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http://dx.doi.org/10.5345/JKIBC.2018.18.2.151

Quantification Model Development of Human Accidents based on the Insurance Claim Payout on Construction Site  

Ha, Sun-Geun (School of Architectural Engineering, University of Ulsan)
Kim, Tae-Hui (Department of Architectural Engineering, Mokpo National University)
Son, Ki-Young (School of Architectural Engineering, University of Ulsan)
Kim, Ji-Myong (Construction Science Department, Texas A&M University)
Publication Information
Journal of the Korea Institute of Building Construction / v.18, no.2, 2018 , pp. 151-159 More about this Journal
Abstract
Accident rate in the construction industry of South Korea is increasing every year, and it represents the highest percentage among industries. This shows that activities performed to prevent safety accidents in the country are not efficient when it comes to reduce the accident rate. In order to resolve this issue, a model for the prediction of human accidents should be established. In addition, it is required a quantification study based on pattern of human accidents. Therefore, the objective of this study is to quantify uncertainty of human accidents risk and predict how to change in various circumstances by using Monte Carlo Simulation. To achieve the objective, first, pattern of human accidents was defined. Second, insurance claim payout and information of human accidents during 14 years in construction site were collected. Third, descriptive analysis is conducted to determine the characteristics of the accident pattern. Fourth, to quantitatively analyze the pattern of the human accidents, the population of each accident occurrence and payout were estimated. Finally, estimated populations was analyzed according to characteristics of distribution by using Monte carlo simulation. In the future, this study can be used as a reference for developing the safety management checklist in construction site and development of prediction models of human accident.
Keywords
Insurance claim payout; risk assessment; monte carlo simulation; human accidents analysis;
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