Application Of Cream For Evaluation Reliability Of Safety Inspector In Coal Mine

The safety inspector, as a grassroots-level manager, undertakes an important responsibility of protecting miners' life and state property, and plays a decisive role on coal mine safety production. Therefore, we can effectively prevent and reduce coal-mine accidents and ease the grim situation of coal mine safety in our country by improving the human reliability of safety inspectors in coal mines.The cognitive reliability and error analysis method(CREAM) in the second generation of HRA is selected to analyze the reliability of coal mine safety inspector according to the characteristics of the coal mining operation system, and CREAM is improved from two aspects.The factors affect safety inspector's reliability in coal mine are analyzed from five aspects of environment, individual, organization, task and technology combined with process of the individual behavior---perception, cognition and decision-making by using task decomposition method according to the safety inspectors' job functions and working content in coal mine. And the CPC framework table for safety inspectors in coal mine, which solved the problem of CPCs in CREAM are not applicable in the field of coal mine, is established according to the description of CPC in CREAM.Then, the quantitative mode for safety inspector in coal mine is established by using the fuzzy theory and analytic hierarchy process(AHP) according to the CPC framework table for safety inspectors framework of coal mine safety inspectors CPC table. At the same time, the tracking analysis flow chart of root cause in incident caused by human is established on the basis of factors affecting coal mine safety inspector's reliability.The reliability of safety inspector during a certain coal mine human error accident in coal mine is predicted by using improved CREAM extension method and traditional method, and compared with actual results. The comparison shows that prediction made by using improved CREAM extension method highlights and measures the effect of human error on accident.