## 5 Research Questions
To better understand why researchers have been focusing more on fuzzy logic, we can present a table of method distribution. This table (Table 7) can help readers to more easily search and match authors with their respective problem-solving models. From the table, it becomes clear that certain fuzzy logic methods are encountered in all or most fields of risk assessment applications. One such method is the AHP. The Analytic Hierarchy Process (AHP) is a popular decision-making tool that helps to prioritize and select alternatives based on multiple criteria. When combined with fuzzy logic, it becomes particularly useful in risk assessment by addressing the inherent uncertainty and ambiguity in human judgment. Another method that appears in most fields is FTA. Fault \begin{table}
\begin{tabular}{l l l} \hline \hline
**Field** & \multicolumn{1}{c}{**Subcategory**} & \multicolumn{1}{c}{**Publication**} \\ \hline
**Industry** & AHP & [125,126] \\  & FTA & [127,128,129] \\  & Bowtie & [32] \\  & AFRA & [124] \\  & FMEA & [130,131,132] \\  & Monte Carlo & [30,133] \\  & LOPA & [134] \\  & FAP & [21] \\  & FCE & [135] \\  & FCM & [120] \\  & FHWI & [136] \\  & QRA & [96,137,138] \\  & PRAT & [139] \\
**Transportation** & AHP & [118,122] \\  & CART & [19] \\  & CREAM & [75] \\  & FTA & [140] \\  & FMEA & [141,142,143], \\  & FFTA & [123,144] \\  & FBN & [145] \\  & IVIS & [146] \\
**Construction** & AHP & [147] \\  & DEMATEL & [148] \\  & LSRA & [149] \\  & QRA & [150] \\  & ORCA & [151] \\
**Mines** & AHP & [100] \\  & FRA & [152] \\  & SPA & [103] \\  & IVFN & [153] \\
**Medicine** & AHP-TOPSIS & [64] \\  & MCDM & [154] \\
**Environment** & AHP & [155] \\  & ECI & [40] \\
**Oil and gas** & FMEA & [79] \\
**All fields** & BN & [156] \\  & CREAM & [39,75,78,157] \\  & FMEA & [141,158] \\  & FMEA & [159] \\  & FTA & [88,158,160] \\  & TOPSIS & [161,162] \\  & HRA & [163] \\  & LOPA & [106,164] \\  & MCDM & [165] \\  & QFD & [37] \\
**University Chemistry** & FMEA & [166] \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Model solutions by various authors across professional fields. Tree Analysis (FTA) is a widely used technique for analyzing the causes of system failures and assessing risk in various fields. When combined with fuzzy logic, FTA can effectively handle uncertainty and ambiguity in risk assessment, making it a powerful tool for complex decision-making processes. The same applies to other methods that appear in most fields, such as QRA, FMEA, and TOPSIS [167]. 2. Into what subcategories can the four techniques be divided, and what problems do they solve in risk assessment? As shown in the table from the previous research question, it is not the use of the technique itself but a subcategory of it that is usually referred to by the authors as a model or protocol. In this research question, the goal is to not only present the subcategory but also explain what it solves in risk assessment. Specifically, the AHP model, when combined with fuzzy logic [168], can be used for emergency planning in the industry [169] and to prevent risks throughout the life cycle of a renewable energy source, specifically a wind turbine [170]. Furthermore, the model identifies the primary cause of accidents in mining environments and can assess risk in construction projects [125]. Additionally, the subcategory of the FTA method is also important, which, when combined with fuzzy logic and neural networks, provides significant results in risk assessment and safety assurance. Specifically, it prevents unwanted events that cause catastrophic accidents in gas facilities [171], is applied in oil storage tank zones [127], and prevents fires during production in oil tanks [128]. Moreover, it prevents accidents at intersections caused by human error [134], supports decision-making on highways, and ensures risk avoidance in marine transport by identifying qualitative and quantitative uncertainties [102]. Another method commonly combined with fuzzy logic is FMEA.