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- 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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| 2. |
- Al-Jumaili, Mustafa, et al.
(författare)
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Data quality assessment using multi-attribute : maintenance perspective
- 2018
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Ingår i: International Journal of Information and Decision Sciences. - : InderScience Publishers. - 1756-7017 .- 1756-7025. ; 10:2, s. 147-161
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Tidskriftsartikel (refereegranskat)abstract
- The paper proposes a model for data quality (DQ) assessment in maintenance. Data has become an increasingly important since most of the maintenance planning and implementations are based on data analysis. Poor DQ reduces customer satisfaction, leading to poor decision making, and has negative impacts on strategy execution. To improve DQ as well as to evaluate the current status, DQ needs to be measured. A measure for DQ could be an important support for decision makers. Multi-criteria decision-making (MCDM) methods can provide a framework for DQ assessment, however, they are not used in literature for DQ assessment. In order to assess DQ, the attributes or KPIs need to be defined, their hierarchy should be designed and the assessment model is proposed to evaluate these attributes. A case study is also presented in this paper. The study shows that MCDM methods could provide qualitative estimation for the quality of DQ attributes.
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| 5. |
- Jägare, Veronica
(författare)
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A Challenge-driven Framework for Innovations in Railways
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The railway is often perceived as an industry where new technology is not utilised to its full potential. However, the future of the railway and its ability to respond to future transportation demands lies in its ability to adopt, adapt, implement, and integrate emerging technology. These technologies are expected to lead to, e.g. intelligent asset lifecycle management with a whole-life asset approach and digital railway industry supply chain management. The technology transformation and digitalisation affect not only the technical systems, e.g. railway infrastructure and rolling stock, but also regulations, organisations, processes, and individuals. The railway industry needs to recognise the challenges and define strategies, which enable the successful implementation of innovations in railway. Thus, the purpose of this research work is to study, explore, and investigate how implementation of innovations in a multi-stakeholder environment such as railway maintenance, can be facilitated through a systematic approach. Further, the main objective of this research is to develop and provide, a challenge-driven framework that can be used to facilitate implementation of innovations in the Swedish railway. To achieve the purpose of this research, nine (9) descriptive and exploratory case studies have been carried out. In these case studies, issues and challenges have been identified, related to: a) Lead times; b) Complex multi-stakeholder environment; c) Business incentives; d) Governance for data sharing; e) Regulations and maintenance; f) Technology; g) Assessment of innovations; h) Business models; i) Responsibilities, and j) Implementation.To overcome the identified challenges, several artefacts have been developed and provided in this research, i.e. a) A challenge-driven mission-based framework; b) A methodology for evaluating innovations; c) Strategies and guidelines for data governance; d) Strategies and guidelines for innovation in maintenance contracts; and e) Railway domain systemic aspects for the implementation pathway. The findings and artefacts of this study may be used as a framework and a road map in any industry by providing scientific guidance in the implementation of innovations. Some of the expected benefits for organisations are: a) Reduced development and production costs; b) Increased efficiency in testing, implementing, and utilising existing innovations; c) Increased awareness in data sharing; and d) Increased implementation support. Furthermore, in the context of railway maintenance, the artefacts from this study are expected to improve the overall effectiveness and efficiency through facilitating the implementation of innovations that support digitalisation of railway maintenance. The digitalisation of railway maintenance enables fact-based decision support utilising enhanced analytics aimed for nowcasting and forecasting. These capabilities will lead to: a) Improved knowledge and information exchange between railway stakeholders to enable efficient asset management; b) Enhanced condition monitoring; c) Improved risk management; and d) Improved sustainability.
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| 6. |
- Jägare, Veronica, et al.
(författare)
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A framework for testbed concept in railway
- 2019
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Ingår i: Proceedings of the International Heavy Haul Association STS Conference (IHHA 2019). - : International Heavy Haul Association (IHHA). ; , s. 986-
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Konferensbidrag (refereegranskat)abstract
- One major prerequisite for an effective implementation and innovation process is the enablement and provision of a collaborative environment. A common area for multi-organisational collaboration together with a technology platform, enabling data sharing and Big Data Analytics, has been developed called ‘Testbed Railway’ with a corresponding framework ‘Railway 4.0’. Testbed Railway can be used to strengthen the railway industry's adaptability and competitiveness by developing and providing a testbed for research and innovation in the rail industry, nationally and internationally.
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| 7. |
- Jägare, Veronica, et al.
(författare)
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Change management in digitalised operation and maintenance of railway
- 2019
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Ingår i: PROCEEDINGS: International Heavy Haul Association Conference June 2019. - 9780911382716 - 9780911382709 ; , s. 904-911
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Konferensbidrag (refereegranskat)abstract
- Globally, railway is experiencing a major technology transformation (or paradigm shift), triggered by the enhanced utilisation of digital technology. This technological transformation affects not only the technical systems, i.e. railway infrastructure and rolling stock, but also regulations, organisations, processes,and individuals. Hence, hardware, software, but also liveware (i.e. humans) are affected. Today, the digitalisation of railway is characterised by digital services. There are also a range of challenges, e.g. data acquisition,transformation, modelling, processing, visualisation, safety, security, quality, and information assurance. To deal with these challenges, the railway industry needs to define strategies, which enable a smooth transformation of the existing configuration to a digitalised system. Digital railway requires a holistic change management approach based on system-of-systems thinking and a set of appropriate technologies and methodologies. The railway digitalisation strategy should be based on systematic risk management that address aspects of, e.g., information security, traffic safety and project risk. In addition, managing changes for a digitalised railway effectively and efficiently also requires a framework for aspects such as needs finding, requirement identification, and impact of changes for individual, teams and organisation. In this work a major case studywithin the ePilot, has been performed in context of the operation and maintenance processes of the Swedish railway. Therefore, this paper aims to propose a framework for implementing innovations and driving change in a digitalised railway.
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| 8. |
- Jägare, Veronica, et al.
(författare)
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Governance of digital data sharing in a cross-organisational railway maintenance context
- 2019
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Ingår i: Proceedings of the 5<sup>th</sup> International Workshop and Congress on eMaintenance. - : Luleå University of Technology. ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- The purpose of this paper is to study and explore the essential aspects of data governance in eMaintenance that need to be considered such as data sharing and data ownership in a cross-organisational railway maintenance context. Furthermore, the paper develops and provides an approach to strategies and guidelines, which can be used to govern digital data sharing.To fulfil this purpose, case studies of several projects where sharing of data between stakeholders in order to develop maintenance decision support, was selected as a research strategy and supported by a literature study. Empirical data were collected through interviews, workshops, document studies, and observations. An approach was developed and validated using a case study.The proposed approach supports the understanding and establishing strategies and guidelines for data governance in a cross-organisational railway context. This can be considered as one of the enablers for information logistics for maintenance purposes where the approach can be used as a support tool in order to facilitate the development of maintenance decision support within the railway industry.
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| 9. |
- Karim, Ramin, 1964-, et al.
(författare)
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AI Factory -- A Framework for Digital Asset Management
- 2021
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Ingår i: Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021). - Singapore : Research Publishing Services. ; , s. 1160-1167
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Konferensbidrag (refereegranskat)abstract
- Advanced analytics empowered by Artificial Intelligence (AI) contributes to the achievement of global sustainability and business goals. It will also contribute to global competitiveness of enterprises through enablement of fact-based decisionmaking and improved insight. The digitalisation process currently ongoing in industry, and the corresponding implementation of AI technologies, requires availability and accessibility of data and models. Data and models are considered as digital assets (ISO55K) that impact a system’s dependability during its whole lifecycle. Digitalisation and implementation of AI in complex technical systems such as found in railway, mining, and aerospace industries is challenging. From a digital asset management perspective, the main challenges can be related to source integration, content processing, and cybersecurity.However, to effectively and efficiently retain the required performance of a complex technical system during its lifecycle, there is a need of appropriate concepts, methodologies, and technologies. With this background, Luleå University of Technology, in cooperation with a number of Swedish railway stakeholders – fleet managers, railway undertakings, infrastructure managers and Original Equipment Manufacturers (OEM), has created a universal platform called ‘the AI Factory’ (AIF). The concept of AIF has further been specialised for railway industry, so called AI Factory for Railway (AIF/R).Hence, this paper aims to provide a description of findings from the development and implementation of ‘AI Factory (AIF)’ in the railway context. Furthermore, the paper provides a case-study description used to verify the developed technologies and methodologies within AIF/R.
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