Research Article
Assessing the Risks of Airport Airside through the Fuzzy Logic-Based Failure Modes, Effect, and Criticality Analysis
Table 10
Evaluation to a fuzzy conclusion-example.
| | Rule no. | Probability (d. m.) | Severity (d. m.) | Detectability (d. m.) | Risk | Min. membership |
| | Rule N | Low (0.24) | Low (0.03) | Low (0.17) | Low | μ (low risk) = 0.03 | | Rule N | Low (0.24) | Low (0.03) | Moderate (0.11) | Low | μ (low risk) = 0.03 | | Rule M | Low (0.24) | Moderate (0.26) | Low (0.17) | Moderate | μ (moderate risk) = 0.17 | | Rule M | Low (0.24) | Moderate (0.26) | Moderate (0.11) | Moderate | μ (moderate risk) = 0.11 | | Rule I | Moderate (0.2) | Low (0.03) | Low (0.17) | Moderate | μ (moderate risk) = 0.03 | | Rule J | Moderate (0.2) | Low (0.03) | Moderate (0.11) | Low | μ (low risk) = 0.03 | | Rule G | Moderate (0.2) | Moderate (0.26) | Low (0.17) | High | μ (high risk) = 0.17 | | Rule H | Moderate (0.2) | Moderate (0.26) | Moderate (0.11) | Moderate | μ (moderate risk) = 0.11 |
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d. m.: degree of membership.
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