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Publications (10 of 397) Show all publications
Kasraei, A., Garmabaki, A. H., Odelius, J., Famurewa, S. M. & Kumar, U. (2024). Climate Zone Reliability Analysis of Railway Assets. In: International Congress and Workshop on Industrial AI and eMaintenance 2023: . Paper presented at 7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023. Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Climate Zone Reliability Analysis of Railway Assets
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2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Infrastructure Engineering Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103882 (URN)10.1007/978-3-031-39619-9_16 (DOI)2-s2.0-85181981181 (Scopus ID)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023
Funder
VinnovaThe Kempe Foundations
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-01-23Bibliographically approved
Kumar, U., Karim, R., Galar, D. & Kour, R. (2024). Editorial. In: Kumar U.; Karim R.; Galar D.; Kour R. (Ed.), International Congress and Workshop on Industrial AI and eMaintenance 2023: (pp. v-vi). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Editorial
2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023 / [ed] Kumar U.; Karim R.; Galar D.; Kour R., Springer Science and Business Media Deutschland GmbH , 2024, p. v-viChapter in book (Other academic)
Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2024
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103907 (URN)2-s2.0-85182009595 (Scopus ID)978-3-031-39618-2 (ISBN)978-3-031-39619-9 (ISBN)
Available from: 2024-01-24 Created: 2024-01-24 Last updated: 2024-01-24Bibliographically approved
Kumar, U., Karim, R., Galar, D. & Kour, R. (Eds.). (2024). International Congress and Workshop on Industrial AI and eMaintenance 2023. Paper presented at IAI: International Congress and Workshop on Industrial AI, Luleå, Sweden, 13-15 june, 2023. Springer
Open this publication in new window or tab >>International Congress and Workshop on Industrial AI and eMaintenance 2023
2024 (English)Conference proceedings (editor) (Refereed)
Place, publisher, year, edition, pages
Springer, 2024. p. 801
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356, E-ISSN 2195-4364
National Category
Reliability and Maintenance
Research subject
Quality Technology and Logistics
Identifiers
urn:nbn:se:ltu:diva-103915 (URN)10.1007/978-3-031-39619-9 (DOI)978-3-031-39618-2 (ISBN)978-3-031-39619-9 (ISBN)
Conference
IAI: International Congress and Workshop on Industrial AI, Luleå, Sweden, 13-15 june, 2023
Available from: 2024-01-24 Created: 2024-01-24 Last updated: 2024-01-24Bibliographically approved
Karim, R., Galar, D. & Kumar, U. (2023). AI Factory: Theories, Applications and Case Studies (1ed.). Taylor & Francis
Open this publication in new window or tab >>AI Factory: Theories, Applications and Case Studies
2023 (English)Book (Other academic)
Abstract [en]

This book provides insights into how to approach and utilise data science tools, technologies, and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI technologies and their interconnections. It includes descriptions of various technology and methodology approaches and their purpose and benefits when developing AI solutions in industrial contexts. In addition, this book summarises experiences from AI technology deployment projects from several industrial sectors. Features:

• Presents a compendium of methodologies and technologies in industrial AI and digitalisation.

• Illustrates the sensor-to-actuation approach showing the complete cycle, which defines and differentiates AI and digitalisation.

• Covers a broad range of academic and industrial issues within the field of asset management.

• Discusses the impact of Industry 4.0 in other sectors.

• Includes a dedicated chapter on real-time case studies.

This book is aimed at researchers and professionals in industrial and software engineering, network security, AI and machine learning (ML), engineering managers, operational and maintenance specialists, asset managers, and digital and AI manufacturing specialists.

Place, publisher, year, edition, pages
Taylor & Francis, 2023. p. 444 Edition: 1
Series
AI Factory: Theories, Applications and Case Studies
National Category
Computer Systems
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-99496 (URN)10.1201/9781003208686 (DOI)2-s2.0-85165345291 (Scopus ID)9781032077642 (ISBN)9781003208686 (ISBN)
Available from: 2023-08-11 Created: 2023-08-11 Last updated: 2023-08-11Bibliographically approved
Rantatalo, M., Chandran, P., Thiery, F., Odelius, J., Gustafsson, C., Asplund, M. & Kumar, U. (2023). Evaluation of Measurement Strategy for Track Side Monitoring of Railway Wheels. Applied Sciences, 13(9), Article ID 5382.
Open this publication in new window or tab >>Evaluation of Measurement Strategy for Track Side Monitoring of Railway Wheels
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2023 (English)In: Applied Sciences, ISSN 2076-3417, Vol. 13, no 9, article id 5382Article in journal (Refereed) Published
Abstract [en]

Wheelsets form an indispensable part of the railway rolling stock and need to be periodically inspected to ensure stable, safe, reliable, and sustainable rail operation. Wheel profiles are usually inspected and measured in a workshop environment using handheld equipment or by utilizing wayside measuring equipment. A common practice for both methods is to measure the wheel profile at one position along the circumference of the wheel, resulting in a one-slice measurement strategy, based on the assumption that the wheel profile has the same shape independent of the measurement position along the wheel. In this article, the representability of a one-slice measurement strategy with respect to the wheel profile parameters is investigated using handheld measurement equipment. The calculated range of standard deviation of the parameters estimated such as flange height, flange width, flange slope, and hollow wear from the measurements shows a spread in the parameter value along the circumference of the wheel. As an initial validation of the results, measurements from the wayside monitoring systems were also investigated to see if a similar spread was visible. The spread was significantly higher for flange height, flange width, and flange slope estimated from wayside measurement equipment than for the same parameters estimated using the handheld measurement equipment.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
railway wheel, wheel profile, wheel parameters, wayside monitoring, condition monitoring
National Category
Other Civil Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-97646 (URN)10.3390/app13095382 (DOI)000987233600001 ()2-s2.0-85159355820 (Scopus ID)
Projects
InfraSweden2030, supported by Vinnova, Formas, and EnergimyndighetenShift2Rail project IN2SMART
Funder
Luleå Railway Research Centre (JVTC)Swedish Transport Administration
Note

Validerad;2023;Nivå 2;2023-05-29 (joosat);

Licens fulltext: CC BY License

Available from: 2023-05-29 Created: 2023-05-29 Last updated: 2023-09-05Bibliographically approved
Chamkhorami, K. S., Kasraei, A., Garmabaki, A. S., Famurewa, S. M., Kumar, U. & Odelius, J. (2023). Implications of Climate Change in Life Cycle Cost Analysis of Railway Infrastructure. In: Mário P. Brito; Terje Aven, Piero Baraldi; Marko Čepin; Enrico Zio (Ed.), Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023): . Paper presented at 33rd European Safety and Reliability Conference (ESREL 2023), Southampton, United Kingdom, September 3-8, 2023 (pp. 2089-2096). Research Publishing, Article ID P093.
Open this publication in new window or tab >>Implications of Climate Change in Life Cycle Cost Analysis of Railway Infrastructure
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2023 (English)In: Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023) / [ed] Mário P. Brito; Terje Aven, Piero Baraldi; Marko Čepin; Enrico Zio, Research Publishing , 2023, p. 2089-2096, article id P093Conference paper, Published paper (Other (popular science, discussion, etc.))
Abstract [en]

Extreme weather conditions from climate change, including high or low temperatures, snow and ice, flooding,storms, sea level rise, low visibility, etc., can damage railway infrastructure. These incidents severely affect the reliability of the railway infrastructure and the acceptable service level. Due to the inherent complexity of the railway system, quantifying the impacts of climate change on railway infrastructure and associated expenses has been challenging. To address these challenges, railway infrastructure managers must adopt a climate-resilient approach that considers all cost components related to the life cycle of railway assets. This approach involves implementing climate adaptation measures to reduce the life cycle costs (LCC) of railway infrastructure while maintaining the reliability and safety of the network. Therefore, it is critical for infrastructure managers to predict, "How will maintenance costs be affected due to climate change in different RCP's scenarios?"The proposed model integrates operation and maintenance costs with reliability and availability parameters such as mean time to failure (MTTF) and mean time to repair (MTTR). The proportional hazard model (PHM) is used to reflect the dynamic effect of climate change by capturing the trend variation in MTTF and MTTR. A use case from a railway in North Sweden is studied and analyzed to validate the process. Data collected over a 20-year period is analyzed for the chosen use case. As a main result, this study has revealed that climate change may significantly influence the LCC of switch and crossing (S&C) and can help managers predict the required budget.

Place, publisher, year, edition, pages
Research Publishing, 2023
Keywords
Life Cycle Cost Analysis, Switch and Crossing, Railway Infrastructure, Climate Adaptation
National Category
Civil Engineering Other Environmental Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103278 (URN)
Conference
33rd European Safety and Reliability Conference (ESREL 2023), Southampton, United Kingdom, September 3-8, 2023
Funder
Vinnova, 2021-02456Vinnova, 2019-03181The Kempe Foundations, JCK-2215Swedish Transport AdministrationSwedish Meteorological and Hydrological InstituteLuleå Railway Research Centre (JVTC)
Note

Funder: SWECO AB; WSP AB; InfraNord; BnearIT;

Host for ISBN: 978-981-18-8071-1

Available from: 2023-12-08 Created: 2023-12-08 Last updated: 2024-02-12Bibliographically approved
Galar, D. & Kumar, U. (2023). Robotics and artificial intelligence (AI) for maintenance. In: Pasquale Daponte, Florentin Paladi (Ed.), Monitoring and Protection of Critical Infrastructure by Unmanned Systems: (pp. 206-223). IOS Press
Open this publication in new window or tab >>Robotics and artificial intelligence (AI) for maintenance
2023 (English)In: Monitoring and Protection of Critical Infrastructure by Unmanned Systems / [ed] Pasquale Daponte, Florentin Paladi, IOS Press , 2023, p. 206-223Chapter in book (Other academic)
Abstract [en]

This paper reviews the application of AI in maintenance and inspections. It gives an overview of the development of AVs and distant inspection operations for industrial assets using unmanned aerial vehicles (UAVs). It discusses the use of AVs in infrastructure inspection and explain the types of sensors used for these applications. It explains how autonomous robots, including drones, are currently used in various industrial settings for inspection and maintenance. The paper concludes by discussing the use of AI in predictive maintenance.

Place, publisher, year, edition, pages
IOS Press, 2023
Series
NATO Science for Peace and Security Series - D: Information and Communication Security, ISSN 1874-6268, E-ISSN 1879-8292 ; 63
Keywords
AI, Failure, Faults, Maintenance, Robotics, UAV
National Category
Robotics Computer Sciences
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-97069 (URN)10.3233/NICSP230016 (DOI)2-s2.0-85153842204 (Scopus ID)978-1-64368-376-8 (ISBN)978-1-64368-377-5 (ISBN)
Available from: 2023-05-10 Created: 2023-05-10 Last updated: 2023-05-10Bibliographically approved
Vila Forteza, M., Galar Pascual, D., Kumar, U. & Verma, A. (2023). Work-In-Progress: Reliability Prediction of Api Centrifugal Pumps Using Survival Analysis. In: Zsolt János Viharos; Lorenzo Ciani; Piotr Bilski (Ed.), 19th IMEKO TC10 Conference: “MACRO meets NANO in Measurement for Diagnostics, Optimization and Control”: Proceedings. Paper presented at 19th IMEKO TC10 Conference: "MACRO meets NANO in Measurement for Diagnostics, Optimization and Control", Delft, Netherlands, September 21-22, 2023 (pp. 116-121). International Measurement Confederation (IMEKO)
Open this publication in new window or tab >>Work-In-Progress: Reliability Prediction of Api Centrifugal Pumps Using Survival Analysis
2023 (English)In: 19th IMEKO TC10 Conference: “MACRO meets NANO in Measurement for Diagnostics, Optimization and Control”: Proceedings / [ed] Zsolt János Viharos; Lorenzo Ciani; Piotr Bilski, International Measurement Confederation (IMEKO) , 2023, p. 116-121Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
International Measurement Confederation (IMEKO), 2023
National Category
Computational Mathematics Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103369 (URN)10.21014/tc10-2023.018 (DOI)
Conference
19th IMEKO TC10 Conference: "MACRO meets NANO in Measurement for Diagnostics, Optimization and Control", Delft, Netherlands, September 21-22, 2023
Note

ISBN for host publication: 978-92-990090-4-8

Available from: 2023-12-20 Created: 2023-12-20 Last updated: 2023-12-20Bibliographically approved
Galar, D. & Kumar, U. (2022). Advanced Analytics for Modern Mining. In: Soofastaei, A. (Ed.), Advanced Analytics in Mining Engineering: Leverage Advanced Analytics in Mining Industry to Make Better Business Decisions (pp. 23-54). Springer Nature
Open this publication in new window or tab >>Advanced Analytics for Modern Mining
2022 (English)In: Advanced Analytics in Mining Engineering: Leverage Advanced Analytics in Mining Industry to Make Better Business Decisions / [ed] Soofastaei, A., Springer Nature, 2022, p. 23-54Chapter in book (Other academic)
Place, publisher, year, edition, pages
Springer Nature, 2022
National Category
Computer Sciences Computer Systems
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-97236 (URN)10.1007/978-3-030-91589-6_2 (DOI)2-s2.0-85156183120 (Scopus ID)
Note

ISBN för värdpublikation: 978-3-030-91588-9, 978-3-030-91591-9, 978-3-030-91589-6

Available from: 2023-05-17 Created: 2023-05-17 Last updated: 2023-05-17Bibliographically approved
Galar, D., Seneviratne, D. & Kumar, U. (2022). Big Data in Railway O&M: A Dependability Approach. In: Research Anthology on Big Data Analytics, Architectures, and Applications: (pp. 391-416). IGI Global, 1
Open this publication in new window or tab >>Big Data in Railway O&M: A Dependability Approach
2022 (English)In: Research Anthology on Big Data Analytics, Architectures, and Applications, IGI Global, 2022, Vol. 1, p. 391-416Chapter in book (Other academic)
Abstract [en]

Railway systems are complex with respect to technology and operations with the involvement of a wide range of human actors, organizations and technical solutions. For the operations and control of such complexity, a viable solution is to apply intelligent computerized systems, for instance, computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by only applying operation and maintenance activities. Indeed, safety is a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them and trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Big data analytics are expected to improve the overall performance of the railways supported by smart systems and Internetbased solutions. Operation and Maintenance will be application areas, where benefits will be visible as a consequence of big data policies due to diagnosis and prognosis capabilities provided to the whole network of processes. This chapter shows the possibilities of applying the big data concept in the railway transportation industry and the positive effects on technology and operations from a systems perspective. © 2022 by IGI Global. All rights reserved.

Place, publisher, year, edition, pages
IGI Global, 2022
National Category
Infrastructure Engineering Software Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-90987 (URN)10.4018/978-1-6684-3662-2.ch019 (DOI)2-s2.0-85130128941 (Scopus ID)
Note

ISBN för värdpublikation: 978-166843663-9, 978-166843662-2

Available from: 2022-06-09 Created: 2022-06-09 Last updated: 2022-06-09Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8111-6918

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