데이터마이닝 기법을 활용한 건설 중대 재해요인 간 연관성 분석

초록

Governments and companies are trying to reduce occupational accidents in the construction industry; however, the number of disasters are not decreasing significantly. This study aims to identify the correlation between factors affecting construction disasters quantitatively. To this end, 1,197 cases of serious disasters provided by Korea Occupational Safety and Health Administration (KOSHA) were analyzed using affinity analysis, one of the data mining techniques. The data from KOSHA were preprocessed and analyzed with variables of accident type, project type, activity type, original cause materials, sensory temperature, time of the accident, and fall height, and the association rules were derived for fall accidents and the others. For fall accidents, 64 association rules with lift ratios of 1.38 or greater were derived, and for the other accidents, 59 association rules with lift ratios of 1.54 or greater were derived. After analyzing the derived association rules focusing on the relationship among accident factors, this study presented the significance of applying the affinity analysis to address the study’s limitations. The significance of this study can be found in that the correlation among factors affecting construction accidents is presented quantitatively.

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