# Risk Assessment of Lift-Jacking Accidents Using FFTA-FMEA
## 2 Literature Review
### FftA, FMEA Theory Review  
Among the classical risk identification techniques, FTA uses a deductive modelling approach that enables effective fault research to be carried out to trace the causes of a given event. FTA is already widely used in industry as a safety and reliability analysis system. [PERSON] developed a new method for power system reliability analysis using FTA, which allows qualitative and quantitative determination of the reliability of the power system [9]. [PERSON] constructed reliability modelling and proposed an assessment framework for a photovoltaic system based on FTA [10]. A significant advantage of FTA is its ability to keep the qualitative characteristics of the model itself intact when quantifying risk [11]. A large number of quantitative risk models can be found in the FTA literature. Similar to models constructed by other risk assessment methods, these models use probability functions and require a large amount of data to support them to ensure accuracy. In fact, the most common risk assessment and management tools rely heavily on quantitative data, and the information is extremely difficult to obtain in some industries. In response to the scarcity of statistical data and the limitations of human cognition, a likelihood approach based on fuzzy sets is proposed. FFTA can offer greater flexibility than FTA, as opposed to exact probability values, experts can express their recommendations on failure rates in natural language terms. [PERSON] applied the fuzzy theory as a solution to the problem of failure rates and used FFTA to analyze the leakage in abandoned oil and natural-gas wells [12]. [PERSON] applied fuzzy set theory to solve the problem of uncertain data on the probability of occurrence and severity of consequences during risk analysis and used FFTA and FETA to compute [13]. FFTA is a useful diagnostic tool for identifying fault paths and critical events with ambiguity. FMEA is another critical safety and reliability analysis tool that is widely used in a wide range of industries. The core of traditional FMEA is the evaluation of three indicators: S (Severity), O (Occurrence), and D (Detectability) of equipment (components) failure. The S, O, and D can be algebraically multiplied, representing the RPN (Risk Priority Number) to identify failure modes and prioritise key causes of failure. However, the application of the traditional RPN method has several limitations and can lead to some problems. The main controversial points are summarised below [14; 15]: (1) S, O, and D are set the same weight, without considering relative importance. (2) There is no scientific basis for calculating RPN by multiplication. (3) Different combinations of S, O, and D can produce the same RPN and their implications are also different. (4) S, O, and D are difficult to be evaluated precisely. Despite these criticisms, FMEA-based models continue to be widely used in industry because of their applicability and ease of use. Many attempts have been made by some academics to overcome one or more of the limitations. [PERSON] applied the TOPSIS to rank the risk priority of all failure modes [16]. [PERSON] combined ANP and COPRAS methods with interval-valued intuitionistic fuzzy numbers to address the problem of inefficiency of traditional FMEA methods of prioritisation [17]. To determine the relative weights of S, O, and D, [PERSON] proposed a modified FMEA by using TRIZ Anticipatory Failure Determination to identify failures and using the AHP method to calculate the weight of each factor [18]. [PERSON] proposed the Best-Worst Method to determine the importance of weights of criteria flexibly [19]. The objective of the above models is overall to reduce ambiguity or improve the calculation of the RPN to obtain a more accurate ranking. However, in most cases, it does not seem necessary to obtain an accurate ranking of the causes. [PERSON] stated that FMEA aims to identify critical failure modes and should be considered as a clustering problem [20].