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- Khanna, Parul, et al.
(författare)
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Issues and Challenges in Implementing the Metaverse in the Industrial Contexts from a Human-System Interaction Perspective
- 2024
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Ingår i: International Congress and Workshop on Industrial AI and eMaintenance 2023. - : Springer Science and Business Media Deutschland GmbH. ; , s. 303-318
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The concept of Metaverse is emerging in the industry. Metaverse is expected to be important in industrial asset management and sustainable operation and maintenance. Some of the potentials of implementing Metaverse in the industry can be related to virtual co-creation and design, remote and virtual inspection and maintenance, skills development and training, simulation, safety, and security. Additionally, Metaverse integrated with Artificial Intelligence (AI) and digital technologies will augment human perception, facilitating the Human-System-Interaction (HSI). The traditional HSI carries limitations regarding usability, immersiveness, and connectivity when it comes to the interaction between the virtual, augmented, and real world. An improved HSI in such cyberspace applications may lead to a better understanding of the system and eventually reduced faults. However, implementing Metaverse in industrial contexts is challenging and has not yet been explored thoroughly and systematically. Hence, this paper aims to systematically identify and investigate the various issues and challenges in the implementation of Metaverse in industrial contexts from an HSI perspective. The paper will further provide a taxonomy of these issues and challenges. The research methodology has been based on literature surveys, active and passive observations, and experiments done in the eMaintenanceLAB at Luleå University of Technology. The findings from this paper can be used to increase the effectiveness and efficiency of implementing Metaverse in various industrial contexts.
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| 2. |
- Kumari, Jaya
(författare)
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A System-of-Systems Approach for Enhancing Asset Management of Railway System
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In Sweden, railway transport of freight and passengers is a significant portion of the total transport system. The demand for railway transport is forecasted to increase in the coming decades. One of the main reasons for this ever-increasing demand is the requirement for sustainable transport, nationally and globally. Today, railways are considered an environment-friendly option of transport. The increasing demands on railway transport raise the requirements on the efficiency and effectiveness of the railway system.From a system engineering perspective, the railway system is generally described to consist of two (2) main systems, i.e. a) railway infrastructure and b) railway rolling stock. Further, each of these two systems consists of a set of inherent interconnected integrated systems. Hence, from a system engineering perspective, the railway system can be considered as a System-of-Systems (SoS). Managing complex technical SoS, such as the railway system and its inherent items (also considered as assets), is complex and complicated, that requires a holistic systemic and systematic approach for asset management.A holistic and systematic asset management strategy, considering aspects of reliability, availability, maintainability, safety, and security, is essential in ensuring railway system proficiency. This SoS approach will enforce fact-based informed decision-making by enabling a comprehensive understanding of assets within interconnected systems, facilitating strategic, tactical, and operative planning and execution decision-making as well as tactical processes and operational activities. Augmenting asset management with data-driven analytics, with a focus on the maintenance of assets, is expected to improve the effectiveness and efficiency of asset management. However, challenges related to data quality issues and dynamic asset characteristics must be addressed to gain the anticipated benefits of digitalisation.Asset management of railway infrastructure has received substantial attention from within academia and industry. However, there is a noticeable research gap in the field of railway rolling stock asset management. The characteristics of the railway rolling stock system such as cross-organisational operation and maintenance, and the aspects of fleet management, poses certain challenges. These challenges are related to factors such as 1) the selection of maintenance strategies, 2) considering the dynamic nature of maintenance decisions and strategies 3) a holistic approach to increase system availability, and 4) the use of data-driven approaches such as industrial artificial intelligence, now-casting and forecasting.To address these challenges and bridge the gaps, there is a need to identify the state-of-the-art and challenges associated with asset management of railway rolling stock. Additionally, there is a need to develop a holistic, systemic, and dynamic approach utilising data-driven solutions for enhanced asset management of railway rolling stock. The development of such an approach requires frameworks, tools, technologies, methodologies, and tools. These artefacts will also increase the knowledge related to domain requirements, state-of-the-art, best practices, and use of technology in asset management of railway rolling stock.Hence, in this research, a taxonomy of issues and challenges has been identified. Furthermore, additional artefacts such as approaches, frameworks, platforms, technologies, methodologies, and tools for asset management of railway rolling stock have been developed and provided. These artefacts have been developed through literature surveys, experiments, best practices, standards, structured and semi-structured interviews with experienced professionals from railway organisations and learning from the development of demonstrators in the context of asset management and maintenance of railway rolling stock.These developed and provided artefacts utilising an SoS approach can be used to establish effective and efficient asset management of railway rolling stock with a focus on the use of Industrial AI and digitalisation for the improvement of operation and maintenance processes. These artefacts can also be used by railway organisations to enhance the existing asset management and maintenance processes for railway rolling stock.
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