Nash equilibrium-based FMEA for risk prioritization in hydrogen refueling station design

This chapter focuses on developing a modified Failure Mode and Effect Analysis (FMEA) method for prioritising potential failure modes in the design stage of hydrogen refuelling stations, explicitly targeting the liquid hydrogen storage (Dewar) system. The conventional FMEA method is widely used but has limitations, such as equal importance weights for risk factors, limited consideration of risk factors, and static risk assessment. To address these shortcomings, a new approach based on the “Nash equilibrium” concept is proposed. The proposed method incorporates the perspectives of multiple decision-makers (DMs) who assess the risk factors associated with each failure mode using Pythagorean fuzzy uncertain linguistic variables. Payoff matrices are constructed based on the assessments provided by the DMs, representing a zero-sum game between failure and success. The FMEA process is then formulated as a combination of game theory and risk assessment, aiming to prioritise failure modes for intervention actions. To demonstrate the application of the proposed method, a case study of the liquid hydrogen storage (Dewar) system in a hydrogen refuelling station is presented. Failure modes are identified, and their severity, occurrence, and detection are assessed. The risk priority number (RPN) is calculated for each failure mode based on the proposed method, enabling the prioritisation of failure modes for appropriate intervention actions. The proposed FMEA method offers several advantages over the conventional approach. It allows for unequal importance weights of risk factors, incorporates a comprehensive set of risk factors, avoids the issue of different combinations producing the same RPN, and provides a systematic framework for considering the dynamic nature of risk assessment over time. By integrating game theory principles and FMEA, this study offers a novel perspective on risk prioritisation in the design stage of hydrogen refuelling stations. The proposed method provides a more comprehensive and flexible approach to assessing and prioritising failure modes, contributing to developing safer and more reliable hydrogen infrastructure.