Study of Occupational Safety Risks in Prefabricated Building Hoisting Construction Based on HFACS-PH and SEM

Abstract

As the concern for environmental pollution and occupational safety caused by the construction industry is gradually increasing worldwide, the prefabricated building model has become a type of construction promoted by sustainable societies. In China, the management codes of prefabricated buildings are not mature enough and safety accidents occur frequently during the construction process. Therefore, how to analyze and determine the main factors that affect the safety of the construction of prefabricated buildings has become a problem to protect the lives and health of construction workers. In this study, we focused our research on the accident-prone component-hoisting construction phase. First, through the questionnaire and accident data, the traditional human factors analysis and classification system (HFACS) was improved into the HFACS–prefabricated building hoisting (PH) risk model. This study also established a comprehensive safety prevention and control system for the component-hoisting process of prefabricated buildings by combining the factor analysis of using structural equation modeling (SEM). The prevention and control measures to avoid the occurrence of prefabricated building component-hoisting accidents were also proposed from four aspects: external environment, organizational factors, prerequisites for triggering accidents, and unsafe leadership behaviors. The results showed the following: (1) For the external environment, occupational safety and health system standards should be established and safety supervision responsibilities should be implemented. (2) For organizational factors, safety management systems should be improved with more capital investment. (3) For unsafe leadership behaviors, safety education and training should be strengthened to ensure workers’ optimal physical and psychological states. (4) For the prerequisite of accidents, it is necessary to create a good hoisting work environment.

Safety Risk Factors for Tower Cranes Used by Small and Medium-Scale Contractors on Construction Sites

“…However, obtaining data on construction accidents is nearly impossible as the records are simply unavailable. Where the records are available, they hardly establish the basic causes of the accidents being investigated [6,9,12,30,31]. Thus, the accident investigation records are mostly incomplete and inaccurate in serving as a safety hazard source and the predominant project site conditions that cause them.…”

“…In the last decade, there have been over a thousand reported cases of crane accidents worldwide [8]. As Song [9] pointed out, working with tower cranes to lift loads during construction is among the major causes of accidents and loss of lives in the construction industry. For instance, in 2015, a tower crane collapsed onto the Grand Mosque in Makkah, Saudi Arabia, killing over one hundred persons.…”

Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

“…As an empirical analysis model, it can test the internal structural relationships between the variables in the model. This relationship was expressed as a causality model and path graph through factor, path, and covariance analyses [ 44 ]. The SEM includes potential and observational variables.…”

Evolutionary game of government safety supervision for prefabricated building construction using system dynamics

“…Moreover, as these models only study the causes of construction safety accidents from the perspective of objective influencing factors, they neglect the construction process main body, namely the behavior influencing construction safety accidents. Especially in PB projects, the supervision of governmental personnel and the attitude of construction personnel play an important role in construction safety accidents (Song et al, 2022). SD is a tool for analyzing and studying information feedback systems and is a cross-cutting, comprehensive method that explores how to understand and solve system problems (Li et al, 2017).…”