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A Human-Centric Model for Sustainable Asset Management in Railway: A Case Study
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-0734-0959
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-9992-7791
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-0055-2740
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-7438-1008
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2022 (English)In: Sustainability, E-ISSN 2071-1050, ISSN 2071-1050, Vol. 14, no 2, article id 936Article in journal (Refereed) Published
Abstract [en]

The ongoing digital transformation is changing asset management in the railway industry. Emerging digital technologies and Artificial Intelligence is expected to facilitate decision-making in management, operation, and maintenance of railway by providing an integrated data-driven and model-driven solution. An important aspect when developing decision-support solutions based on AI and digital technology is the users’ experience. User experience design process aims to create relevance, context-awareness, and meaningfulness for the end-user. In railway contexts, it is believed that applying a human-centric design model in the development of AI-based artefacts, will enhance the usability of the solution, which will have a positive impact on the decision-making processes. In this research, the applicability of such advanced technologies i.e., Virtual Reality, Mixed Reality, and AI have been reviewed for the railway asset management. To carry out this research work, literature review has been conducted related to available Virtual Reality/Augmented Reality/Mixed Reality technologies and their applications within railway industry. It has been found that these technologies are available, but not applied in railway asset management. Thus, the aim of this paper is to propose a human-centric design model for the enhancement of railway asset management using Artificial Intelligence, Virtual Reality, and Mixed Reality technologies. The practical implication of the findings from this work will benefit in increased efficiency and effectiveness of the operation and maintenance processes in railway

Place, publisher, year, edition, pages
MDPI, 2022. Vol. 14, no 2, article id 936
Keywords [en]
railway, asset management, model, virtual reality, mixed reality, AI, HoloLens 2
National Category
Human Computer Interaction
Research subject
Operation and Maintenance Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-88826DOI: 10.3390/su14020936ISI: 000747034900001Scopus ID: 2-s2.0-85122909534OAI: oai:DiVA.org:ltu-88826DiVA, id: diva2:1629125
Funder
Vinnova, 2019-05140
Note

Validerad;2022;Nivå 2;2022-01-31 (johcin)

Available from: 2022-01-17 Created: 2022-01-17 Last updated: 2023-09-13Bibliographically approved
In thesis
1. Enablement of digital twins for railway overhead catenary system
Open this publication in new window or tab >>Enablement of digital twins for railway overhead catenary system
2022 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Railway has the potential to become one of the most sustainable mediums for passenger and freight transport. This is possible by continuous updates to the asset management regime supporting Prognostics and Health Management (PHM). Railway tracks and catenaries are linear assets, and their length plays a vital role in maintenance. Railway catenary does not present many failures as compared to the rail track, but the failures that occur do not give enough opportunity for quick recovery. These failures cause extensive time delays disrupting railways operations. Such situations can be handled better by updating the maintenance approach. The domain of maintenance explores possible tools, techniques, and technologies to retain and restore the systems. PHM is dependent on data acquisition and analytics to predict the future state of a system with the least possible divergence. In the case of railway catenary and many other domains, this new technology of data acquisition is Light Detection And Ranging (LiDAR) device-based spatial point cloud collection. Current methods of catenary inspection depend on contact-based methods of inspection of railway catenary and read signals from the pantograph and contact wire while ignoring the rest of the wires and surroundings. Locomotive-mounted LiDAR devices support the collection of spatial data in the form of point-cloud from all the surrounding equipment and environment. This point cloud data holds a large amount of information, waiting for algorithms and technologies to harness it. A Digital Twin (DT) is a virtual representation of a physical system or process, achieved through models and simulations and maintains bidirectional communication for progressive enrichment at both ends. A systems digital twin is exposed to all the same conditions virtually. Such a digital twin can be used to provide prognostics by varying factors such as time, malfunction in components of the system, and conditions in which the system operates. Railways is a multistakeholder domain that depends on many organisations to support smooth function. The development of digital twins depends on the understanding of the system, the availability of sensors to read the state and actuators to affect the system’s state. Enabling a digital twin depends on governance restrictions, business requirements and technological competence. A concrete step towards enablement of the digital twin is designing an architecture to accommodate the technical requirements of content management, processing and infrastructure while addressing railway operations' governance and business aspects.The main objective of this work is to develop and provide architecture and a platform for the enablement of a DT solution based on Artificial Intelligence (AI) and digital technologies aimed at PHM of railway catenary system. The main results of this thesis are i) analysis of content management and processing requirements for railway overhead catenary system ii) methodology for catenary point cloud data processing and information representation iii) architecture and infrastructure requirements for enablement of Digital Twin and iv) roadmap for digital twin enablement for PHM of railway overhead catenary system.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2022
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
Keywords
Railway catenary, Maintenance, eMaintenance, LiDAR, Point Cloud, Digital Twin, Software Architecture
National Category
Computer Systems
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-92656 (URN)978-91-8048-129-8 (ISBN)978-91-8048-130-4 (ISBN)
Presentation
2022-10-14, F-1031, Luleå University of Technology, Luleå, 09:30 (English)
Opponent
Supervisors
Available from: 2022-08-25 Created: 2022-08-24 Last updated: 2022-12-01Bibliographically approved

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Kour, RavdeepCastaño, MiguelKarim, RaminPatwardhan, Amit

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