Statistical Regularities in the Industrial Injury Data at the Mining and Metallurgical Enterprise of the Fuel and Energy Industry



Annotation:

The article provides statistical analysis and the calculation of injury rate indices as well as the frequency of accidents of the mining and metallurgical company Norilsk Nickel JSC based on the annual report in open access. The indices of the number of victims of industrial accidents with disablements for one working day and more as well as with more severe and fatal outcomes, without division by age, gender, the average number of employees, and the amount of funds spent on labor protection measures during a year. Linear regression models of statistical dependence between expenditures on labor protection measures per 1000 employees per year and the number of accidents of different types per 1000 employees per year have been built in the study. Correlation coefficients between the parameters specified and the average relative deviation between the real data and the linear regression models have been calculated. The conclusions on the potential application of the methodology for a forecast assessment of industrial injury rate have been made.

References:
1. Milojica M., Dundovic K. Primjena poissonove razdiobe u statističkoj obradi ozljeda na radu u trgovačkom društvu «luka Rijeka». Zbornik Veleučilišta u Rijeci. 2014. Vol. 2. № 1. pp. 295–312.
2. Abikenova S., Issamadiyeva G., Kulmagambetova E., Daumova G., Abdrakhmanova N. Assessing Occupational Risk: A Classification of Harmful Factors in the Production Environment and Labor Process. International Journal of Safety and Security Engineering. 2023. № 13. DOI: 10.18280/ijsse.130511
3. Sashidharan C., Mohan Kumar P., Gopalakrishnan S. Prevalence and determinants of external injuries among industrial workers in an urban area of Kancheepuram district, Tamil Nadu. International Journal of Community Medicine and Public Health. 2017. Vol. 4. № 12. DOI: http://dx.doi.org/10.18203/2394-6040.ijcmph20175358
4. Clar C., Koutp A., Leithner A., Leitner L., Puchwein P., Vielgut I., Sadoghi P. Occupational injuries in orthopedic and trauma surgeons in Austria. Archives of Orthopaedic and Trauma Surgery. 2024. Vol. 144. DOI: 10.1007/s00402-024-05200-0
5. Obshiev V.A., Daginova N.S., Muchkaeva B.A., Bakurov O.H., Sanjiev B.V., Mueva E.C., Zulaev D.N. Information technologies in the prevention of injuries and occupational diseases based on the results of monitoring indicators of labor conditions and labor protection. Ekonomika i predprinimatelstvo = Economics and Entrepreneurship. 2024. 9 (170). (In Russ.). DOI: 10.34925/EIP.2024.170.9.189
6. Ivanov E.N., Grafkina M.V., Klindukh M.A., Sviridova E.Y. The Influence of regional specifics of economic activities on the indicators of occupational injuries. Rossiyskiy zhurnal ekonomiki truda = Russian Journal of Labor Economics. 2018. № 4. (In Russ.). DOI: 10.18334/et.5.4.39416
7. Grafkina M.V., Klindukh M.A., Sviridova E.Y. Modeling the current trend and predicting changes in indicators of occupational accidents. Rossiyskiy zhurnal ekonomiki truda = Russian Journal of Labor Economics. 2018. Vol. 5. (In Russ.). DOI: 10.18334/et.5.1.38756
8. Mogilat V.L., Tyrsin A.N. Mathematical modeling of traumatism dependence on competence and awareness of personnel at mining enterprises. Izvestiya vuzov. Gornyy zhurnal = Minerals and Mining Engineering. 2006. № 2. Vol. 2. pp. 77–81. (In Russ.).
9. Zilberstein O.B., Melnik P.V. The relationship between of labor costs and revenue (on the example of JSC «Nevinnomyssk’s nitrogen»). Rossiyskiy zhurnal ekonomiki truda = Russian Journal of Labor Economics. 2018. № 2. (In Russ.). DOI: 10.18334/et.5.2.39166
10. Sizov V.A., Alov Y.Y., Sennikova A.E. Statistical analysis of labor productivity in the Russian Federation. Upravlencheskiy uchet = Management Accounting. 2022. № 5. (In Russ.). DOI: 10.25806/uu5-12022247-252
DOI: 10.24000/0409-2961-2025-2-80-84
Year: 2025
Issue num: February
Keywords : occupational safety occupational safety industrial injuries injuries statistical patterns linear regression models correlation coefficient relative deviation
Authors:
  • Mingaleva E.I.
    Student, mingaleva2001@mail.ru, RGU of Oil and Gas (NIU) named after I.M. Gubkin, Moscow, Russian Federation