Rail yard digital twin implementation into an industrial information system

Mishkurov, Pavel; Rakhmangulov, Aleksandr; Kornilov, Sergey; Aleksandrin, D. V.

doi:10.1063/5.0074662

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…The railway industry has garnered considerable attention in recent times due to the need for a comprehensive Intelligent Transportation System (ITS) [21] and the requirement for sustainable, accurate, and efficient monitoring of rail inspections and maintenance [22]. However, traditional approaches still present a challenge as they are susceptible to human errors and lack the ability to provide swift and direct solutions for defects and faults.…”

Section: A Research Questionsmentioning

confidence: 99%

Digital Twin for Railway: A Comprehensive Survey

Ghaboura,

Ferdousi,

Laamarti

et al. 2023

IEEE Access

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Digital transformation has been prioritized in the railway industry to bring automation to railway operations. Digital Twin (DT) technology has recently gained attention in the railway industry to fulfill this goal. Contemporary researchers argue that DT can be advantageous in Railway manufacturing logistics to planning and scheduling. Although underlying technologies of DT, e.g., modelling, computer vision, and the Internet of Things, have been studied for various railway industry applications, the DT has been least explored in the context of railways. Thus, in this paper, we aim to understand the state-of-the-art of DT for railway (DTR), for advanced railway systems. Besides, this survey clarifies how DT can serve the railway twin system designers and developers. As DTR is still in its early adoption stage, there is hardly any clear direction to identify the technologies for specific DTR applications. Therefore, based on our findings we present a taxonomy for DTR for designers and developers. Finally, we describe potential challenges, pitfalls, and opportunities in DTR for future researchers.

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Section: A Research Questionsmentioning

confidence: 99%

Digital Twin for Railway: A Comprehensive Survey

Ghaboura,

Ferdousi,

Laamarti

et al. 2023

IEEE Access

View full text Add to dashboard Cite

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Integrating AI and DTs: challenges and opportunities in railway maintenance application and beyond

Dirnfeld,

De Donato,

Somma

et al. 2024

SIMULATION

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In the last years, there has been a growing interest in the emerging concept of digital twin (DT) as it represents a promising paradigm to continuously monitor cyber–physical systems, as well as to test and validate predictability, safety, and reliability aspects. At the same time, artificial intelligence (AI) is exponentially affirming as an extremely powerful tool when it comes to modeling the behavior of physical assets allowing, de facto, the possibility of making predictions on their potential evolution. However, despite the fact that DTs and AI (and their combination) can act as game-changing technologies in different domains (including the railways), several challenges have to be faced to ensure their effectiveness, especially when dealing with safety-critical systems. This paper provides a narrative review of the scientific literature on DTs for railway maintenance applications, with a special focus on their relationship with AI. The aim is to discuss the opportunities the integration of these two technologies could open in railway maintenance applications (and beyond), while highlighting the main challenges that should be overcome for its effective implementation.

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Rail yard digital twin implementation into an industrial information system

Cited by 2 publications

References 17 publications

Digital Twin for Railway: A Comprehensive Survey

Digital Twin for Railway: A Comprehensive Survey

Integrating AI and DTs: challenges and opportunities in railway maintenance application and beyond

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