Abstract

Background: The aim of the present study was to assess the safety performance in a steel industry and predicting the occurrence of incidents using Customized Predictive Risk Index (CPRI) technique. Materials and methods: 350 unsafe observations were recorded and scored based on risk factors of probability of danger, frequency of work exposure, number of persons at risk, and severity of consequence. Risk Index (RI) of each observation was calculated through geometric average of risk factors. Optimum forecasting time series model of RI was determined using the smallest value of Akaike information criterion (AIC) to predict the CPRI trend and forecast the occurrence of incidents with a 95 confidence interval. Descriptive analysis was conducted using SPSS 22.00 and incident forecasting based on CPRI trend was conducted using forecast package for R 3.3.1. Results: Autoregressive of 6 consecutive observations (AR-6) was chosen as the optimum model to fit time series data and define CPRI (AC = 1226.58). Most incidents occurred when the CPRI value was exceeds five and this range was determined as action zone and forecasting criteria for predicting the occurrence of incidents. Conclusion: Customized Predictive Risk Index (CPRI), developed in this study could be used as a leading indicator for safety performance in steel industry. Ensuring the managers about the functionality of leading indicators to assess safety performance could be facilitated with comparing the results achieved by models with the real data.