ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 4 No. 1-2 (2019): TTTP - APEIRON

Dragutin Jovanović, Zoran Ž. Avramović, Siniša Arsić, Miloš Arsić

Safety of railway transport of dangerous cargo

Original scientific paper

DOI: 10.7251/JTTTP1901039J

Abstract

By railway, according to its technological characteristics, the respective amounts of dangerous cargo are being transported. Numerous hazards for people, assets and environment during the danger- ous railway cargo transport processes, are expressed in the case of an extraordinary case or any other mismanagement, where the transport becomes risky, but the same risk is an opportunity for improve- ments if it’s recognized on the way and measures are defined and established for its management. For achieving safety goals within transport of dangerous cargo, it means minimizing the number of extraor- dinary circumstances and overall consequences with undisturbed transport process support, it’s neces- sary to manage and to work constantly on the safety improvements. In the safety management process, the whole railroad staff must take part according to the work duties, responsibilities and competences.

Keywords : dangerous cargo, railway, transport, safety, management.

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.