Моделирование ожидаемого предотвращенного ущерба в энергетике. Часть 1. Детерминированный подход

Abstract

Inspection control and supervisory activities are one of the important mechanisms of proactive industrial safety. Corporate control ensures early detection of security violations and their prompt elimination to prevent accidents. The expected prevented damage at hazardous production facilities is considered one of the efficiency factors of inspection activities. In order to assess the expected prevented damage (direct or indirect), the number of expected incidents and damage for each event must be calculated. An approach to the assessment of the number of prevented events based on the pyramid of incidents (Heinrich’s pyramid, Berd’s pyramid) by supplementing it with the level of detected violations has been proposed. The number of prevented incidents can be assessed within the framework of deterministic and scholastic approaches. The study focuses mainly on building and analysis of the ratio of the number of incidents between different levels of the pyramid within the framework of the deterministic approach. The accident statistics at oil and gas industry facilities has been analyzed; Heinrich’s hypothesis regarding the type of dependence between the pyramid levels has been tested; and coefficients of the injury rate pyramid have been determined. To find the final coefficients of the improved pyramid of an oil and gas company, the method of coefficient calculation with accumulations for each year has been chosen. It has been demonstrated that traditional values of coefficients of Heinrich’s pyramid and those obtained as a result of calculations do not comply, which can be explained by the significant difference in industrial technologies and efficiency of occupational safety measures as of today and at the moment of initial building of Heinrich’s pyramid. Based on the regression analysis and other forecasting methods (the Holt method, the Brown exponential smoothing method, the ARIMA model, and the moving average extrapolation method), modeling and forecasting injury rate factors have been conducted. The comparative analysis of methods to forecast the number of accidents has been carried out. It has been shown that it is advisable to apply the linear regression model to predict injury rates.