ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 3 No. 1-2 (2018): TTTP - APEIRON

Aleksandar Blagojević, Iskra Stojanova, Marko Subotić, Veljko Radičević

Fuzzy Model for Assessing the Scope of Work of Railway Passanger Transport Undertaking

Original scientific paper

DOI: 10.7251/JTTTP1801015B

Abstract

The main objective of the European policy of rail transport is the development of a single railway area. The opening of the railway sector to market competition impose that railway undertak- ings behave like any other modern enterprises in other markets and in other industries. It means, they must constantly develop and maintain competitive advantages, and be better than others. In today’s very intense competition conditions, this is the most difficult to achieve. The railway undertakings are challenged to find optimal solutions to operate efficiently and effectively, in order not only to survive on the transport market, but also to develop and maintain a competitive advantage. The paper developed innovative model for the evaluation of efficiency of railway operators for passenger transport assessing the scope of work of railway undertakings that can greatly help to increase the competitive ability of railway undertakings in the single railway market. The developed models allow the integration of indica- tor groups (resources, operational, financial, quality and safety indicators) into a single assessment of the scope of work of railway undertakings and also allow the provision of information about the correc- tive actions that can improve the scope of work of the railway undertaking. The proposed model has been tested on actual examples, e.g. railway undertaking Railways of Republic of Srpska. The analysis of the results shows exceptional suitability for use of developed approach for assessing the scope of work of railway undertakings.

Keywords : cc

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.