Layers of Protection Analysis Using Possibility Theory
Автор: Nouara Ouazraoui, Rachid Nait-Said, Mouloud Bourareche, Ilyes Sellami
Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa
Статья в выпуске: 1 vol.5, 2012 года.
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An important issue faced by risk analysts is how to deal with uncertainties associated with accident scenarios. In industry, one often uses single values de-rived from historical data or literature to estimate events probability or their frequency. However, both dynamic environments of systems and the need to consider rare component failures may make unrealistic this kind of data. In this paper, uncertainty encountered in Layers Of Protection Analysis (LOPA) is considered in the framework of possibility theory. Data provided by reliability databases and/or experts judgments are represented by fuzzy quantities (possibilities). The fuzzy outcome frequency is calculated by extended multiplication using α-cuts method. The fuzzy outcome is compared to a scenario risk tolerance criteria and the required reduction is obtained by resolving a possibilistic decision-making problem under necessity constraint. In order to validate the proposed model, a case study concerning the protection layers of an operational heater is carried out.
LOPA, Uncertainty, Possibility Theory, Risk Reduction
Короткий адрес: https://sciup.org/15010350
IDR: 15010350
Список литературы Layers of Protection Analysis Using Possibility Theory
- L. Harms-Ringdal, Analysis of Safety Functions and barriers in accidents, Safety Science, 2009, 47: 353-363.
- Sklet S, Safety barriers: Definition, classification, and performance, J. Loss Prev. Proc. Industries, v19, 2006, pp.494-506.
- Functional Safety-Safety instrumented systems for the process industry sector, IEC 61511-Parts 1 and 3, International Electrotechnical Commission Std., 2003.
- Layer Of Protection Analysis, simplified process assessment, Simplified process risk assessment, Center for Chemical Process Safety (CCPS) of the American Institute of Chemical Engineers (AICHE), 2001.
- L. Zadeh, Outline of a New Approach to the Anal-ysis of Complex Systems and Decision Processes, IEEE Trans. Systems, Man, and Cybernetics, vol. SMC-3,1973, pp.28-44.
- A.S. Markowski, M.S. Mannan, A. Kotynia, D. Siuta, Uncertainty aspects in process safety analy-sis, J. Loss. Prev. Proc. Industries, v23, 2010, pp.446-454.
- W.K. Muhlbauer, Pipeline risk management manu-al: Ideas, techniques and resources, 3rd ed., Else-vier InC, 2004.
- A.M. Dowell, D.C. Hendershot, Simplified Risk Analysis-Layers of Protection Analysis, presented at the National Meeting of the American Institute of Chemical Engineers, Indianapolis, Nov. 3-8, Pa-per 281a, 2002.
- J.B. Bowles, C.E. Pelaez, Application of Fuzzy logic to Reliability Engineering, Proceedings of the IEEE, v83, 1995, pp.435-449.
- M.H. Chun, K.I. Ahn, Assessment of the potential applicability of fuzzy set theory to accident pro-gression event trees with phenomenological uncer-tainties, Reliab. Eng. System Safety, v37, 1992, pp.237-252.
- R. Kenarangui, Event tree Analysis by fuzzy prob-ability, IEEE Trans. on Reliab., v40, 1991, pp.120-124.
- Markowski A S, Mannan M S, Fuzzy logic for pip-ing risk assessment (pfLOPA), J. Loss. Prev. Proc. Industries, v22, 2009, pp.921-927.
- Guidelines for Process Equipment Reliability Data With Data Tables, Center for Chemical Process Safety (CCPS) of the American Institute of Chemi-cal Engineers (AIChE), 1989.
- IEEE Guide to the Collection and Presentation of Electrical, Electronic, Sensing Component, and Mechanical Equipment Reliability Data for Nucle-ar-Power Generating Station, IEEE-Std-500, 1984.
- Offshore Reliability Data Handbook, 4th ed. Off-shore Reliability Data (OREDA), 2002.
- M. Abrahamsson, Uncertainty in Quantitative Risk Analysis-Characterisation and Methods of Treat-ment, Department of Fire Safety Engineering, Lund University, Report n1024, 2002.
- L.A. Zadeh, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Syst., v1, 1978, pp.3-28.
- D. Dubois and H. Prade, Possibility Theory. New York: Plenum, 1988.
- S. Murè, M. Demechela, Fuzzy Application Proce-dure (FAP) for the risk assessment of occupational accidents, J. Loss. Prev. Proc. Industries, v22, 2009, pp.593-599.
- H. Tanaka, L.T. Fan, F.S. Lai, K. Toguchi, Fault-Tree Analysis by Fuzzy Probability, IEEE Trans. on Reliab., vol. R-32, 1983, pp.453-457.
- C. Wei, W.J. Rogers, M.S. Mannan, Layer of pro-tection analysis for reactive chemical risk assess-ment, J. Hazard. Materials, v159, 2008, pp.19-24.
- E.M. Marszal, E.W. Scharpf, Safety Integrity Level selection-Systematic Methods Including Layer of Protection Analysis. The Istrumentation, Systems, and Automation Society (ISA), 2002.
- Guidelines for Developing Quantitative Safety Risk Criteria, Center for Chemical Process Safety (CCPS) of the American Institute of Chemical En-gineers (AIChE), 2009.
- Reducing Risks, Protecting People - HSE ’s Deci-sion-making Process, Health and Safety Executive (HSE), Her Majesty’s Stationery Office, London, 2001.
- Guidelines for Chemical Process Quantitative Risk Analysis, 2nd ed. Center for Chemical Process Safety (CCPS) of the American Institute of Chemi-cal Engineers (AIChE), 2000.
- F.P. Lees, Loss Prevention in the Process Industries. 2nd ed., vol.1, Butterworth-Heinmann, Ox-ford,1996.
- M. Sallak, C. Simon, J.F. Aubry, A Fuzzy Proba-bilistic for Determining Safety Integrity Level, IEEE Trans. on Fuzzy Syst., v16, 2008, pp.239-248.
- L.A. Zadeh, Fuzzy sets, Information and Control, v8, 1965, pp.338-353.
- R. Nait-Said, F. Zidani, N. Ouazraoui, Modified risk graph method using fuzzy-rule-based approach, J. Hazard. Materials, v164, 2009, pp.651-658.
- Zadeh L A, The concept of a linguistic variable and its application to approximate reasoning, Parts I and II, Information Sciences, v8, 1975, pp. 199-249, 301-357.
- A. Kaufman, M.M. Gupta, Introduction to Fuzzy Arithmetic Theory and Application. 1991, New York: Van Nostrand Reinhold.
- G. Bortolan, R. Degani, A review of some methods for ranking fuzzy substs, Fuzzy Sets and Syst., v15,1985, pp.1-19.
- D. Dubois, H. Prade, A unified view of ranking techniques for fuzzy numbers, Proceedings of the IEEE Conf. on Fuzzy Systems, v3, 1999, pp.1328-1333.
- D. Dubois, H. Prade, Ranking Fuzzy Numbers in the Setting of Possibility Theory, Information Sci-ences, v30, 1983, pp.183-224.
- R.E. Bellman, L.A. Zadeh, Decision-Making in a Fuzzy Environment, Management Science, v17, 1970, pp141-164.
- E. Muela, G. Schweickardt, F. Garcés, Fuzzy pos-sibilistic model for medium-term power generation planning with environmental criteria, Energy Policy, v35, 2007, pp.5643-5655.
- Inuiguchi M, Ramik J, Possibilistic linear pro-gramming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem, Fuzzy Sets and Syst., v111, 2000, pp.3-28.
- Das B, Maity K, Maiti M, A two warehouse sup-ply-chain model under possibil-ity/necessity/credibility measures, Mathematical and Computer Modelling, v46, 2007, pp.398-409.
- Methodology for Layer Of Protection Analysis, SONATRACH Company, Hassi-R’Mel, Rep. S-30-1240-140, 2007.
- Notebooks of Industrial Safety: Frequencies of accident initiating events, Institute for a Culture in Industrial Safety (ICIS), 2009, Available: http://www.icsi-eu.org/
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