protection, Iranian Railways, 2007.
32. The statistical accident/incident bulletin, Persian calendar year 1386, The office of transportation safety and protection, Iranian Railways, 2008.
33. The statistical accident/incident bulletin, Persian calendar year 1387, The office of transportation safety and protection, Iranian Railways, 2009.
34. The Iranian Railways report on passenger train derailments during the years of 2004-2008, The office of transportation safety and protection.