{"title":"Analysis of Frequently Occurring Violations of the Mandatory Requirements in the Field of Activity of Rostechnadzor for the Period 2016–2022","authors":"A. Tyurin","doi":"10.24000/0409-2961-2023-6-90-96","DOIUrl":null,"url":null,"abstract":"The results of studies of frequent violations of mandatory requirements in the field of activity of the Federal Environmental, Industrial and Nuclear Supervision Service for the period 2016–2022 are presented. The main approaches used to analyze data in this area, which are found in the domestic and international practice, are described. Using the methods of structuring the collected materials considering the division into groups and subgroups in accordance with a certain criterion presented in the source data, and arranging the data in the required order, the causes and types of identified violations are investigated. The enlarged groups of violations detected by different types of state supervision (in the field of nuclear energy use, energy supervision, construction supervision, industrial safety supervision) are identified. The purpose of the study is to systematize open data for the period of 2016–2022 for the subsequent identification of the distribution of the number of recorded cases of violations in various sections — according to the severity of the consequences, as a percentage of detected violations by enlarged groups of violations. When checking the data for compliance with the Pareto rule, it is shown that, on the one hand, 13 % of the detected types of violations of mandatory requirements lead to 80 % of the total number of violations detected, on the other hand, 13.3 % of the main causes of violations also lead to 80 % of the total number of violations detected. The parameters of the presented open data are identified, the completion of which can lead to a refinement of the obtained values in the analysis of the identified violations, as well as the key types of violations, for which there are no well-developed methods for assessing the risk of consequences and the severity of negative consequences.","PeriodicalId":35650,"journal":{"name":"Bezopasnost'' Truda v Promyshlennosti","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bezopasnost'' Truda v Promyshlennosti","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24000/0409-2961-2023-6-90-96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The results of studies of frequent violations of mandatory requirements in the field of activity of the Federal Environmental, Industrial and Nuclear Supervision Service for the period 2016–2022 are presented. The main approaches used to analyze data in this area, which are found in the domestic and international practice, are described. Using the methods of structuring the collected materials considering the division into groups and subgroups in accordance with a certain criterion presented in the source data, and arranging the data in the required order, the causes and types of identified violations are investigated. The enlarged groups of violations detected by different types of state supervision (in the field of nuclear energy use, energy supervision, construction supervision, industrial safety supervision) are identified. The purpose of the study is to systematize open data for the period of 2016–2022 for the subsequent identification of the distribution of the number of recorded cases of violations in various sections — according to the severity of the consequences, as a percentage of detected violations by enlarged groups of violations. When checking the data for compliance with the Pareto rule, it is shown that, on the one hand, 13 % of the detected types of violations of mandatory requirements lead to 80 % of the total number of violations detected, on the other hand, 13.3 % of the main causes of violations also lead to 80 % of the total number of violations detected. The parameters of the presented open data are identified, the completion of which can lead to a refinement of the obtained values in the analysis of the identified violations, as well as the key types of violations, for which there are no well-developed methods for assessing the risk of consequences and the severity of negative consequences.