Study on the dynamic safety risk of struck-by-equipment hazard: risk analysis, prediction and safety performance evaluation
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abstract
Having a system that can proactively identify risks on sites is the key to the success of hazard identification and prevention in the dynamic and hazardous construction environment. Safety performance evaluation also is a primary means to enhance construction safety. Leading indicators are aspects reflecting safe practices or observations that can be used to strengthen safety performance prior to the occurrence of an undesirable consequence. Thus this paper employs a network-based model and a probabilistic method with two safety leading indicators to investigate the dynamic struck-by-equipment risk. In the network-based model, entities’ dynamics and the interactions among them are monitored, quantified, and analyzed to identify risk and their risk-related behaviors. Degree centrality and algebraic connectivity are employed as the leading indicators to measure the struck-by-equipment risk at the entity and network levels. Meanwhile, a probabilistic method with Monte Carlo simulation is applied to predict the risk at the two levels. Thus, real-time, posterior, and prospective safety performance evaluation can be conducted. The implementation and assessment of the network-based model and the probabilistic method for risk analysis, prediction and safety performance evaluation were conducted by using two simulated examples. The safety performance of entities (i.e., workers-on-foot and equipment) and job sites pertinent to struck-by-equipment hazard was evaluated. Accordingly, safety managers can gain a full understanding of workforce behaviors and job sites in terms of safety, to proactively eliminate unsafe actions and practices. The results also provide insight into the development of safety training strategies and programs.
