Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them
Introduction. Industrial accidents are associated with various factors: human, social and economic problems, which we must strive to eliminate, thereby ensuring a safe working environment. Statistics on occupational injuries are necessary to assess the degree of hazard and potential risks associated...
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Format: | Article |
Language: | Russian |
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Don State Technical University
2020-12-01
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Series: | Безопасность техногенных и природных систем |
Subjects: | |
Online Access: | https://www.bps-journal.ru/jour/article/view/64 |
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author | I. S. Kuptsova Y. I. Bulygin R. R. Lazurenko A. R. Temirkanov |
author_facet | I. S. Kuptsova Y. I. Bulygin R. R. Lazurenko A. R. Temirkanov |
author_sort | I. S. Kuptsova |
collection | DOAJ |
description | Introduction. Industrial accidents are associated with various factors: human, social and economic problems, which we must strive to eliminate, thereby ensuring a safe working environment. Statistics on occupational injuries are necessary to assess the degree of hazard and potential risks associated with occupational factors to protect workers. Labor inspectorate statistics play an important role in developing national policies, systems, programs and strategies to improve safety and working conditions for miners in Zimbabwe. Labor Inspection in Zimbabwe is one of the main safety control mechanisms. Labor inspection statistics enable the government to monitor the mining industry and better analyze mining safety compliance issues.Problem Statement. The article discusses the prediction of accidents in the mining industry of the Republic of Zimbabwe in order to reduce the incidence of injuries. Economic and social development in the mining industry requires reliable analysis of injury statistics. Statistics of injuries in various production processes are given.Theoretical Part. In the process of data analysis, interpolation algorithms are used embedded in mathematical software. Statistical reports on occupational injuries provided by the Federal State Statistics Service were used as basic information.Conclusion. Mathematical forecasting of industrial injuries in the mining industry in Zimbabwe allows us to determine the likely values of the predicted indicators. |
first_indexed | 2024-04-10T03:54:03Z |
format | Article |
id | doaj.art-9d8006a2e5a8450bbe79562f3eab3e5d |
institution | Directory Open Access Journal |
issn | 2541-9129 |
language | Russian |
last_indexed | 2024-04-10T03:54:03Z |
publishDate | 2020-12-01 |
publisher | Don State Technical University |
record_format | Article |
series | Безопасность техногенных и природных систем |
spelling | doaj.art-9d8006a2e5a8450bbe79562f3eab3e5d2023-03-13T07:14:29ZrusDon State Technical UniversityБезопасность техногенных и природных систем2541-91292020-12-010421110.23947/2541-9129-2020-4-2-1163Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce themI. S. Kuptsova0Y. I. Bulygin1R. R. Lazurenko2A. R. Temirkanov3Донской государственный технический университетДонской государственный технический университетДонской государственный технический университетДонской государственный технический университетIntroduction. Industrial accidents are associated with various factors: human, social and economic problems, which we must strive to eliminate, thereby ensuring a safe working environment. Statistics on occupational injuries are necessary to assess the degree of hazard and potential risks associated with occupational factors to protect workers. Labor inspectorate statistics play an important role in developing national policies, systems, programs and strategies to improve safety and working conditions for miners in Zimbabwe. Labor Inspection in Zimbabwe is one of the main safety control mechanisms. Labor inspection statistics enable the government to monitor the mining industry and better analyze mining safety compliance issues.Problem Statement. The article discusses the prediction of accidents in the mining industry of the Republic of Zimbabwe in order to reduce the incidence of injuries. Economic and social development in the mining industry requires reliable analysis of injury statistics. Statistics of injuries in various production processes are given.Theoretical Part. In the process of data analysis, interpolation algorithms are used embedded in mathematical software. Statistical reports on occupational injuries provided by the Federal State Statistics Service were used as basic information.Conclusion. Mathematical forecasting of industrial injuries in the mining industry in Zimbabwe allows us to determine the likely values of the predicted indicators.https://www.bps-journal.ru/jour/article/view/64зимбабвеанализпрогнозтравматизмгорнодобывающая промышленностьэкстраполяциятехника безопасностивероятные величины |
spellingShingle | I. S. Kuptsova Y. I. Bulygin R. R. Lazurenko A. R. Temirkanov Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them Безопасность техногенных и природных систем зимбабве анализ прогноз травматизм горнодобывающая промышленность экстраполяция техника безопасности вероятные величины |
title | Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them |
title_full | Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them |
title_fullStr | Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them |
title_full_unstemmed | Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them |
title_short | Predicting accidents in the mining industry in Zimbabwe in order to develop preventive measures to reduce them |
title_sort | predicting accidents in the mining industry in zimbabwe in order to develop preventive measures to reduce them |
topic | зимбабве анализ прогноз травматизм горнодобывающая промышленность экстраполяция техника безопасности вероятные величины |
url | https://www.bps-journal.ru/jour/article/view/64 |
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