Abstract
This is a forward-looking approach that uses a multiple-criteria decision analysis (MCDA) model as an assessment tool for risk identification. This study proposes an indifference threshold-based attribute ratio analysis and technique for order preference by similarity to an ideal solution (ITARA-TOPSIS)-based assessment model to identify critical failure modes in products and systems. The improved indifference threshold-based attribute ratio analysis (ITARA) method can generate more reliable weights for risk factors. In addition, the modified technique for order preference by similarity to an ideal solution (TOPSIS) is used to obtain the risk levels of the failure modes. The gray correlation coefficient is applied to replace the conventional Euclidean distance, and a new index is used to determine the priority of failure modes. The determination of risk factors is based on the failure mode and effect analysis (FMEA) theory, including severity, occurrence, and detection. An important indicator, the expected cost, is also included in the framework. The case of a steam turbine for a nuclear power plant is used to demonstrate the approach, and the analysis results show that the proposed model is practical and effective. Moreover, the advantages of our integrated model are illustrated through model comparisons and sensitivity analysis. This paper can help decision-makers, risk engineers, and related researchers to better understand how a systematic risk assessment can be conducted.
Highlights
Risk assessment has grown into a separate scientific field over the course of about40 years, with the establishment of principles, theories, and methods for how to conceptualize, manage, and assess risk
We propose a novel multiple-criteria decision analysis (MCDA) risk analysis model that integrates the improved indifference threshold-based attribute ratio analysis (ITARA) method and the modified TOPSIS technique
The TOPSIS is effective for dealing with this type of problem because it explores the distance between each failure mode and the PIS and NIS when determining the priority for improvement
Summary
Risk assessment has grown into a separate scientific field over the course of about. 40 years, with the establishment of principles, theories, and methods for how to conceptualize, manage, and assess risk. The current MCDA follows an important trend in the development of risk assessment technology, that being to develop faster, more effective, and more reliable analysis models for determining the risk factor weights and sorting the failure modes. ITARA with TOPSIS to formulate the risk analysis model; This study improves the original ITARA method to more effectively identify critical risk factors and generate more reliable weights. The quality and efficiency of the solution obtained from the proposed model are not affected by the amount of data; The results of the sensitivity analysis of weight changes for the improved ITARA method indicate that this MCDA model has the robustness for practical applications.
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