# The Full Lifecycle Evolution Model of Accidents: A Case Study of Underground Metal Mines in China
## 1 Introduction
However, applying chain-based models to enterprise-wide accident causation analysis can be difficult due to a lack of procedural guidance and real-world case studies, resulting in challenges in merging similar factors across different accident types [19]. This can lead to a redundancy in control factors, an increase system complexity, and ultimately reduce the accuracy of key factor analysis at the enterprise level [20]. These issues arise primarily from unclear distinctions between common factors across different accident types. Most existing accident causation theories assume that organizational or managerial factors are indirect or higher-level causes of accidents [21], whilst unsafe human behaviors and unsafe conditions are considered direct causes. However, the relationship between human factors and unsafe conditions, as well as their roles in accidents, remains a topic of ongoing debate [6]. [PERSON] [22] first proposed that accidents are caused by unsafe behaviors and conditions, attributing unsafe conditions to human error. The energy transfer theory, on the other hand, emphasizes the fundamental role of unsafe conditions of energy in accidents [23]. The loss causation model (LCM) views accidents as failures in control measures, describing the process of accident development [24]. However, it is important to note that humans, as the only active entities in the accident system, influence all other factors, including the environment, equipment, and management systems. [PERSON] [25] emphasized the central role of human factors in the accident process with his Swiss cheese model (SCM). However, the SCM lacks descriptions of the role of material factors in accident evolution. To address this issue, some models have introduced improvements. The 24 Model [26] considers both unsafe behavior and unsafe conditions as direct causes of accidents. [PERSON] et al. [27] explored factors influencing the choice of safety analysis methods, while [PERSON] et al. [28] extracted 15 core system thinking principles to analyze the relationships among accident causation factors. However, these improvements either apply to specific industries or still suffer from the lack of clear distinctions between human and material factors, leading to a redundancy in causative elements across accident categories. A standardized and comprehensive enterprise-level accident analysis framework is still lacking [29]. Therefore, it is necessary to re-evaluate the logical relationships and evolution processes between the various elements of accidents, with particular emphasis on the interaction between unsafe human behaviors and unsafe conditions. Additionally, existing theories still have limitations in analyzing the consequences of accidents [30]. Many scholars have conducted in-depth research on the relationships between safety measures and accident consequences, revealing how deficiencies or inadequacies in safety measures at various stages accelerate accident escalation [31; 32]. For example, [PERSON] et al. [33] analyzed dynamic coupling in chemical processes and devices using the hazard and operability study model. They quantified the likelihood and severity of chemical accidents, validating the dynamic risk evolution trend with the BP refinery explosion in the U.S. [PERSON] and [PERSON] [34] applied multiple machine learning algorithms to classify accidents of different severities, identifying measures to reduce accident severity. [PERSON] et al. [35] used human factors analysis and classification system (HFACS) to classify and code accident causation in 701 mining accident reports from Ghanaian gold mines, identifying significant relationships between accident severity and unsafe behaviors. [PERSON] et al. [36], [PERSON] et al. [37], and [PERSON] et al. [38] conducted studies on the potential impact of unsafe behaviors on the severity of accidents in maritime traffic, construction, and public transportation, respectively.