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Developing a hybrid risk assessment method for prioritizing the critical risks of temporary accommodation sites after destructive earthquakes

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Abstract

One of the most critical challenges in preventive planning and disaster management is the multitudinous uncertainties involved in decision-making. Previous studies showed the usefulness of intuitionistic fuzzy sets for considering uncertainties in decision-making process. Hence, the current study aims to present a combined model using Intuitionistic Fuzzy Sets and Risk Failure Mode and Effects Analysis (IF-RFMEA) to determine and prioritize the critical risks of temporary accommodation sites after destructive earthquakes in Iran and bridge the existing research gaps in the literature. To this end, 49 common temporary accommodation risks after earthquakes were identified via a desktop literature survey. Then, the fuzzy Delphi technique was applied to determine the top 20 critical risks with the highest priorities according to experts for evaluation using the proposed method. The Delphi panel members included 18 experts based in Iran with relevant hands-on experience in crisis management and risk management. Finally, 20 identified critical risks were evaluated using three criteria of the probability of occurrence, level of effect, and detection value using the IF-RFMEA technique. According to the analytical results, infectious disease challenges, mental and psychological disorders among survivors, and unemployment and closing of businesses, were the most critical risks after earthquakes in the region. The proposed method of analysis can diminish uncertainties and adopt the main criteria of the probability of occurrence, level of effect, and detection value to improve risk assessment results and analysis in relation to the critical risks of temporary accommodation sites after destructive earthquakes.

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Describes a new technique for prioritizing failures for corrective actions in failure mode and effects analysis (FMEA). This technique extends the risk prioritization beyond the conventional risk priority number (RPN) method. A new scale has been defined. The ranks 1 through 1,000 are used to represent the increasing risk of the 1,000 possible severity-occurrence-detection combinations, called risk priority ranks (RPRs). The failures having a higher rank are given higher priority. This approach resolves some of the shortcomings in the traditional RPN technique. Traditionally, FMEA identifies the risk associated with a product failure through assignment of a standard RPN. A fundamental problem with FMEA is that it attempts to quantify risk without adequately quantifying the factors that contribute to risk. In particular cases, RPNs can be misleading. This deficiency can be eliminated by using the new technique. A methodology combining the benefits of matrix FMEA and the new technique as stated above is presented.