Abstract
Fire safety in healthcare facilities is extremely important due to limited evacuation capacity of occupants. Therefore, poor fire safety precautions lead to more fatalities and financial losses. This study introduces an effective fire risk management approach for healthcare buildings utilizing an interval valued neutrosophic-fuzzy framework. This framework identifies fire risks and determine appropriate safety measures. In addition, essential fire risk criteria in healthcare centers were systematically identified through a multi-factor decision-making process, employing the Fuzzy-Delphi technique and a comprehensive literature review. The proposed framework initially determines the importance weights of these factors using the Interval Valued Neutrosophic-Analytical Hierarchy Process (IVN-AHP). Subsequently, three main parameters - Potential Risk Level (PRL), Acceptance Risk Level (ARL) and Protection Level (PL) - were calculated as alternatives in IVN-AHP technique using novel mathematical equations. A fuzzy inference system (FIS) was then employed to estimate the risk magnitude and subsequently classify departments within the healthcare building based on their risk level. The fire risk control strategy is then determined based on this risk classification. The proposed approach was applied to departments within a hospital in Iran. Its validity was evaluated by comparing the results with the comprehensive Fire Risk Assessment Method for Engineering (FRAME) technique. Additionally, the sensitivity of the IVN-AHP in determining the weights of factors and alternatives was validated using real data. The results revealed that the utilities and kitchen departments exhibited a critical risk class exceeding 50%. Furthermore, the operating room, laundry, post-NICU 1 and 2, and waste disposal were classified as critical, with more than 50% falling within the major risk class. A strong correlation coefficient of 99.1% was observed between the Fire Risk Magnitude (FRM) obtained using the proposed farmwork and the FRM for occupants obtained using the FRAME technique. These findings demonstrate the applicability and reliability of the proposed approach as a valuable tool for risk management and decision-making in healthcare facilities.
Published Version
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