JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Study of SIL Allocation with a Multi-Phase Fuzzy Risk Graph Model
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Study of SIL Allocation with a Multi-Phase Fuzzy Risk Graph Model
Yang, Heekap; Lee, Jongwoo;
  PDF(new window)
 Abstract
This paper introduces a multi-phase fuzzy risk graph model, representing a method for determining for SIL values for railway industry systems. The purpose of this paper is to compensate for the shortcomings of qualitative determination, which are associated with input value ambiguity and the subjectivity problem of expert judgement. The multi-phase fuzzy risk graph model has two phases. The first involves the determination of the conventional risk graph input values of the consequence, exposure, avoidance and demand rates using fuzzy theory. For the first step of fuzzification this paper proposes detailed input parameters. The fuzzy inference and the defuzzification results from the first step will be utilized as input parameters for the second step of the fuzzy model. The second step is to determine the safety integrity level and tolerable hazard rate corresponding to be identified hazard in the railway industry. To validate the results of the proposed the multi-phase fuzzy risk graph, it is compared with the results of a safety analysis of a level crossing system in the CENELEC SC 9XA WG A0 report. This model will be adapted for determining safety requirements at the early concept design stages in the railway business.
 Keywords
Risk graph;SIL(Safety Integrity Level);Fuzzification;Fuzzy Inference;Defuzzification;
 Language
Korean
 Cited by
 References
1.
H. Yang, J. Lee (2016) A study on the SIL allocation for signalling function with the fuzzy risk graph, Journal of the Korean Society for Railway, to be published.

2.
IEC (1997) 61508-5, Functional safety of electrical/electronic programmable electronic safety-related systems Part5, Geneva, pp. 21- 30.

3.
IEC (2003) 61511-3, Functional safety - Safety instrumented systems for the process industry sector- Part3: Guidance for the determination of the required safety integrity levels, Geneva, pp. 33-35.

4.
IEC (2002) 62278, Railway Applications-Specification and Demonstration of Reliability, Availability, Maintainability and Safety(RAMS), Geneva, pp 49-53.

5.
E. Marzal and E. Scharpf (2002) Safety Integrity Selection, The instrumentation, System and Automation Society, pp. 5-28.

6.
Engineering Safety Management(The Yellow Book) (2007) Fundamental and Guidance, Railtrack, Vol. 1&2, NY, pp.198-206.

7.
Didier Dubois and Henri Prade (1987) The Mean Value of Fuzzy Number. Fuzzy Sets and Systems, 24(3), pp. 79-300. crossref(new window)

8.
IRSE (2009) Validation of a semi-quantitative approach for railway risk assessments, IRSE NEWS Issue147, Geneva, pp. 8-11.

9.
Korea Transportation Safety Authority (2014) The estimated standard of risk and application plan, Seoul, p. 8.

10.
Safe Prod (2005) Process hazard and risk analysis Risk graph matrix, Process Industry IEC 61511, Geneva, pp. 1-5.

11.
PD CLC/TR (2007) 50451, Railway applications Systematic allocation of safety integrity requirements, Annex B, London, pp. 67-76.