## 5 Research Questions
FMEA has been applied to evaluate failure of conveyor belts due to human error in coal mines [172; 173; 174; 175] and has been proposed for risk assessment in the maritime industry [176; 177; 131; 178]. In addition, it aims to reduce workplace accidents in the construction sector [129] and is applied in chemical laboratories of universities, but it can also be applied in engineering and physics labs by weighing the severity index [166]. FMEA can assist in decision-making in earthwork operations and is used in textile manufacturing [131]. It was developed for application in the chemical industry and is considered to be a suitable method in unstable and uncertain environments [9; 179; 180]. Finally, it has been shown to help with more accurate risk assessment in technical safety management systems [181] and facilitates safety in the aviation sector as a tool for risk analysis. MCDM is another subcategory that, when combined with neural networks, helps to ensure industrial safety and enriches regulations by using the Taiwanese government regulations [131]. It is also applied by hospital managers to keep safety risk levels low [68]. LPOA is another subcategory of fuzzy logic that finds application in industries using LNG [134] but has also been used for protection against heaters in combination with fuzzy logic [113]. QRA is a subcategory of fuzzy logic that helps to assess uncertainty in real time in chemical plants [137; 139] and improves uncertainty in oil, gas, and chemical industries [138]. Similarly, the PRAT method ensures worker safety and is applied in textile companies that produce towels and bathrobes [139]. Another important subcategory that is applied in both neural networks and fuzzy logic is the TOPSIS method. The TOPSIS method is applied with the help of neural networks in industrial safety and workplace accidents, while also improving Pareto models [3]. When combined with fuzzy logic, TOPSIS helps in the field of engineering, for example, scaffolding, excavators, and trucks [161]. The HRA method is applied in combination with fuzzy logic and machine learning. It has been proposed as a method for assessing human errors in nuclear power plants [182; 183]and for managing human errors in industries combined with fuzzy logic [161]. On the other hand, it enhances machine learning, addressing occupational risk in processing industries [184]. A notable subcategory of fuzzy logic is DEMATEL, which is applied in the construction industry [148], but, in combination with methods such as AHP, MCDM, and TOPSIS, it determines the causality of risk in various occupational sectors [185]. The Monte Carlo method is combined with fuzzy logic to aid in uncertainty analysis in accident probability at nuclear power plants [186; 187] and has been applied in decision-making support for wind energy projects [132]. Two well-known subcategories of neural networks, whose methods are used for facility safety, are the ANFIS and ANNs. The ANFIS has been applied to scaffolding in the construction sector [188]. ANNs help managers to make decisions in natural gas refineries [189]; they have been identified as reducing fatal accidents in the construction sector [18], they improve accidents related to musculoskeletal issues in the construction industry [190], and they have been applied for the safety and utilization of workers in transportation, such as in railways [191]. Additionally, ANNs have been used to assess deep mine risks [192], manage safety in construction work [193], and classify risks in manual loading problems [194]. One of the most significant subcategories of neural networks that aid in safety and risk assessment is Bayesian Networks (BNs) [195; 196; 197; 149]. BNs have been applied in transportation, focusing on the safety of people and organizations [198; 199], help to assess the severity of injury in traffic accidents [173], and are used in human and organizational evaluation systems to reduce accidents [200; 201; 202].