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1- Department of Maritime Engineering, Amirkabir University of Technology, Tehran, Iran
Abstract: (35 Views)
Traditional Lenjes operating in coastal regions face significant navigational risks due to dense maritime traffic, complex geography, and mixed traditional-modern navigation practices. While Failure Mode and Effects Analysis (FMEA) is widely used for risk assessment, its reliance on the Risk Priority Number (RPN) suffers from limitations, especially when multiple failure modes share identical RPNs. This study proposes an integrated methodology combining FMEA with the CRiteria Importance Through Intercriteria Correlation (CRITIC) and COmbinative Distance-based ASsessment (CODAS). CRITIC objectively weights criteria (Severity, Occurrence, Detection) using variability and inter-correlations, minimizing subjectivity. CODAS then prioritizes failure modes using Euclidean and Manhattan distances from a negative ideal solution. Sensitivity analysis confirms the framework’s robustness. Results demonstrate that the FMEA-CRITIC-CODAS approach effectively enhances risk assessment for Lenjes, providing actionable insights for navigational safety. The framework is adaptable to other complex systems requiring accurate risk prioritization.
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Highlights
1. Objective Weighting via CRITIC: The integration of the CRITIC method allows for the objective determination of weights for FMEA risk factors (severity, occurrence, detection) based on the contrast intensity and conflict between criteria derived from actual assessment data, reducing subjectivity in the evaluation process.
2. Enhanced Ranking with CODAS: The CODAS method, which uses both Euclidean and Manhattan distances from the negative-ideal solution, provides a more robust and discriminating ranking of failure modes, especially in complex decision environments with conflicting criteria.
3. Application in a Novel Context: The methodology is applied to assess navigational risks in traditional Lenj vessels operating in coastal regions—a context that has not been widely addressed in the literature. This demonstrates the adaptability of the integrated approach to traditional maritime operations where modern and indigenous navigation practices coexist.
4. Improved Risk Discrimination and Stability: The proposed model effectively resolves the issue of tied or near-identical RPN values among different failure modes, offering clearer prioritization. The study also includes a comparative and sensitivity analysis, confirming the stability and reliability of the results.
By integrating MCDM techniques like CRITIC and CODAS into FMEA, this article advances the state-of-the-art in risk assessment methodologies, offering a more systematic, data-driven, and effective approach for identifying and prioritizing critical failure modes in safety-sensitive domains. This represents a significant improvement over previous fuzzy, linguistic, or hybrid models by enhancing objectivity, computational efficiency, and practical applicability.
1. Objective Weighting via CRITIC: The integration of the CRITIC method allows for the objective determination of weights for FMEA risk factors (severity, occurrence, detection) based on the contrast intensity and conflict between criteria derived from actual assessment data, reducing subjectivity in the evaluation process.
2. Enhanced Ranking with CODAS: The CODAS method, which uses both Euclidean and Manhattan distances from the negative-ideal solution, provides a more robust and discriminating ranking of failure modes, especially in complex decision environments with conflicting criteria.
3. Application in a Novel Context: The methodology is applied to assess navigational risks in traditional Lenj vessels operating in coastal regions—a context that has not been widely addressed in the literature. This demonstrates the adaptability of the integrated approach to traditional maritime operations where modern and indigenous navigation practices coexist.
4. Improved Risk Discrimination and Stability: The proposed model effectively resolves the issue of tied or near-identical RPN values among different failure modes, offering clearer prioritization. The study also includes a comparative and sensitivity analysis, confirming the stability and reliability of the results.
By integrating MCDM techniques like CRITIC and CODAS into FMEA, this article advances the state-of-the-art in risk assessment methodologies, offering a more systematic, data-driven, and effective approach for identifying and prioritizing critical failure modes in safety-sensitive domains. This represents a significant improvement over previous fuzzy, linguistic, or hybrid models by enhancing objectivity, computational efficiency, and practical applicability.
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