Open AccessForecasting and Managing Professional Risks Using Information-Analytical Systems Based on Fuzzy Logic Methods
Author(s) -
A. Yu Semeykin,
Е. V. Klimova,
I. A. Kochetkova
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/459/5/052083
Subject(s) - hazardous waste , risk analysis (engineering) , production (economics) , risk management , competence (human resources) , fuzzy logic , business , computer science , operations management , engineering , psychology , social psychology , finance , artificial intelligence , economics , macroeconomics , waste management
The article presents the results of studies aimed at improving the effectiveness of professional risk management in enterprises of various industries. For this purpose, an information-analytical system has been developed. It consist of modules for accumulating and processing statistical information about incidents, qualifications, competence of employees, a module for forecasting incidents and determining the degree of risk, and a module for determining options for management decisions. The proposed modules are components of a comprehensive integrated occupational safety management system. It has been designed to determine the level of professional risk of personnel of industrial enterprises and hazardous production facilities and ensure the safety of production activities. Using the product will allow enterprises to interactively monitor the dynamics of personnel competency indicators, the technical condition of production facilities, external factors and predict the risks of accidents and emergencies at enterprises and hazardous production facilities. The use of a fuzzy analysis of incidents by various factors makes it possible to compare data on the personnel of enterprises and evaluate the statistical probability of incidents and accidents. This allows us to identify categories of employees of enterprises for whom the value of occupational risk exceeds the allowable values, and make decisions to reduce it.