Factor Analysis of Industrial Injuries with the Purpose to Improve the Procedures for Training the Employees in Occupational Safety during Coal Mining

The article describes the concept of «zero injury», within the framework of which the current level of injury rate in the coal industry is analyzed, the causes of juries are given, and also, the problem of personnel qualification is raised. On the example of JSC «SUEK-Kuzbass», the analysis of industrial injury rate is presented. There are three key causes of injury: technical, systemic, and human factors. Qualitative dependence of the level of injury rate on time is given in the implementation of preventive measures — technical, systemic, and aimed at the formation of a safety culture, proposed by the International Labor Organization as a hypothesis confirmed at the number of enterprises in the mining industry, construction, and transport. Detailed analysis is conducted on such factors as profession, age and experience of the victims, the time elapsed after the start of the shift until the injury at work, as well as the competence of employees in safety matters. According to the analysis over the past three years, the most traumatic professions are: drifter, engineering and technical worker, underground miner, electrical fitter (locksmith), face miner, mining operator and driver. The most frequent injuries occurred with the employees with work experience of up to a year, from 5 to 10 years, and over 15 years. By age groups, the largest number of injuries was recorded for the employees aged from 31 to 35 years, which roughly corresponds to 5–10 years of work experience. Considering such a factor as the time from the beginning of a work shift to injury, it shall be noted that the greatest number of injuries occurs at the beginning of the shift and in the period 4–7 hours from the beginning of the shift. In accordance with GOST R ISO 45001—2020, the conducted analysis is an element of risk assessment and opportunities for further improvement of training programs for the employees in the field of occupational safety.

Research on MCL for Mobile Underground Miner Location System Based on ZigBee

In this paper, we try to solve the problem of mine safety and real-time scheduling in underground miner, the Monte-Carlo localization methods of the underground location system based on ZigBee wireless sensor network were proposed. This paper designs software application for the nodes in the network, builds the overall structure of the miner location system and constructs the ZigBee wireless network. After testing and simulation, the results indicate that we can locate precisely in the complex terrain and terrible communication environment by the Monte-Carlo Localization algorithm.

Mechanistic model predicts a U-shaped relation of radon exposure to lung cancer risk reflected in combined occupational and US residential data

A mechanistically based cytodynamic two-stage (CD2) cancer model was shown recently to predict both ecologic US county data and underground-miner data on lung-cancer mortality (LCM) vs radon concentration, indicating biological plausibility of the apparent negative dose-response relation exhibited by the ecologic data.6 To further investigate this hypothesis, the CD2 model was fitted to combine age-specific LCM data vs estimated radon-exposure in white females of age 40+ years in 2821 US counties during 1950-1954 using new estimates of county-specific mean residential radon exposure, and in five cohorts of underground nonsmoking miners. The negative association of radon levels and corresponding county-level LCM rates apparent in women dying in 1950-1954 (11% of whom never smoked) was also apparent in women of age 60+ years (5% of whom never smoked). The CD2 fit obtained to the combined residential and occupational data was found to predict the combined data using biologically plausible parameter values, and also to predict inverse dose-rate effects exhibited in nonsmoking miner data to which the CD2 model was not fit. These results are consistent with the hypothesis that residential radon exposure has a nonlinear U-shaped relation to LCM risk, and that current linear extrapolation models substantially overestimate such risk.