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Vol. 7 No. 2 (2018): JITA - APEIRON

Hristo Hristov, Mariya Hristova

Computer Control Systems With Critical Safety Applications: Problems And Some Solutions

Original scientific paper

DOI: https://doi.org/10.7251/JIT1702061H

Abstract

Safety Critical Systems (SCS) are defined as systems controlling critical technological processes, on the proper functioning of which depends human safety. The taxonomy of concepts related to SCS is presented as a dendritic classification scheme. The emphasis is on hierarchical relationships between concepts. After studying global scientific literature, international standards and corporate materials, a classification of the scientific issues accompanying the creation of new SCSs was made.

Regarding a part of the broached issues, technical solutions are suggested based on the structural system of the system. In particular, methods and means have been developed to detect and tolerate failures and errors in building the structure and to reduce their adverse impact on the functionality and safety of the systems.

Formal models have been developed, concerning which calculations and studies have been performed. Quantitative dependencies are established between the technical and probability parameters of diversity structure on the one hand and the reliability and safety of the system on the other. Conclusions are drawn as regards the practical application of the methods and models.

Keywords: Safety Critical Systems, risk, security, safety, reliability.

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.