Application of fuzzy logic to reliability engineering

Bowles, J.B.; Peláez, Enrique

doi:10.1109/5.364489

Cited by 125 publications

(92 citation statements)

References 16 publications

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“…[8]. However, the triangular and trapezoidal MFs are the most frequently used in safety risk analysis practice [1][2][3][11][12][13].…”

Section: Fuzzy Sets and Membership Functionsmentioning

confidence: 99%

“…The centroid of area method, which determines the centre of gravity of an aggregated fuzzy set, is the most frequently used method in the fuzzy reasoning systems [3,8,11,13,23], defined as…”

Section: Defuzzificationmentioning

confidence: 99%

“…The RL of a failure event in the railway safety risk analysis is determined by two risk factors, i.e. FP and CS of a failure or hazard event [2,4,6,12,13,15,16,25,26].…”

Section: A Railway Safety Risk Assessment Modelmentioning

confidence: 99%

“…Their MF parameters are chosen according to WRA values [16,17] and listed in Table 2. The fuzzy set of RL in terms of qualitative descriptors is defined as Low, Possible, Substantial and High [3,12,13,15,16]. Their definitions are generally similar to those described in EN50126, EN50129, and GE/GN8561 [5,24,27] are listed in Table 3.…”

Section: Qualitative Descriptorsmentioning

confidence: 99%

“…Furthermore, in many situations, the data of probability of failure of a system do not exist and it must be estimated based on the expert knowledge and experience or engineering judgement from similar items. In this context, a safety risk model using fuzzy reasoning-based approach may be more appropriate to analyse the risks of the system where there is incomplete safety risk information [3,12,13]. A fuzzy reasoning approach allows imprecision or approximate information in its analysis process, which helps to restore integrity to safety risk analysis.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An Intelligent Railway Safety Risk Assessment Support System for Railway Operation and Maintenance Analysis

An¹,

Lin²,

Huang³

2013

TOTJ

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Abstract:The paper presents the development of an intelligent railway safety risk assessment based support system. The proposed method can evaluate qualitative and quantitative safety risk data and information in a uniform manner for railway safety risk assessment. It permits the safety risk analysts to assess the risks associated with the failure modes directly using linguistic terms, i.e. qualitative descriptors. The proposed intelligent railway safety risk assessment system is capable of assessing the risks at component level, sub-system level and system level. It can assess not only "hard" risks (e.g. risks of a system), but also "soft" risks (e.g. staff risks). The outcomes of safety risk assessment are represented in two formats, risk score and risk category with a belief of percentage, which provide very useful safety risk information to railway designers, operators, engineers and maintainers for risk response decision making. An illustrative example of staff risk assessment in a railway depot is used to demonstrate the proposed intelligent railway safety risk assessment system. The results indicate that by using the proposed system, risks associated with a railway depot can be assessed effectively and efficiently.

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“…[8]. However, the triangular and trapezoidal MFs are the most frequently used in safety risk analysis practice [1][2][3][11][12][13].…”

Section: Fuzzy Sets and Membership Functionsmentioning

confidence: 99%

Section: Defuzzificationmentioning

confidence: 99%

“…The RL of a failure event in the railway safety risk analysis is determined by two risk factors, i.e. FP and CS of a failure or hazard event [2,4,6,12,13,15,16,25,26].…”

Section: A Railway Safety Risk Assessment Modelmentioning

confidence: 99%