An Innovative Construction Site Safety Assessment Solution Based on the Integration of Bayesian Network and Analytic Hierarchy Process

Abstract

The building construction industry in mainland China is distinguished by one of the highest accident rates and numbers of fatalities. Therefore, risk assessment plays a significant role in preventing safety incidents and economic losses. However, traditional risk assessment methods are mainly experience-based which could introduce significant uncertainties in accident chain estimation, quantitative analysis, and handling with uncertainty. Safety accidents are difficult to estimate, which might lead to inappropriate safety-related decision making. To solve this problem, an innovative quantitative analysis strategy has been developed, generating a loss index for various accidents in the construction site, based on the Bayesian Network and Analytic Hierarchy Process solution. In this solution, the contribution rate of every risk factor to a certain accident can be calculated. Based on those, the loss index of each construction site can be calculated by inputting current risk factors in the construction site. Moreover, the real-time loss index can be estimated which can help the management team with more accurate decision making compared with the traditional approaches. With this model, the safety situation on the construction site can be clarified and the risk priority can be analyzed according to the dynamic condition.