| 1. |
- 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. |
- Kour, Ravdeep, 1981-, et al.
(författare)
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A cybersecurity approach for improved system resilience
- 2022
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Ingår i: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022). - : Research Publishing Services. ; , s. 2514-2521
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Konferensbidrag (refereegranskat)abstract
- The ongoing digitalisation of industrial systems is bringing new challenges in managing, monitoring, and predicting the overall reliability performance. The overall reliability of a cyber-physical system, such as railways, is highly influenced by the level of resilience in its inherent digital items. The objective of this paper is to propose a systematic approach, based on an enhanced Cyber Kill Chain model, to improve the overall system resilience through monitoring and prediction. The proposed cybersecurity approach can be used to assess the future cyberattack penetration probabilities based on the present security controls. With the advancement in cybersecurity defensive controls, cyberattacks have continued to evolve through the exploitation of vulnerabilities within the cyber-physical systems. Assuming the possibility of a cyberattack it is necessary to select appropriate security controls so that this attack can be predicted, prevented, or detected before any catastrophic consequences to retain the resilience of the system. Insufficient cybersecurity in the context of cyber-physical systems, such as railways, might have a fatal effect on the whole system availability performance and sometimes may lead to safety risks. However, to improve the overall resilience of a cyber-physical system there is a need of a systematic approach to continuously monitor, predict, and manage the health of the system’s digital items with respect to security. Furthermore, the paper will provide a case-study description in railway sector, which has been used for the verification of the proposed approach.
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| 3. |
- Kumari, Jaya, et al.
(författare)
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A framework for now-casting and forecasting in augmented asset management
- 2022
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Ingår i: International Journal of Systems Assurance Engineering and Management. - : Springer. - 0975-6809 .- 0976-4348. ; 13:5, s. 2640-2655
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Tidskriftsartikel (refereegranskat)abstract
- Asset Management of a complex technical system-of-systems needs cross-organizational operation and maintenance, asset data management and context-aware analytics. Emerging technologies such as AI and digitalisation can facilitate the augmentation of asset management (AAM), by providing data-driven and model-driven approaches to analytics, i.e., now-casting and forecasting. However, implementing context-aware now-casting and forecasting analytics in an operational environment with varying contexts such as for fleets and distributed infrastructure is challenging. The number of algorithms in such an implementation can be vast due to the large number of assets and operational contexts for the fleet. To reduce the complexity of the analytics, it is required to optimize the number of algorithms. This can be done by optimizing the number of operational contexts through a generalization and specialization approach based on both fleet behaviour and individual behaviour for improved analytics. This paper proposes a framework for context-aware now-casting and forecasting analytics for AAM based on a top-down, i.e., Fleet2Individual and bottom-up, i.e., Individual2Fleet approach. The proposed framework has been described and verified by applying it to the context of railway rolling stock in Sweden. The benefits of the proposed framework is to provide industries with a tool that can be used to simplify the implementation of AI and digital technologies in now-casting and forecasting.
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| 4. |
- kumari, jaya, 1984-
(författare)
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A performance-driven framework with a system-of-systems approach for augmented asset management of railway system
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Ingår i: International Journal of Systems Assurance Engineering and Management. - 0975-6809 .- 0976-4348.
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Tidskriftsartikel (refereegranskat)abstract
- The railway system is a complex technical system-of-systems (SoS). To address the complexity of the railway system, a holistic approach is needed that facilitates the development of an appropriate asset management regime. A systems-of-systems (SoS) approach considers the complex nature of the railway system, comprising interconnected subsystems like rolling stock and infrastructure. Neglecting these interdependencies risks sub-optimization of the overall system performance. Asset management, of the railway system utilising a SoS approach ensures the focus of asset management on overall system requirements. The efficiency and effectiveness of the railway system is based on aspects such as availability, reliability, and safety performance. To enhance these aspects, monitoring, and improvement of key performance indicators (KPIs) emphasizing increased capacity and reduced operational costs is essential. The KPIs offer quantifiable parameters for performance optimization. Augmenting asset management through data-driven technologies can improve the efficiency and effectiveness of asset management. However, challenges persist in the implementation of data-driven solutions due to the railway system's complexity and lack of a holistic perspective. A systematic performance-driven framework with a system-of-systems approach for augmented asset management of railway system provides handrail for the utilisation of data-driven technologies with railway system requirements at the centre while developing an asset management regime. The proposed framework aims to establish a clear relationship between system KPIs, and the performance of sub-systems and components aiding railway organizations in asset management design and implementation. This paper explains the important components of the proposed framework and demonstrates the application the framework for asset management and maintenance planning of high value components in the fleet of railway rolling stock. Adoption of the proposed framework is expected to enhance asset management through development and implementation of data-driven solutions that are aligned with system KPIs, to support asset management decision making.
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| 5. |
- 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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| 6. |
- Kumari, Jaya, et al.
(författare)
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Augmented asset management in railways - Issues and challenges in rolling stock
- 2022
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Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit. - : Sage Publications. - 0954-4097 .- 2041-3017. ; 236:7, s. 850-862
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Tidskriftsartikel (refereegranskat)abstract
- Managing assets in railway, including infrastructure and rolling stock, efficiently and effectively is challenging. The emerging digital technologies and Artificial Intelligence (AI) are expected to augment the decision making in Asset Management (AM) and Fleet Management (FM). The AI technologies need to be adapted to the specific needs of any industrial domain, e.g. railways, to facilitate the implementation and achievement of the overall business goals. This adaptation is denoted as ‘Industrial AI’(IAI). IAI for railways infrastructure and rolling stock, is dependent on an appropriate technology roadmap reflecting necessary know-hows. The IAI roadmap aims to provide a strategic and executive plan to augment managing railway assets i.e. ‘Augmented Asset Management (AAM)’. AAM can be applied through an end-to-end secure platform for e.g. data sharing among stakeholders, the development of analytics, and model sharing through distributed computing. AAM in railways can be enhanced through implementation of a generic fleet management (FM) approach. In the FM approach, any population of assets with common characteristics and also the relationship of the asset to the fleet is considered. This paper aims to develop and propose a concept for AAM enabled through IAI and digital technologies to provide augmented decision support through a secure platform, for AM in railways. A FM approach towards a holistic operation and maintenance of assets, based on a System of Systems thinking, for AAM in railways is applied for population of infrastructure assets and rolling stock assets with common characteristics. Finally, a taxonomy of issues and challenges, in the application of AAM to FM in railways is provided. The data for this taxonomy has been collected from railway organizations through iterative rounds of interviews. This taxonomy can be used for research and development of frameworks, approaches, technologies, and methodologies for AAM in railways.
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| 7. |
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| 8. |
- kumari, jaya, 1984-
(författare)
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Dynamic maintenance policy development for railway rolling stock
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Ingår i: Journal of Quality in Maintenance Engineering. - 1355-2511 .- 1758-7832.
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThis paper proposes an approach for the development of a dynamic maintenance policy for the railway rolling stock system considering the dynamic characteristics of the system, the operation environment, and the maintenance process. The proposed approach can also be applied to other similar complex technical systems.Design/methodology/approachThis study explores the state-of-the-art in dynamic maintenance policy development for rolling stock to identify research gap. The proposed approach is demonstrated through a case study on dynamic maintenance policy development for rolling stock maintenance support planning, emphasizing constant assessment and improvement in the maintenance policy.FindingsThis study emphasises on the need for an effective, efficient, and dynamic maintenance policy that adapts to evolving system requirements such as organizational contexts, technological advancements, and regulatory requirements.This study finds that there are specific dynamic characteristics in each step of the maintenance policy development process. These dynamic characteristics are dependent on the changes in system requirements, the environment and in the maintenance process. The proposed approach for dynamic maintenance policy development provides a framework for the identification of these dynamic characteristics for different complex technical systems operating in a specific context.OriginalityDespite the significant impact of rolling stock maintenance on railway system availability, research in this area is limited. The proposed approach for maintenance policy development for rolling stock integrates adaptability and responsiveness to dynamic factors in the maintenance process and the system requirements. Thus, the proposed approach provides a guide for industry professionals and directions for future research in dynamic maintenance policy development for other similar complex technical systems.
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| 9. |
- Kumari, Jaya, et al.
(författare)
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MetaAnalyser - A Concept and Toolkit for Enablement of Digital Twin
- 2022
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Ingår i: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; 55:2, s. 199-204
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Tidskriftsartikel (refereegranskat)abstract
- Digital Twin (DT) has promising impact on the life cycle management of assets in manufacturing industry. The concept of DT has become possible with digitalisation and Artificial Intelligence (AI). Data driven Machine Learning (ML) capabilities, can enhance the performance of the DT. To replicate a dynamic system, the DT should continuously receive and process incoming data in real-time. However, every time that the system receives new incoming datasets, the challenges of ML such as data preparation, feature selection, model selection and performance evaluation, slow down the development process of DT. This paper proposes a MetaAnalyser platform that automates these steps for incoming datasets in real-time. The MetaAnalyser platform through automating data preparation, feature selection, model selection and performance evaluation, is expected to increase the level of agility in the development process of DT and the efficiency of the DT during its lifecycle. The MetaAnalyser platform is demonstrated in this paper by ranking the features that affect the arrival delays in trains and ranking regression models based on their performance on the dataset.
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| 10. |
- Kumari, Jaya, et al.
(författare)
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Use Cases of Generative AI in Asset Management of Railways
- 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. 15-29
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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