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EN
Purpose: The choice of preventive measures and labour protection equipment should be justified taking into account the occupational risk. For objective reasons, existing approaches do not provide an opportunity to justify the choice of the necessary measures, which best reduce the occupational risk level. Consequently, an effective methodological approach to justify preventive measures is required, since the level of risk in mining enterprises is still high, especially in developing countries and countries with weak economies. The current research is devoted to solving this urgent scientific problem. Design/methodology/approach: Construction of mathematical models based on accumulated statistical data on the values of production factors using polynomial regression, which is justified by the simplicity of computational algorithms and the clarity of the results obtained. Findings: On the example of the Ukrainian mining industry, it was found that to reduce occupational risk; the most effective is to change the operating mode of the equipment and rational planning of working hours, but not measures to reduce the dust concentration. Research limitations/implications: The study is focused on the mining industry; a methodological approach and a mathematical model are proposed for specific working conditions at Ukrainian mining industry. Practical implications: The proposed approach makes it possible, based on statistical data, to quickly and reliably select the most effective measures to reduce the industrial risk level. Originality/value: A feature of the proposed approach to reducing industrial risk is a comprehensive accounting of data on factors affecting occupational risk, the construction of mathematical models and the use of modelling results when planning measures to improve working conditions.
EN
Purpose: To develop a more advanced methodology, the application of which will provide an informational and computational and analytical basis for planning and implementing effective preventive measures aimed at minimizing occupational risks with limited resources, as well as in the absence of organizational and technical capabilities to create absolutely safe working conditions. Design/methodology/approach: For the study, statistical data were used that obtained from enterprises of the metallurgical industry of Ukraine. Research methods: analysis and generalization of known scientific results, methods of statistical analysis, mathematical modelling, expert assessments and decision theory. Findings: The results of experimental studies have confirmed the possibility of an objective assessment of various options for the OSH management strategy, which allows justifying the allocation of funds for OSH in the required amounts. It is shown that professional risk management strategies are characterized by different efficiency in the use of available financial resources, and the most effective strategy is one that allows you to minimize the level of risk (in comparison with other strategies) with the same amount of funding. Research limitations/implications: The study focuses on enterprises of the metallurgical industry in Ukraine. Practical implications: The application of the developed mathematical models demonstrates the effectiveness of financing certain preventive and protective measures, and stimulates the head to ensure industrial safety. Originality/value: The developed mathematical models allow justifying the allocation of funds for OSH in the required amounts.
EN
Purpose: Improving the systematic approach to planning and rationalizing labour protection measures at oil and gas enterprises, based on the results of hazard identification and industrial risk assessment. At the same time, the main task of the risk management process is to ensure the rights of employees guaranteed by the current legislation, namely, to create proper, safe and healthy working conditions. Design/methodology/approach: A comparative legal method for identifying the features of European and Ukrainian legislation in the occupational safety and health field; a structural-logical method for determining the main directions for the further development of the occupational safety and health management system at enterprises; analysis and generalization of well-known scientific results on the research topic; statistical analysis to identify the relationship between the industrial risk' level and various factors that may affect its value; applied systems analysis and mathematical modelling method for new methodological approaches' development to assessing of hazards' likelihood and their consequences' severity were used. The basis for improving the systematic approach to planning and rationalizing labour protection measures is based on the standard IEC 61882:2001. The statistics are taken from the "Messages" information system, which operates in the State Service of Ukraine on Labour and is designed to collect and process data on occupational injuries Findings: An analysis of the current legislative and regulatory acts showed promising directions for their improvement. A mathematical model for scoring industrial risk is proposed, which takes into account the relationship between industrial risk and preventive measures and the time of their implementation. The calculation system developed on the basis of the proposed model provided a reduction in the time for processing data and calculating the values of industrial risks by 20...25%. Research limitations/implications: Statistical data on industrial injuries at enterprises of the oil and gas industry of Ukraine for 2018-2019 were used. Practical implications: Implementation of the proposed systematic approach to the organization of occupational safety and health management at enterprises has shown its simplicity and effectiveness, which can induce employers to finance reasonable and timely preventive measures. Originality/value: The method has been improved by decreasing the discreteness step in the assessment of industrial risk components, which has increased its accuracy; by developing a mathematical model for calculating the probability of a hazard, taking into account the frequency with which workers are exposed to danger, which eliminates the need to involve experts for an expert assessment at this stage.
EN
Purpose: To develop and implementation in practice an algorithm for smart monitoring of workplace environmental physical factors for occupational health and safety (OSH) management. Design/methodology/approach: A brief conceptual analysis of existing approaches to workplace environmental physical factors monitoring was conducted and reasonably suggest a decision-making algorithm to reduce the negative impact of this factors as an element of the OSH management system. Findings: An algorithm has been developed that provides continual improvement of the OSH management system to improve overall labour productivity and which has 3 key positive features: (1) improved data collection, (2) improved data transfer and (3) operational determination of the working conditions class. Research limitations/implications: The implementation of the proposed algorithm for substantiating managerial decisions to reduce the negative impact of workplace physical factors is shown by the example of four workplace environmental physical factors in the products manufacture from glass. Practical implications: If management decisions on the implementation of protective measures are taken in accordance with the proposed monitoring algorithm, these decisions will be timely and justified. This makes it possible to reduce the time of the dangerous effects of physical factors on the health of workers and reduce the level of these factors to improve working conditions. That is, an algorithm is proposed that provides continuous improvement of the OSH management system to increase overall labour productivity. Originality/value: Current monitoring of workplace environmental physical factors values are carried out in accordance with the justified monitoring intervals for each factor that provides the necessary and sufficient amount of data and eliminates the transfer of useless data.
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