| description abstract | Safe operation of cranes is essential in the construction industry to ensure continuous gains in productivity and control potential hazards to workers on construction sites. In this research, which was based on human-machine-environment (HME) system thinking, a structured crane-related accident database was developed to identify and prioritize the safety concerns of construction crane operators. In order to technically investigate risk factors from accident reports, an approach was proposed in this work integrating factor clustering and prioritization. Accordingly, the research methodology was designed to first collect crane-related accident cases and determine database variables, including accident types, contributing operational factors, and accident consequences. Second, an advanced multiple correspondence analysis (MCA) method coupled with the fuzzy logic was applied to distribute the variables into different clusters and visualize their associations. Third, once the variables were well clustered, failure mode and effect analysis (FMEA) was adopted to investigate the multiscaled structure of clustering and explore the priorities of failure modes based on current legislation, regulations, and industrial codes of practice. In summary, the proposed approach integrating clustering analysis and prioritization analysis contributes to determining essential safety concerns and their potential impacts during crane operation, generating implications for construction crane safety management and eliciting detailed managerial implementation strategies for prevention measures for crane accidents in the construction industry. | |
