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Famurewa, Stephen MayowaORCID iD iconorcid.org/0000-0001-9843-5819
Publications (10 of 55) Show all publications
Kasraei, A., Garmabaki, A. H., Odelius, J., Famurewa, S. M., Chamkhorami, K. S. & Strandberg, G. (2024). Climate change impacts assessment on railway infrastructure in urban environments. Sustainable cities and society, 101, Article ID 105084.
Open this publication in new window or tab >>Climate change impacts assessment on railway infrastructure in urban environments
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2024 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 101, article id 105084Article in journal (Refereed) Published
Abstract [en]

Climate change impacts can escalate the deteriorating rate of infrastructures and impact the infrastructure’s functionality, safety, operation and maintenance (O&M). This research explores climate change’s influence on urban railway infrastructure. Given the geographical diversity of Sweden, the railway network is divided into different climate zones utilizing the K-means algorithm. Reliability analysis using the Cox Proportional Hazard Model is proposed to integrate meteorological parameters and operational factors to predict the degree of impacts of different climatic parameters on railway infrastructure assets. The proposed methodology is validated by selecting a number of switches and crossings (S&Cs), which are critical components in railways for changing the route, located in different urban railway stations across various climate zones in Sweden. The study explores various databases and proposes a climatic feature to identify climate-related risks of S&C assets. Furthermore, different meteorological covariates are analyzed to understand better the dependency between asset health and meteorological parameters. Infrastructure asset managers can tailor suitable climate adaptation measures based on geographical location, asset age, and other life cycle parameters by identifying vulnerable assets and determining significant covariates. Sensitivity analysis of significant covariates at one of the urban railway stations shows precipitation increment reveal considerable variation in the asset reliability.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Climate change adaptation, Reliability analysis, Cox proportional hazard model, Railway infrastructure
National Category
Other Civil Engineering Meteorology and Atmospheric Sciences
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-103152 (URN)10.1016/j.scs.2023.105084 (DOI)
Funder
Vinnova, 2021- 02456, 2019-03181The Kempe Foundations, JCK-2215
Note

Validerad;2023;Nivå 2;2023-12-04 (joosat);

License full text: CC BY 4.0

Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2023-12-04Bibliographically approved
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
Famurewa, S. & Kirilmaz, E. (2024). LCC Based Requirement Specification for Railway Track System. 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 (pp. 343-353). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>LCC Based Requirement Specification for Railway Track System
2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 343-353Conference 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-103879 (URN)10.1007/978-3-031-39619-9_25 (DOI)2-s2.0-85181980856 (Scopus ID)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-01-23Bibliographically approved
Soleimani-Chamkhorami, K., Garmabaki, A. S., Kasraei, A., Famurewa, S. M., Odelius, J. & Strandberg, G. (2024). Life cycle cost assessment of railways infrastructure asset under climate change impacts. Transportation Research Part D: Transport and Environment, 127, Article ID 104072.
Open this publication in new window or tab >>Life cycle cost assessment of railways infrastructure asset under climate change impacts
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2024 (English)In: Transportation Research Part D: Transport and Environment, ISSN 1361-9209, E-ISSN 1879-2340, Vol. 127, article id 104072Article in journal (Refereed) Published
Abstract [en]

Climate change impacts such as extreme temperatures, snow and ice, flooding, and sea level rise posed significant threats to railway infrastructure networks. One of the important questions that infrastructure managers need to answer is, “How will maintenance costs be affected due to climate change in different climate change scenarios?” This paper proposes an approach to estimate the implication of climate change on the life cycle cost (LCC) of railways infrastructure assets. The proportional hazard model is employed to capture the dynamic effects of climate change on reliability parameters and LCC of railway assets. A use-case from a railway in North Sweden is analyzed to validate the proposed process using data collected over 18 years. The results have shown that precipitation, temperature, and humidity are significant weather factors in selected use-case. Furthermore, our analyses show that LCC under future climate scenarios will be about 11 % higher than LCC without climate impacts.

Place, publisher, year, edition, pages
Elsevier Ltd, 2024
Keywords
Climate adaptation, Climate change, Life cycle cost analysis, Proportional hazard model, Railway infrastructure, Reliability analysis
National Category
Infrastructure Engineering
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-104359 (URN)10.1016/j.trd.2024.104072 (DOI)2-s2.0-85184743796 (Scopus ID)
Note

Funder: Vinnova (2019-03181, 2021-02456); Kempe foundation (JCK-3123); Järnvägstekniskt Centrum, Luleå Tekniska Universitet; Trafikverket; Kempe Foundation; Sveriges Meteorologiska och Hydrologiska Institut;

Full text license: CC BY

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-22
Garmabaki, A. S., Naseri, M., Odelius, J., Juntti, U., Famurewa, S., Barabady, J., . . . Strandberg, G. (2024). Risk Assessment of Climate Change Impacts on Railway Infrastructure Asset. 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 (pp. 773-788). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Risk Assessment of Climate Change Impacts on Railway Infrastructure Asset
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2024 (English)In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 773-788Conference 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-103883 (URN)10.1007/978-3-031-39619-9_57 (DOI)2-s2.0-85181981308 (Scopus ID)
Conference
7th International Congress and Workshop on Industrial AI and eMaintenance, IAI 2023, Luleå, Sweden, June 13-15, 2023
Funder
Vinnova, 2019-03181Vinnova, 2021-02456
Available from: 2024-01-23 Created: 2024-01-23 Last updated: 2024-02-01Bibliographically 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
Garmabaki, A. S., Odelius, J., Thaduri, A., Famurewa, S. M., Kumar, U., Strandberg, G. & Barabady, J. (2022). Climate Change Impact Assessment on Railway Maintenance. In: Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, Simon Wilson (Ed.), Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022): . Paper presented at 32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland, August 28 - September 1, 2022. Singapore: Research Publishing, Article ID S25-01-126.
Open this publication in new window or tab >>Climate Change Impact Assessment on Railway Maintenance
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2022 (English)In: Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022) / [ed] Maria Chiara Leva, Edoardo Patelli, Luca Podofillini, Simon Wilson, Singapore: Research Publishing , 2022, article id S25-01-126Conference paper, Published paper (Refereed)
Abstract [en]

Modern societies have become more and more complex, interconnected, and heavily dependent ontransport infrastructure. Moreover, most transport infrastructures were conceptualized, designed and built withoutanticipating the future variations of climate change. Climate changes have a negative impact on the railway systemand related costs. Increased temperatures, precipitation, sea levels, and frequency of extremely adverse weatherevents such as floods, heatwaves, and heavy snowfall pose major risks and consequences for railway infrastructureassets, operations and maintenance. Approximately, 5 to 10% of total failures and 60% of delays of trains are dueto various climate change impacts of railway infrastructure in northern Europe. In Sweden, weather-related failureswere responsible for 50% of train delays in switches and crossings (S&C).The paper explores a pathway toward climate resilience in transport networks and assess the climate change impactson railway infrastructure by integrating transport infrastructure health information with meteorological, satellite,and expert knowledge. The paper provides recommendations considering adaptation options to ensure an effectiveand efficient railway transport operation and maintenance.

Place, publisher, year, edition, pages
Singapore: Research Publishing, 2022
Keywords
Resilient railway infrastructure, Climate change, Climate adaptation, Extreme weather condition
National Category
Reliability and Maintenance
Research subject
Operation and Maintenance Engineering
Identifiers
urn:nbn:se:ltu:diva-93542 (URN)10.3850/978-981-18-5183-4_S25-01-126-cd (DOI)
Conference
32nd European Safety and Reliability Conference (ESREL 2022), Dublin, Ireland, August 28 - September 1, 2022
Projects
Robust infrastructure – Adapting railway maintenance to climate change (CliMaint)
Funder
Vinnova, 2019-03181
Note

ISBN for host publication: 978-981-18-5183-4

Available from: 2022-10-11 Created: 2022-10-11 Last updated: 2024-02-01Bibliographically approved
Garmabaki, A. S., Thaduri, A., Famurewa, S. M. & Kumar, U. (2021). Adapting Railway Maintenance to Climate Change. Sustainability, 13(24), Article ID 13856.
Open this publication in new window or tab >>Adapting Railway Maintenance to Climate Change
2021 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 13, no 24, article id 13856Article in journal (Refereed) Published
Abstract [en]

Railway infrastructure is vulnerable to extreme weather events such as elevated temperature, flooding, storms, intense winds, sea level rise, poor visibility, etc. These events have extreme consequences for the dependability of railway infrastructure and the acceptable level of services by infrastructure managers and other stakeholders. It is quite complex and difficult to quantify the consequences of climate change on railway infrastructure because of the inherent nature of the railway itself. Hence, the main aim of this work is to qualitatively identify and assess the impact of climate change on railway infrastructure with associated risks and consequences. A qualitative research methodology is employed in the study using a questionnaire as a tool for information gathering from experts from several municipalities in Sweden, Swedish transport infrastructure managers, maintenance organizations, and train operators. The outcome of this questionnaire revealed that there was a lower level of awareness about the impact of climate change on the various facets of railway infrastructure. Furthermore, the work identifies the challenges and barriers for climate adaptation of railway infrastructure and suggests recommended actions to improve the resilience towards climate change. It also provides recommendations, including adaptation options to ensure an effective and efficient railway transport service.

Place, publisher, year, edition, pages
MDPI, 2021
Keywords
climate change, climate adaptation, railway infrastructure, resilience of transport
National Category
Energy Systems
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-88639 (URN)10.3390/su132413856 (DOI)000742868800001 ()2-s2.0-85121468279 (Scopus ID)
Funder
Vinnova, 2019-0318
Note

Validerad;2022;Nivå 2;2022-01-03 (johcin)

Available from: 2022-01-03 Created: 2022-01-03 Last updated: 2023-02-28Bibliographically approved
Chandran, P., Thiery, F., Odelius, J., Famurewa, S. M., Lind, H. & Rantatalo, M. (2021). Supervised Machine Learning Approach for Detecting Missing Clamps in Rail Fastening System from Differential Eddy Current Measurements. Applied Sciences, 11(9), Article ID 4018.
Open this publication in new window or tab >>Supervised Machine Learning Approach for Detecting Missing Clamps in Rail Fastening System from Differential Eddy Current Measurements
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2021 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 11, no 9, article id 4018Article in journal (Refereed) Published
Abstract [en]

The rail fastening system forms an integral part of rail tracks, as it maintains the rail in a fixed position, upholding the track stability and track gauge. Hence, it becomes necessary to monitor their conditions periodically to ensure safe and reliable operation of the railway. Inspection is normally carried out manually by trained operators or by employing 2-D visual inspection methods. However, these methods have drawbacks when visibility is minimal and are found to be expensive and time consuming. In the previous study, the authors proposed a train-based differential eddy current sensor system that uses the principle of electromagnetic induction for inspecting the railway fastening system that can overcome the above-mentioned challenges. The sensor system includes two individual differential eddy current sensors with a driving field frequency of 18 kHz and 27 kHz respectively. This study analyses the performance of a machine learning algorithm for detecting and analysing missing clamps within the fastening system, measured using a train-based differential eddy current sensor. The data required for the study was collected from field measurements carried out along a heavy haul railway line in the north of Sweden, using the train-based differential eddy current sensor system. Six classification algorithms are tested in this study and the best performing model achieved a precision and recall of 96.64% and 95.52% respectively. The results from the study shows that the performance of the machine learning algorithms improved when features from both the driving channels were used simultaneously to represent the fasteners. The best performing algorithm also maintained a good balance between the precision and recall scores during the test stage.

Place, publisher, year, edition, pages
MDPI, 2021
Keywords
clamps, rail fastening system, differential eddy current sensor, machine learning, classification
National Category
Transport Systems and Logistics
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-84271 (URN)10.3390/app11094018 (DOI)000649877600001 ()2-s2.0-85105754999 (Scopus ID)
Funder
Luleå Railway Research Centre (JVTC)VinnovaSwedish Transport Administration
Note

Validerad;2021;Nivå 2;2021-05-18 (alebob)

Available from: 2021-05-17 Created: 2021-05-17 Last updated: 2023-09-05Bibliographically approved
Thaduri, A. & Famurewa, S. M. (2020). Evolution of Maintenance Processes in Industry 4.0. In: Alberto Martinetti, Micaela Demichela and Sarbjeet Singh (Ed.), Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0: (pp. 49-69). IGI Global
Open this publication in new window or tab >>Evolution of Maintenance Processes in Industry 4.0
2020 (English)In: Applications and Challenges of Maintenance and Safety Engineering in Industry 4.0 / [ed] Alberto Martinetti, Micaela Demichela and Sarbjeet Singh, IGI Global, 2020, p. 49-69Chapter in book (Refereed)
Abstract [en]

Several industries are looking for smart methods to increase their production throughput and operational efficiency at the lowest cost, reduced risk, and reduced spending of resources considering demands from stakeholders, governments, and competitors. To achieve this, industries are looking for possible solutions to the above problems by adopting emerging technologies. A foremost concept that is setting the pace and direction for many sectors and services is Industry 4.0. The focus is on augmenting machines and infrastructure with wireless connectivity, sensors, and intelligent systems to monitor, visualize, and communicate incidences between different entities for decision making. An aspect of physical asset management that has been enormously influenced by the new industrial set-up is the maintenance process. This chapter highlights the issues and challenges of Industry 4.0 from maintenance process viewpoint according to EN 60300-3-14. Further, a conceptual model on how maintenance process can be integrated into Industrial 4.0 architecture is proposed to enhance its value.

Place, publisher, year, edition, pages
IGI Global, 2020
Series
Advances in Civil and Industrial Engineering (ACIE), ISSN 2326-6139, E-ISSN 2326-6155
Keywords
EN 60300-3-14, Management, Planning, Preparation, Execution, Assessment, Improvement, Industrial revolution
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-78963 (URN)10.4018/978-1-7998-3904-0.ch003 (DOI)
Note

ISBN för värdpublikation: 9781799839040, 9781799839057

Available from: 2020-05-21 Created: 2020-05-21 Last updated: 2021-09-01Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-9843-5819

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