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

Veselin Salamadija, Pavle Gladovic

Model of Information Integration of Management in Road Transport Companies

Original scientific paper

DOI: 10.7251/JTTTP1901010S

Abstract

In modern business conditions, the management of work by road transport companies is becoming more and more complex, and it is challenging to manage the companies’ management and business continuously before the management of these companies.

The expansive development of information and communication technologies, technique and technol- ogy, the globalization of the world economy, the ever more diverse requirements of transport service users require efficient adaptation of the business of road transport companies. The application of mod- ern information and communication technologies facilitates the business and operation of road trans- port companies, and management information systems create the preconditions for efficient decision- making by all decision makers in road transport companies.

In order to improve the process of managing the work of a road transport company it is necessary to ex- plore the possibility of information integration of the management of a road transport company, which will integrate all the managers regardless of the level of management they belong to. Infrastructure integration is necessary in the horizontal line of management, especially operative and medium, and in the vertical line all levels of management (top, middle and operational).

In this paper, a new model of information integration of management will be proposed, which can be applied in medium-sized and bigger transport companies.

Keywords : road transport companies; road transport; information systems; 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.