Modified risk graph method using fuzzy rule-based approach

Nait-Said, Rachid; Zidani, F.; Ouzraoui, N.

doi:10.1016/j.jhazmat.2008.08.086

Cited by 27 publications

(23 citation statements)

References 24 publications

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“…in some uncertainty in a safety system. However, in view of the latest research [1], the assessment of safety integrity for determining quantitative risk indicators was not performed [4] to the full extent, as the advantage is given to qualitative information and its comprehensive analysis [1]. In this case, various methods and standards [5], such as Program Evaluation and Review Technique, Monte Carlo and others are used [1].…”

Section: сформульовано задачI дослIдження запропонована теоретична Imentioning

confidence: 99%

Construction of methods for ensuring the required level of safety integrity in the automated systems of control over technological processes

Vitalii

Baturin

Lyfar

et al. 2019

EEJET

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Section: сформульовано задачI дослIдження запропонована теоретична Imentioning

confidence: 99%

Construction of methods for ensuring the required level of safety integrity in the automated systems of control over technological processes

Vitalii

Baturin

Lyfar

et al. 2019

EEJET

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“…This transformation seems to offer the average value of a fuzzy interval as an inverse problem. In front of this situation, we have taken as reference the recent work of Nait-Said et al [6]. In this work, the authors propose below equations derived by considering the transformation of an ordinary interval of borders E * and E * in a fuzzy interval "Q" likewise the inverse problem determining the average value a fuzzy interval.…”

Section: Development Of the Fuzzy Scalesmentioning

confidence: 99%

Criticality assessment risk; contribution of fuzzy logic

Masmoudi

Dhiaf²

2018

YUGOSLAV J OPERATION

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In order to determine the criticality of a risk, an assessment of the probability of occurrence (notion of frequency) and of the impact (notion of severity) are to be estimated. The criticality is the product of the probability of its occurrence and the impact that the risk has on the project, hence on the whole company. So, the practice of matrix or the criticality grid considering these two dimensions is necessary. However, the criticality grid involves the insufficiencies inherent to the subjective behavior of expert judgments and to the imprecise information engaged in the assessment of the risk. Taking into account the problems of the imperfection implied in the Conventional Criticality Matrix (CCM), the objective of this work is to develop a Fuzzy Criticality Matrix (FCM) to overcome these difficulties. The proposed model aims at improving the system of fuzzy inference. The proposed approach is applied to a test system which is the company SAROST S.A.

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“…Fuzzy set theory [28] has emerged as a very appropriate tool in dealing with uncertainty in reliability and safety analysis. Several fu zzy models concerning fau lt tree analysis (FTA), event tree analysis (ETA), failure mode, effects and criticality analysis (FM ECA), risk graph method, ... have been developed to deal with the behaviour of systems which are too co mplex o r too illdefined to ad mit of conventional quantitative techniques [9][10][11], [20,29]. Imperfect data are dealt with in a natural and flexib le way by using fu zzy ru les -based systems and/or fuzzy arithmetic.…”

Section: Fuzzy Lopa Modelmentioning

confidence: 99%

Layers of Protection Analysis Using Possibility Theory

Ouazraoui¹,

Nait-Said²,

Bourareche³

et al. 2012

IJISA

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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 derived fro m 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 (possibilit ies). The fu zzy outcome frequency is calculated by extended mu ltip licat ion using αcuts method. The fu zzy outcome is co mpared 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.

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Modified risk graph method using fuzzy rule-based approach

Cited by 27 publications

References 24 publications

Construction of methods for ensuring the required level of safety integrity in the automated systems of control over technological processes

Construction of methods for ensuring the required level of safety integrity in the automated systems of control over technological processes

Criticality assessment risk; contribution of fuzzy logic

Layers of Protection Analysis Using Possibility Theory

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