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Vol. 11 No. 2 (2021): JITA - APEIRON

Mihajlo Travar, Igor Dugonjić, Saša Ristić

Accelerated Process of Digital Transformation - The Impact and Consequences of Covid-19

Original scientific paper

DOI:https://doi.org/10.7251/JIT2102116T

Abstract

Due to the current pandemic caused by the COVID-19 virus, the world is changing rapidly along with digital technologies that transform every aspect of life, society and the economy. To prevent a complete collapse and suspension of all business processes, companies were forced to organize remote work, i.e. workers perform their daily work activities from their homes. The situation in which the world is currently in clearly indicates that digital transformation is something that should be a priority. Digital transformation is changing the way of doing and developing the business, new opportunities for economic progress in the public and private sectors. It allows companies to survive and focus on innovation, increasing their competitiveness. We can say with certainty that digital transformation means much more than complete integration of digital technologies. It also means digitalization and business processes and models automation, marketing, sales, digital purchase, Big Data, and related processes, and is based on five different areas, which include customers, competition, value, innovation and data.

Keywords: Digital transformation, Information technology, Business process, Impact, Pandemic Covid-19.

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.