Simulation analysis of productivity variation affected by accident risk in underground construction operations

Sangyoub Lee, Purdue University

Abstract

The construction industry has had a disproportionately high rate of accident for its size. Accident statistics have played an important role as a prime indicator for measuring safety performance as well as a framework for evaluating accident prevention programs. However, the current system of statistics collection is based upon post-accident analysis. These data provide factual information regarding the post accident situation, but ignore conditions existing prior to occurrence of the accident. This study discusses the identification of factors affecting safety performance in trench operations in order to analyze their effect to the risk of accidents and estimates the risk of accidents by estimating the probability of accidents due to the fuzzy-based effect of the factors prior to the occurrence of an accident. The quantitative variation in productivity resulting from the probability of accidents is simulated based on MicroCYCLONE simulation to reflect the impact of accident risk on productivity and the potential savings possible can be presented. This provides insights into the relationship between the accident risk and their associated productivity variation. This study can contribute to helping those who are in charge of the safety in construction sites make more appropriate decisions to ensure the safe and cost-effective work activities regarding safety management.

Degree

Ph.D.

Advisors

Halpin, Purdue University.

Subject Area

Civil engineering|Industrial engineering|Occupational safety

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