Fuzzy Set Theory

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Abstract

Chemical process industries (CPI) handling hazardous chemicals in bulk can be attractive targets for deliberate adversarial actions by terrorists, criminals and disgruntled employees. It is therefore imperative to have comprehensive security risk management programme including effective security risk assessment techniques. In an earlier work, it has been shown that security risk assessment can be done by conducting threat and vulnerability analysis or by developing Security Risk Factor Table (SRFT). HAZOP type vulnerability assessment sheets can be developed that are scenario based. In SRFT model, important security risk bearing factors such as location, ownership, visibility, inventory, etc., have been used. In this paper, the earlier
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It is difficult to obtain the quantitative data due to numerous constraints such as rare occurrence of the events, human subjectivity and economic considerations. Even if the data is available, it is often inaccurate or subject to uncertainty. Thus, it is difficult to establish rational database for safety and security considerations. Fuzzy set theory can provide a framework for handling such subjectivity and uncertainty associated with the data. Zadeh [11] initiated the fuzzy set theory. Bellman and Zadeh [12] presented some applications of fuzzy theories to the various decision making processes of fuzzy environment. Fuzzy logic has been applied to solve many real world problems where fuzziness exists. The potential of using fuzzy sets theory in treating different sources of uncertainty has been acknowledged in the literature [13], [14] and [15]. Several authors make use of fuzzy set theory to tackle uncertainties in risk and security decision making. Pelaez and Bowles [16], Bowles and Pelaez [17], Cai [18], Moss and Woodhouse [19], Braglia et al. [20], and Sharma et al. [21] suggested the use of fuzzy logic theory for the risk criticality analysis and risk priority number (RPN) evaluation. The basic fuzzy concepts are outlined briefly in later…show more content…
In the modified SRFT model, two linguistic fuzzy scales (three-point and four-point) have been devised based on trapezoidal fuzzy numbers. Human subjectivity of different experts associated with previous SRFT model is tackled by mapping their scores to the newly devised fuzzy scale. Finally, the fuzzy score thus obtained is defuzzyfied to get the results. A test case of a refinery has been taken to compare the results of both the models. The total risk score obtained using previous SRFT model was ‘40’. The modified SRFT model gives ‘38.08’. The final risk score suggests it is a high risk facility and therefore demands serious security attention. The refinery X should go through detailed security and vulnerability assessment and initiate aggressive risk reduction exercise in coordination with the local law enforcement agencies. Comparing the results of both the models, minor variations are observed due to human (experts) subjectivity involved in assigning scores. However, the results may vary significantly if we take another test

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