광업에서 재해율과 중대재해의 예측치에 의한 산업재해 방지 방안
The Method for Prevention of Industrial Accident by Predicted Results of Accident Rate and Fatal Accident in the Mining Industry
강영식(세명대학교)
25권 3호, 25~35쪽
초록
Mining industry is a high-risk workplace and a blind spot in safety. The prevention of industrial accidents in this industry is very important because it causes many fatal accidents. Accordingly, predicted results considering the industrial accident rate and fatal accident rate in the mining industry are required to prevent the occupational accidents. Therefore, this paper describes very efficient methods for prevention of industrial accidents with these predicted results in the mining industry. Also, this paper proposes minimization of the sum of square errors (SSE) to find the predicted results between static prediction methods to dynamic method with existing accident data in mining industry. The minimum value of SSE in the mining industry was found in 82.7028 and 147.3107 in the occupational accident rate and fatal accident rate, respectively. Double exponential smoothing method (DESM) and kalman filtering model (KFM) are ideally applied in the accident rate. In addition, the optimal method of prediction by fatal accident was found in auto-regressive integrated moving average (ARIMA) model the mining industry. Finally, this paper provides very efficient and systematic method in order to prevent accidents through the trend of predicted results with accidents and fatal accidents in mining industry.
Abstract
Mining industry is a high-risk workplace and a blind spot in safety. The prevention of industrial accidents in this industry is very important because it causes many fatal accidents. Accordingly, predicted results considering the industrial accident rate and fatal accident rate in the mining industry are required to prevent the occupational accidents. Therefore, this paper describes very efficient methods for prevention of industrial accidents with these predicted results in the mining industry. Also, this paper proposes minimization of the sum of square errors (SSE) to find the predicted results between static prediction methods to dynamic method with existing accident data in mining industry. The minimum value of SSE in the mining industry was found in 82.7028 and 147.3107 in the occupational accident rate and fatal accident rate, respectively. Double exponential smoothing method (DESM) and kalman filtering model (KFM) are ideally applied in the accident rate. In addition, the optimal method of prediction by fatal accident was found in auto-regressive integrated moving average (ARIMA) model the mining industry. Finally, this paper provides very efficient and systematic method in order to prevent accidents through the trend of predicted results with accidents and fatal accidents in mining industry.
- 발행기관:
- 한국설비안전학회
- 분류:
- 설비관리