Date of Award

Spring 12-4-2014

Document Type


Degree Name

Master of Engineering (ME)

First Advisor

Matthew R. Hallowell

Second Advisor

Paul M. Goodrum

Third Advisor

Keith R. Molenaar


Due the saturation of the traditional injury prevention strategies in the industry, risk-based safety innovations are emerging. However, application of risk-based strategies is very limited because: (1) there is a dearth of robust empirical databases; (2) the granularity of risk analysis methods is limited to trade/task-level risks; and (3) interactions among risk factors is not considered. In order to address these limitations, this thesis focuses on quantifying attribute-level risks for industrial construction projects using empirical data contained in 1,611 injury reports. An iterative content analysis was employed with a team of analysts in order to identify attributes, outcomes, and energy sources. The resulting data were analyzed, along with an exposure database provided from industry, in order to quantify relative risks. Finally, a Monte Carlo simulation was performed in order to interpret the risk of new safety scenarios.