Safeguarding construction workers from occupational hazards, whether arising from traumatic, ergonomic, and/or exposure accidents, is part and parcel of the lean construction ideal of waste elimination. Howell et al. (2002) proposed a new approach to understand construction accidents based on Rasmussen’s theory of cognitive systems engineering. One aspect of the model focused on worker training to recognize hazards (unsafe conditions). The primary goal of this paper is to develop a method to quantify workers’ ability to identify these hazards. Abdelhamid et al. (2003) explored the need for an assessment of the process of identification and applied Signal Detection Theory (SDT) to assess workers’ ability to detect unsafe conditions. This research applies Fuzzy SDT, proposed by Parasuraman et al. (2000), to increase the applicability of conventional SDT analysis to construction settings where the definition of a signal event and its associated response do not follow a binary or dichotomous structure. Application of the methodology is demonstrated using a pilot study involving structural steel workers. Results from the sample of 10 ironworkers indicated the average sensitivity in identifying hazards was above average and that workers generally adopted a conservative strategy. Data analysis using conventional SDT model showed a marginally increased sensitivity, but with a very high variation. This result illustrated that fuzzy SDT model was more reflective of the ability of construction workers to identify construction hazards.
Occupational Safety, Construction Safety, Signal Detection Theory, Construction Accidents, Hazard Identification