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Vol. 5 No. 1 (2015): JITA - APEIRON

V. M. Lisenkov, P. F. Bestemyanov

Safety and Risk Management

Original scientific paper

DOI: https://doi.org/10.7251/JIT1501042L

Abstract

The article is devoted to the problem of creating a system of security and risk management. Formulated in relation to the process of movement of trains:
– factor of safety of the train
– the probability of traversing the trains on a particular route without transfer of its movement in a dangerous condition;
– a measure of risk of the transfer movement of the train in a dangerous state
– transition probability of motion in a dangerous state when the movement of trains on a given route.
The objectives of security and risk management are: to provide values of their indicators are not worse than normative, namely, the values of the performance security shall be not less than the normative, and the values of indicators of risk – not more than normative. Proposed functional framework and organizational structure for the management of safety and risks.

Keywords: safety index, a measure of risk, a dangerous condition, standard indicators of safety and risk.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.