## 2 The Framework of the Study
The Statistical analysis method for the HFACS framework is also an effective method to mine data law. [PERSON] et al. [34] counted 368 causal factors in the HFACS framework in maritime shipping and found that the technical environment had the highest frequency and identified it as a prerequisite in the preconditions for the unsafe acts category. [PERSON] et al. [35] used the HFACS framework to calculate the proportion of causal factors in marine accidents in the UK and found that the hidden conditions of accidents account for 72% of the total. [PERSON] et al. [36] conducted a frequency analysis of the risk factors in the HFACS framework of nuclear power plants and found that there are potential hazards of insufficient employee knowledge and insufficient training among the organizational factors. In this stage, through the construction of the HFACS framework, the HOFs related to EMAs can be analyzed and classified into the corresponding levels of HFACS. The total frequency of these factors can be counted, and traditional statistical analysis also can be performed. Figure 1: The framework of the study. 4. Fault Tree Modeling. FTA originated from the aerospace industry and was adapted by the nuclear power plant industry to qualify and quantify the risks [37]. FTA is a technique widely used to assess the safety and reliability of safety-critical systems, such as the analysis of tunnel boring machine accident [38], the risk assessments of collision and grounding accidents [39], and the fire risk assessment in the natural gas industry [40]. The typical FT consists of TE, BEs, IEs, and gates. TE is the root of the FT; BEs are the leaves of the acyclic graph, which cannot be decomposed anymore; IEs are represented by BEs and other IEs through a combination of logic gates; gates usually refers to Boolean connectors, AND and OR are used most frequently. In this stage, the HOFs of EMAs analyzed by the HFACS are converted into main elements to construct a fault tree. The main elements of a fault tree can be classified as TE, BEs, and IEs [41; 42]. The FTA method is used to determine the relationships between the HOFs in the system [43]. 1. Fuzzy aggregation analysis. It is often difficult to accurately and quantitatively analyze the failure probability of systems and components. In other words, a crisp method is difficult to convey the inaccurate or vague nature in system modeling to express the failure rate of system components [44]. In this case, therefore, an approximate estimate may be required. Fuzzy set theory, introduced by [PERSON] in 1965 [45], is a rigorous mathematical framework for the precise and rigorous study of fuzzy conceptual phenomena and is well suited to deal with fuzzy relations, fuzzy criteria, and fuzzy phenomena [46]. [PERSON] et al. [47] pioneered the study of the use of fuzzy set theory in FTA, treating the probability of BE as a trapezoidal fuzzy number and applying the principle of fuzzy expansion to determine the probability of TE. In response to this work, further research was carried out by [PERSON] et al. [48] to give other forms of FFTA. Subsequently, variants of FFTA have been widely used in accident analysis, for example in the petrochemical process industry [49], in power transmission grids [50], and in combustion engineering reactor protection systems [51]. In this step, a FFTA model is also used with a fuzzy algorithm called Fuzzy aggregation analysis. The purpose of this stage is to fuzzify, aggregate, and defuzzify the expert's linguistic assessments of EMAs' BEs to obtain the failure probability of the BEs. Then, according to the logical relationship between the failure probability of BE, the failure probability of EMAs' TE is derived [52]. 1. Ranking the MCSs of FT. A cut set (CS) is a group of one or more BEs. The MCS is a CS without any further simplification and is the shortest path that constitutes TE. Therefore, the analysis of MCSs can help researchers gain insight into the importance of each possible pathway of the TE occurrence [53]. 2. Analysis and evaluation of the effects.