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  • 1.
    Candell, Olov
    et al.
    Saab BA Aeronautics, 732 47, Arboga, Sweden.
    Hällqvist, Robert
    Saab BA Aeronautics, 581 88, Linköping, Sweden.
    Olsson, Ella
    Saab BA Aeronautics, 17541, Järfälla, Sweden.
    Fransson, Torbjörn
    Saab BA Aeronautics, 581 88, Linköping, Sweden.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cyber-Physical Asset Management of Air Vehicle System2024In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 679-692Conference paper (Other academic)
  • 2.
    Galar, Diego
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Context awareness for maintenance decision making: A diagnosis and prognosis approach2015In: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 67, p. 137-150Article in journal (Refereed)
    Abstract [en]

    All assets necessarily suffer wear and tear during operation. Prognostics can assess the current health of a system and predict its remaining life based on features capturing the gradual degradation of its operational capabilities. Prognostics are critical to improve safety, plan successful work, schedule maintenance, and reduce maintenance costs and down time. Prognosis is a relatively new area but has become an important part of Condition-based Maintenance (CBM) of systems. Broadly stated, prognostic methods are either data-driven, rule based, or model-based. Each approach has advantages and disadvantages; consequently, they are often combined in hybrid applications. A hybrid model can combine some or all model types; thus, more complete information can be gathered, leading to more accurate recognition of the fault state. In this context, it is important to evaluate the consistency and reliability of the measurement data obtained during laboratory testing and the prognostic/diagnostic monitoring of the system under examination.This approach is especially relevant in systems where the maintainer and operator know some of the failure mechanisms with a sufficient amount of data, but the sheer complexity of the assets precludes the development of a complete model-based approach. This paper addresses the process of data aggregation into a contextual awareness hybrid model to get Residual Useful Life (RUL) values within logical confidence intervals so that the life cycle of assets can be managed and optimised.

  • 3.
    Galar, Diego
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pascual, Rodrigo
    Pontificia Universidad Católica de Chile.
    SMART maintenance and prescriptive asset management for mining2016Conference paper (Refereed)
    Abstract [en]

    Operation and maintenance (O&M) activities are commonly organized into scheduled and unscheduled actions. Scheduled maintenance is undertaken during pre-programmed inspections. Such maintenance operations try to minimize the risk of deterioration based on a priori knowledge of failure mechanisms and their timing. However, in complex systems it is not always possible to schedule maintenance actions to mitigate all undesired effects, and SMART systems, which monitor selected parameters, propose actions to correct any deviation in normal behaviour. Indeed, SMARTness is one step beyond the prediction of failure time but also a proposition of operation and maintenance profiles in order to fulfill the company goals. Therefore prognosis and RUL estimation become a part of the process in order to achieve prescriptive actions and control the degradation and operational aspects of the asset as per expected demand and customer request. These O&M decisions must be made on the basis of accepted risk. Performed or unperformed scheduled tasks as well as deferred corrective actions can have positive or negative consequences for the company, technicians, and machines. These three risks should be properly assessed and prioritized as a function of the goals to be achieved. This paper focuses on the SMARTness of assets in order to go one step forwards and propose prescriptive O&M decisions based on a self-risk assessment as a trade-off for asset integrity and company goals.

  • 4.
    Galar, Diego
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Simon, Victor
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Prognostic Hybrid Modelling from Data Fusion on Machine Tools2016In: Measurement, ISSN 1536-6367, E-ISSN 1536-6359Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    This paper proposes an enhancement of remaining useful life (RUL) prediction method based on degradation trajectory tracking under the scope of machine tools. The operational condition data of the machine over time provides the potential degradation state at the next estimation iteration step, based on data-driven techniques. The model-based approach is considered as long-term prognostics method assuming that a physical model describing the degradation behaviour is available. Fusing the aforementioned techniques outputs a hybrid model for RUL estimation.

  • 5.
    Garmabaki, Amir H. S.
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Opportunistic inspection planning for Railway eMaintenance2016In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 49, no 28, p. 197-202Article in journal (Refereed)
    Abstract [en]

    Railway infrastructure is a complex system that comprises of several subsystems which interacts in hierarchical, multi-distributive and multi-user environment. It is a difficult task to perform inspections for all the assets at an instant because the train management system decides when to conduct different types of inspection techniques on several assets in a particular track section. There are two main wastes of resources for inspection planning occurred in maintenance; under usage due to inaccurate prediction of failure and over usage because the necessary information already has been acquired from other sources. These irregularities lead to wastage of resources, for instance, human, machine and time that has tremendous implications on cost, availability and manpower. This paper proposes a methodology by using intelligent functional test outcome to assess the performability of an asset and integrating the data to the eMaintenance cloud platform of Swedish railway infrastructure. By implementing this methodology, we can achieve better planning of resources for optimal performance of assets. A case study is performed on Switches and Crossings of Swedish railway infrastructure for the applicability of the proposed methodology.

  • 6.
    Garmabaki, Amir H. Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hedström, Annelie
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Laue, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Marklund, Stefan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Asplund, Matthias
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bansal, Tarun
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Indahl, Stefan
    Rörteknik, Arrsleff, Stockholm- HK, Symmetrivägen 29, 196 02 Kungsängen Sweden.
    A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections2019In: Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019) / [ed] Michael beer, Enrico Zio, Research Publishing Services, 2019, p. 1094-1101Conference paper (Refereed)
    Abstract [en]

    Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures are critical for society and industry resulting in direct and indirect costs for all the related stakeholders. Pipeline failures are complex processes, which are affected by many factors, both static (e.g., pipe material, size, age, and soil type) and dynamic (e.g., traffic load, pressure zone changes, and environmental impacts). These failures have serious impacts on public due to safety, disruption of traffic, inconvenience to society, environmental impacts and shortage of resources. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within transportation infrastructure. The aim of this study is to identify failure modes and consequences related to the crossing of pipelines in railway corridors. Expert opinion have been collected through two set of questionnaires which have been distributed to the 291 municipalities in the whole Sweden. The failure analysis revealed that pipe deformation has higher impact followed by pipe rupture at cross-section with railway infrastructure. For underground pipeline under railway infrastructure, aging and external load gets higher ranks among different potential failure causes to the pipeline.

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  • 7.
    Garmabaki, Amir Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Marklund, Stefan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hedström, Annelie
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Underground pipelines and railway infrastructure: failure consequences and restrictions2020In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 16, no 3, p. 412-430Article in journal (Refereed)
    Abstract [en]

    Underground pipelines are an essential part of the transportation infrastructure. The structural deterioration of pipelines crossing railways and their subsequent failures can entail critical consequences for society and industry, resulting in direct and indirect costs for all the stakeholders involved. Therefore, continuous and accurate condition assessment is critical for the effective management and maintenance of pipeline networks within the transportation infrastructure. The aim of this study has been to identify failure modes and consequences related to pipelines crossing railway corridors. Expert opinions have been collected through interviews and two sets of questionnaires have been distributed to the 291 municipalities in Sweden, with 137 responses in total. The failure analysis has revealed that pipe deformation has the highest impact, followed by pipe rupture at locations where pipelines cross railway infrastructure. For underground pipelines under railway infrastructure, ageing and the external load were awarded a higher ranking than other potential causes of pipeline failure.

    Authors gratefully acknowledge the funding provided by Sweden’sinnovation agency, Vinnova, through the strategic innovation programmeInfraSweden2030. The funding was granted in a competitiveapplication process that assessed replies to an open call for proposalsconcerning “Condition Assessment and Maintenance of TransportInfrastructure (Grant No. 2016-033113)”.

    Authors gratefully acknowledge the technical support and collaboration(In-kind support) of Arrsleff R€orteknik at Sweden, Luleå RailwayResearch Center (JVTC), Stormwater&Sewers and the SwedishTransport Administration (Trafikverket). In addition, the authors arethankful to the anonymous referees for their constructive commentsand Dr Matthias Asplund and Dr Masoud Naseri for their support andsuggestions.

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  • 8.
    Garmabaki, Amir Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Strandberg, Gustav
    Rossby Centre, Swedish Meteorological and Hydrological Institute, SMHI, Sweden.
    Barabady, Javad
    Department of Technology and Safety, UiT The Arctic University of Norway, Tromsø, Norway.
    Climate Change Impact Assessment on Railway Maintenance2022In: 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 (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.

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  • 9.
    Garmabaki, Amir Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Adapting Railway Maintenance to Climate Change2021In: Sustainability, E-ISSN 2071-1050, Vol. 13, no 24, article id 13856Article in journal (Refereed)
    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.

  • 10.
    Jiménez-Redondo, Noemi
    et al.
    CEMOSA.
    Calle-Cordón, Álvaro
    CEMOSA.
    Kandler, Ute
    Fraunhofer Inst Verkehrs & Infrastruktursyst IV.
    Simroth, Axel
    Fraunhofer Inst Verkehrs & Infrastruktursyst IV.
    Morales, Francisco J
    Univ Seville.
    Reyes, Antonio
    Univ Seville.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Morgado, Joao
    Infraestruturas Portugal SA.
    Duarte, Emmanuele
    Infraestruturas Portugal SA.
    Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)2017In: IOP Conference Series: Materials Science and Engineering, ISSN 1757-8981, E-ISSN 1757-899X, Vol. 236Article in journal (Refereed)
    Abstract [en]

    The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform ( the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

  • 11.
    Kans, Mirka
    et al.
    Linnaeus University.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance 4.0 in railway transportation industry2015Conference paper (Refereed)
    Abstract [en]

    Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organizations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerized systems, such as 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 applying operation and maintenance activities. Indeed safety becomes 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 trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilizing cyber-physical systems and intelligent factories that are based on the concept of "internet of things". Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry. This paper also discusses the positive effects on technology; organisation and operations from a systems perspective.

  • 12.
    Kans, Mirka
    et al.
    Linnaeus University.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance 4.0 in Railway Transportation Industry2016In: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015) / [ed] Kari T. Koskinen; Helena Kortelainen; Jussi Aaltonen; Teuvo Uusitalo; Kari Komonen; Joseph Mathew; Jouko Laitinen, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 317-331Conference paper (Refereed)
    Abstract [en]

    Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organisations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerised systems, such as computerised 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 applying operation and maintenance activities. Indeed safety becomes a more difficult goal to achieve using traditional maintenance strategies and computerised solutions come into the picture as the only option to deal with complex systems interacting among them trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilising cyber-physical systems and intelligent factories that are based on the concept of “internet of things”. Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry and the positive effects on technology, organisation and operations from a systems perspective.

  • 13.
    Kasraei, Ahmad
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Garmabaki, Amir Hossein Soleimani
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Chamkhorami, Khosro Soleimani
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Climate change and its weather hazard on the reliability of railway infrastructure2023In: Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023), Research Publishing Services , 2023, p. 2072-2078, article id P044Conference paper (Refereed)
  • 14.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cybersecurity for railways: A maturity model2020In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 234, no 10, p. 1129-1148Article in journal (Refereed)
    Abstract [en]

    With the advancements in and widespread adoption of information and communication technologies in infrastructures, cyber-attacks are becoming more frequent and more severe. Advanced cybersecurity threats with automated capabilities are increasing in such sectors as finance, health, grid, retail, government, telecommunications, transportation, etc. Cyber-attacks are also increasing in railways with an impact on railway stakeholders, e.g. threat to the safety of employees, passengers, or the public in general; loss of sensitive railway information; reputational damage; monetary loss; erroneous decisions; loss of dependability, etc. There is a need to move towards advanced security analytics and automation to identify, respond to, and prevent such security breaches. The objective of this research is to reduce cyber risks and vulnerabilities and to improve the cybersecurity capabilities of railways by evaluating their cybersecurity maturity levels and making recommendations for improvements. After assessing various cybersecurity maturity models, the Cybersecurity Capability Maturity Model (C2M2) was selected to assess the cybersecurity capabilities of railway organizations. The contributions of this research are as follows. First, a new maturity level MIL4 (Maturity Indicator Level 4) is introduced in the C2M2 model. Second, the C2M2 model is adapted by adding advanced security analytics and threat intelligence to develop the Railway-Cybersecurity Capability Maturity Model (R-C2M2). The cybersecurity maturity of three railway organizations is evaluated using this model. Third, recommendations and available standards & guidelines are provided to the three railway organizations to improve maturity levels within different domains. In addition, they are given an action plan to implement the recommendations in a streamlined way. The application of this model will allow railway organizations to improve their capability to reduce the impacts of cyber-attacks and eradicate vulnerabilities. The approach can also be extended to other infrastructures with necessary adaptations.

  • 15.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Patwardhan, Amit
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A Methodology for Cybersecurity Risk Assessment – A Case-study in Railway2022In: International Journal of COMADEM, ISSN 1363-7681, Vol. 25, no 2, p. 5-12Article in journal (Refereed)
    Abstract [en]

    Digitalisation is changing the railway globally. One of the major concerns in digital transformation of the railway is the increased exposure to cyberattacks. The railway is vulnerable to these cyberattacks because the number of digital items and number of interfaces between digital and physical components in these systems keep growing. Increased number of digital items and interfaces require new methodologies, frameworks, models, concepts, and architectures to ensure the railway system’s resilience with respect to cybersecurity challenges, such as adoption and convergence of Information Technology (IT) and Operational Technology (OT) technology within the railway. This convergence has brought significant benefits in reliability, operational efficiency, capacity as well as improvements in passenger experience but also increases the vulnerability towards cyberattacks from individuals, organizations, and governments. This paper proposes a methodology on how to deals with OT security in the railway signalling using failure mode, effects and criticality analysis (FMECA) and ISA/IEC 62443 security risk assessment methodologies.

  • 16.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Patwardhan, Amit
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A review on cybersecurity in railways2022In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017Article, review/survey (Refereed)
    Abstract [en]

    Digitalisation is transforming the railway globally. One of the major considerations in digital transformation of any industry including the railway is the increased exposure to cyberattacks. The railway industry is vulnerable to these attacks because since the number of digital items and also number of interfaces between digital and physical components in the railway systems keep increasing. Increased number of items and interfaces require new frameworks, concepts and architectures to ensure the railway system’s resilience with respect to cybersecurity challenges, such as lack of proactiveness, lack of holistic perspective and obsolescence of safety systems exposed to current and future cyber threats landscape. To this date, there are several works carried out in the literature that studied the cybersecurity aspects and its application on railway infrastructure. However, to develop and implement an appropriate roadmap to cybersecurity in railways, there is a need of describing emerging challenges, and approaches to deal with these challenges and the possibilities and benefits of these.Hence, the objective of this paper is to provide a systematic review and outline cybersecurity emerging trends and approaches, and also to identify possible solutions by querying literature, academic and industrial, for future directions. The authors of this paper conducted separate searches through four popular databases, that is, Google Scholar, Scopus, Web of Science and IEEE explore. For the screening process, authors have used keywords with Boolean operators and database filters and identified 90 articles most relevant to the study domain. The analysis of 90 articles shows that majority of the cybersecurity studies lies within the railways are conceptual and lags in application of Artificial Intelligence (AI) based security. Like other industries, it is very important that railways should also follow latest security technologies, trends and train their workforce for cyber hygiene since railways are already in digitalization transition mode.

  • 17.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Operational Security in the Railway - The Challenge2022In: International Congress and Workshop on Industrial AI 2021 / [ed] Ramin Karim, Alireza Ahmadi, Iman Soleimanmeigouni, Ravdeep Kour, Raj Rao, Springer, 2022, Vol. 1, p. 266-277Conference paper (Refereed)
  • 18.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Predictive model for multistage cyber-attack simulation2020In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 11, no 3, p. 600-613Article in journal (Refereed)
    Abstract [en]

    Adoption of information and communication technologies (ICT) in railway has improved the reliability, maintainability, operational efficiency, capacity as well as the comfort of passengers. This adoption introduces new vulnerabilities and entry points for hackers to launch attacks. Advanced cybersecurity threats with automated capabilities are increasing in such sectors as finance, health, grid, retail, government, telecommunications, transportation, etc. These cyber threats are also increasing in railways and, therefore, it needs for cybersecurity measures to predict, detect and respond these threats. The cyber kill chain (CKC) model is a widely used model to detect cyber-attacks and it consists of seven stages/chains; breaking the chain at an early stage will help the defender stop the adversary’s malicious actions. Due to lack of real cybersecurity data, this research simulates cyber-attacks to calculate the attack penetration probabilities at each stage of the cyber kill chain model. The objective of this research is to predict cyber-attack penetrations by implementing various security controls using modeling and simulation. This research is an extension of developed railway defender kill chain which provides security controls at each stage of CKC for railway organizations to minimize the risk of cyber threats.

  • 19.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Railway Defender Kill Chain for Cybersecurity2019In: Proceedings of the 5th International Workshop and Congress on eMaintenance:: eMaintenance: Trends in Technologies & methodologies, challenges, possibilites and applications / [ed] Miguel Castano Arranz; Ramin Karim, Luleå University of Technology, 2019, p. 20-27Conference paper (Refereed)
    Abstract [en]

    The railway is one of the most important infrastructures and its security is as important as other critical infrastructures. Due to the increase in cyber-attacks, there is an increasing trend in the field of cybersecurity. The history of cyber incidents suggested that the railway needs immediate security measures or defensive controls for forthcoming advanced persistent threats (APT). Cyber Kill Chain (CKC) is one of the most widely used models for the identification, detection, and prevention of advanced persistent threats. CKC model was introduced by Lockheed Martin that consists of seven stages as Reconnaissance, Weaponize, Delivery, Exploitation, Installation, Command & Control, and Act on Objective. Breaking the chain as early as possible in the CKC model will help the defender to stop adversary’s malicious actions. As the railway is adapting digital technologies and, therefore, there is a risk that adversary can penetrate into the system following the steps of CKC. The objective of this research is to reduce the risk of cyber-attacks by proposing Railway Defender Kill Chain (RDKC) that provides security controls at each phase of Cyber Kill Chain to predict, prevent, detect and respond to cyber threats.

  • 20.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Railway Defender Kill Chain to Predict and Detect Cyber-Attacks2020In: Journal of Cyber Security and Mobility, ISSN 2245-1439, E-ISSN 2245-4578, Vol. 9, no 1, p. 47-90Article in journal (Refereed)
    Abstract [en]

    Most organizations focus on intrusion prevention technologies, with lessemphasis on prediction and detection. This research looks at prediction anddetection in the railway industry. It uses an extended cyber kill chain (CKC)model and an industrial control system (ICS) cyber kill chain for detectionand proposes predictive technologies that will help railway organizationspredict and recover from cyber-attacks. The extended CKC model consistsof both internal and external cyber kill chain; breaking the chain at anearly stage will help the defender stop the adversary’s malicious actions.This research incorporates an OSA (open system architecture) for railwayswith the railway cybersecurity OSA-CBM (open system architecture forcondition-based maintenance) architecture. The railway cybersecurity OSA-CBM architecture consists of eight layers; cybersecurity information movesfrom the initial level of data acquisition to data processing, data analysis, inci-dent detection, incident assessment, incident prognostics, decision support,and visualization.The main objective of the research is to predict, prevent, detect, andrespond to cyber-attacks early in the CKC by using defensive controls calledthe Railway Defender Kill Chain (RDKC).The contributions of the research are as follows. First, it adapts and mod-ifies the railway cybersecurity OSA-CBM architecture for railways. Second,it adapts the cyber kill chain model for the railway. Third, it introduces theRailway Defender Kill Chain. Fourth, it presents examples of cyber-attackscenarios in the railway system.

  • 21.
    Kour, Ravdeep
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Mechanical Engineering Department, Government College of Engineering and Technology, Jammu, Jammu, India.
    Martinetti, Alberto
    Maintenance Engineering Group, Design, Production and Management Department, University of Twente, Enschede, The Netherlands.
    Big Data Analytics for Maintaining Transportation Systems2019In: Transportation Systems: Managing Performance through Advanced Maintenance Engineering / [ed] Sarbjeet Singh, Alberto Martinetti, Arnab Majumdar, Leo A. M. van Dongen, Springer , 2019, p. 73-91Chapter in book (Other academic)
    Abstract [en]

    Big Data Analytics (BDA) is becoming a research focus in transportation systems, which can be seen from many projects within the world. By using sensor and Internet of Things (IoT) technology in transportation system, huge amount of data is been generated from different sources. This data can be integrated, analyzed and visualized for efficient and effective decision-making for maintaining transportation systems. The key challenges that exist in managing Big Data are the designing of the systems, which would be able to handle huge amount of data efficiently and effectively and to filter the most significant information from all the collected data. This chapter will draw attention towards the present scenario and future projections of big data in transportation systems. It also presents big data tools and techniques and then presents one brief case study of BDA in each type of transportation system. In this chapter, a broad overview of Big Data definitions, its history, present, and future prospects are briefed. Several tools and technologies especially for transportation are pointed out for maintaining transportation systems. At the end of the chapter, a definitive case studies on each transportation area is demonstrated.

  • 22.
    Kumari, Jaya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Castano, Miguel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Augmented asset management in railways - Issues and challenges in rolling stock2022In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 236, no 7, p. 850-862Article in journal (Refereed)
    Abstract [en]

    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.

  • 23.
    Kumari, Jaya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Dersin, Pierre
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A framework for now-casting and forecasting in augmented asset management2022In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 13, no 5, p. 2640-2655Article in journal (Refereed)
    Abstract [en]

    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.

  • 24.
    Mishra, Madhav
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Nissen, Arne
    Trafikverket, Luleå.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Particle filter-based prognostic approach for railway track geometry2017In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 96, p. 226-238Article in journal (Refereed)
    Abstract [en]

    Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.

  • 25.
    Mishra, Madhav
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ontology based diagnosis for maintenance decisions of Paper Mill roller using dynamic response2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 187-196Conference paper (Refereed)
    Abstract [en]

    Context-aware systems have been applied in several fields like Information Technology, mobile, web services, travel guidance etc. These systems deliver decisions based on a ‘context’ by using contextual models. In paper industries, the failures of rollers were prominent and rolling element bearing is one of the critical components. The failure occurs due to the varying levels of the loads and external parameters that defines context. This paper demonstrates the ontology contextual modeling for the diagnosis of rollers as a context by using dynamic response. The roller is modeled using physical models and applying runs of different parameters and its levels. Then contextual models are generated for rollers to show relation among input contextual parameters with different features. This paper shows that this conceptual idea of decision based on different contexts using ontology models is for effective diagnosis facilitates maintenance strategies and further prospects in prognosis.

  • 26.
    Papic, Ljubisa
    et al.
    University of Kragujevac.
    Kovacevic, Srdja
    University of Kragujevac.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Investigation of Causes of Mining Machines Maintenance Problems2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 283-299Conference paper (Refereed)
    Abstract [en]

    Human errors in the area of mining engineering are of critical issue that has serious concerns in safety, operation and production performance. There is a need for finding cause and effect relations with respect to the maintenance issues in order to detect, scrutinize and take necessary actions to reduce it. This paper deals with the human errors in the mining machines for the maintenance problems using fishbone cause and effect analysis. The investigation of these causes and effects are carried out during different operating conditions in typical mining industry and potential problems are assessed. There are several recommendations are provided to reduce the effect of human error so as to increase production by careful consideration of maintenance activities. .

  • 27.
    Papic, Ljubisa
    et al.
    University of Kragujevac.
    Kovacevic, Srdja
    University of Kragujevac.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Safety Analysis of Mining Machines Specific Maintenance Operations2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 485-496Conference paper (Refereed)
    Abstract [en]

    By the rule, the object of the safety analysis is the technical system, for example, production or transportation, as the mining machines or their technological equipment are. The maintenance operations, up to present days, haven’t been investigated as the subject of safety analysis. However, as the practice of the technical systems maintenance shows so far many maintenance operations contain causes of danger. It means that it is useful to analyze such operations from the safety standpoint. From the standpoint of the mining machines safety, it should be stressed that in some researches, the expression “specific” is used for the critical maintenance operations. Therefore, the safety analysis of maintenance operations should precede the stage of maintenance operations. The possible approaches to the safety analysis in the area of maintenance on the basis of the method Failure Modes, Effects and Criticality Analysis are presented in the paper

  • 28.
    Parida, Aditya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Guest Editorial2017In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 258-259Article in journal (Other academic)
  • 29.
    Patwardhan, Amit
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Distributed Ledger for Cybersecurity: Issues and Challenges in Railways2021In: Sustainability, E-ISSN 2071-1050, Vol. 13, no 18, article id 10176Article in journal (Refereed)
    Abstract [en]

    The railway is a complex technical system of systems in a multi-stakeholder environment. The implementation of digital technologies is essential for achieving operational excellence and addressing stakeholders’ needs and requirements in relation to the railways. Digitalization is highly dependent on an appropriate digital infrastructure provided through proper information logistics, whereas cybersecurity is critical for the overall security and safety of the railway systems. However, it is important to understand the various issues and challenges presented by governance, business, and technical requirements. Hence, this paper is the first link in the chain to explore, understand, and address such requirements. The purpose of this paper is to identify aspects of distributed ledgers and to provide a taxonomy of issues and challenges to develop a secure and resilient data sharing framework for railway stakeholders.

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  • 30.
    Patwardhan, Amit
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Point Cloud Data Augmentation for Linear Assets2024In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 615-625Conference paper (Other academic)
  • 31.
    Patwardhan, Amit
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Castano, Miguel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    An Architecture for Predictive Maintenance using 3D Imaging: A Case Study on Railway Overhead Catenary2022In: Proceedings of the 32nd EuropeanSafety and Reliability Conference (ESREL 2022) / [ed] Maria Chiara Leva; Edoardo Patelli; Luca Podofillini; Simon Wilson, Research Publishing Services, 2022, p. 3103-3110Conference paper (Refereed)
    Abstract [en]

    Railway Overhead Catenary (ROC) system is critical for railways’ overall performance! ROC is a linear asset that is spread over a large geographical area. Insufficient performance of ROC has a significant impact on the overall railway operations, which leads to decreased availability and affects performance of the railway system. Prognostic and Health Management (PHM) of ROC is necessary to improve the dependability of the railway. PHM of ROC can be enhanced by implementing a data-driven approach. A data-driven approach to PHM is highly dependent on the availability and accessibility of data, data acquisition, processing and decision-support. Acquiring data for PHM of ROC can be used through various methods, such as manual inspections. Manual inspection of ROC is a time-consuming and costly method to assess the health of the ROC. Another approach for assessing the health of ROC is through condition monitoring using 3D scanning of ROC utilising LiDAR technology.Presently, 3D scanning systems like LiDAR scanners present new avenues for data acquisition of such physical assets. Large amounts of data can be collected from aerial, on-ground, and subterranean environments. Handling and processing this large amount of data require addressing multiple challenges like data collection, processing algorithms, information extraction, information representation, and decision support tools. Current approaches concentrate more on data processing but lack the maturity to support the end-to-end process. Hence, this paper investigates the requirements and proposes an architecture for a data-to-decision approach to PHM of ROC based on utilisation of LiDAR technology.

  • 32.
    Patwardhan, Amit
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Castano, Miguel
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Federated Learning for Enablement of Digital Twin2022In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 55, no 2, p. 114-119Article in journal (Refereed)
    Abstract [en]

    Creation, maintenance, and update of digital twins are costly and time-consuming mechanisms. The required effort can be optimized with the use of LiDAR technologies, which support the process of collecting data related to spatial information such as location, geometry, and position. Sharing such data in multi-stakeholder environments is hindered due to competition, confidentiality, and security requirements. Multi-stakeholder environments favor the use of decentralized creation and update mechanisms with reduced data exchange. Such mechanisms are facilitated by Federated Learning, where the learning process is performed at the data owner’s location. Two case studies are presented in this paper, where LiDAR is used to extract information from industrial equipment as a part of the creation of a digital twin.

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  • 33.
    Rajesh, M.G.
    et al.
    Electronics Division, BARC, Mumbai.
    Vinod, Gopika
    Reactor Safety Division, BARC, Mumba.
    Das, D.
    Electronics Division, BARC, Mumbai.
    Bhatnagar, P.V.
    Electronics Division, BARC, Mumbai.
    Pithawa, C.K.
    Electronics Division, BARC, Mumbai.
    Thaduri, Adithya
    Department of Electrical Engineering, IIT Bombay.
    Verma, Ajit Kumar
    Department of Electrical Engineering, IIT Bombay.
    A study of failure mechanisms in CMOS & BJT ICs and their effect on device reliability2010In: Proceedings of 2nd International Conference on Reliability, Safety and Hazard - ICRESH 2010: Mumbai Dec 15-16, 2010, Piscataway, NJ: IEEE Communications Society, 2010, p. 425-430Conference paper (Refereed)
    Abstract [en]

    The reliability of electronic systems, used in nuclear power plants, is traditionally estimated with empirical databases such as MIL-HDBK-217, PRISM etc. These methods assign a constant failure rate to electronic devices, during their useful life. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. The constant failure rate assumption stems from treating failures as random events. Electronics division of BARC is engaged in design & fabrication of CMOS and BJT ICs for nuclear pulse processing and signal conditioning. New microelectronic devices often exhibit infant mortality and wear-out phenomena while in operation. It points to competing degradation mechanisms-electro migration, hot carrier injection, dielectric breakdown etc. - that make a device's useful life different from that predicted by empirical methods. Understanding the dominant mechanisms that lead to device failure - Physics of Failure - is a more realistic approach to reliability prediction. This paper describes common failure mechanisms- encountered in CMOS and BJT ICs and the efforts being taken to quantify these effects in an optical-isolator IC - 4N36 - which forms a part of the trip generation circuit in neutron flux monitoring systems.

  • 34.
    Soltanali, Hamzeh
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Ferdowsi University of Mashhad, Mashhad, Iran.
    Garmabaki, Amir Soleimani
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Rohani, Abbas
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing2019In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, no 4, p. 682-697Article in journal (Refereed)
    Abstract [en]

    Automotive manufacturing industries are required to improve their productivity with higher production rates at the lowest cost, less number of unexpected shutdowns, and reliable operation. In order to achieve the above objectives, the application of reliability, availability, and maintainability methodologies can constitute for resilient operation, identifying the bottlenecks of manufacturing process and optimization of maintenance actions. In this article, we propose a framework for reliability, availability, and maintainability evaluation and maintenance optimization to improve the performance of conveying process of vehicle body in an automotive assembly line. The results of reliability, availability, and maintainability analysis showed that the reliability and maintainability of forklift and loading equipment are the main bottlenecks. To find the optimal maintenance intervals of each unit, a multi-attribute utility theory is applied for multi-criteria decision model considering reliability, availability, and costs. Due to the series configuration of conveying process in automotive assembly line, the optimized time intervals are obtained using opportunistic maintenance strategy. The results could be useful to improve operational performance and sustainability of the production process.

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  • 35.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Maintenance Engineering, Scania Industrial Maintenance, Södertälje, Sweden.
    Digital Twin: Definitions, Classification, and Maturity2024In: International Congress and Workshop on Industrial AI and eMaintenance 2023, Springer Science and Business Media Deutschland GmbH , 2024, p. 585-599Conference paper (Other academic)
  • 36.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Nowcast models for train delays based on the railway network status2020In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 11, no 2, p. 184-195Article in journal (Refereed)
    Abstract [en]

    Switches and crossings (S&C) or turnouts are one of the important systems in the Swedish railway traffic maintenance planning. For immediate diverting of the trains, they need to be predict the working condition for short time duration, also known as nowcasting and for long time duration, also known as forecasting. The prediction of the condition of turnout is useful for traffic planning without disrupting to the traffic. Hence, the main purpose of this paper is to predict the condition of S&Cs for shorter and longer duration. In order to achieve it, at first, statistical analysis is carried out to find the root causes of failures. Secondly, non-homogenous Poisson process is applied to nowcast and forecast the working condition. The results of this study will guide the train dispatchers to plan the train timetable according the present traffic.

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  • 37.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Physics-of-failure based performance modeling of critical electronic components2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The traditional reliability prediction methods that draw on standard handbooks such as MIL-HDBK 217F, Telcordia, PRISM etc., are not appropriate to determine the reliability indices of these components. For one thing, technology is constantly advancing; for another, the empirical data do not always match the actual working environment.The newest reliability prediction methodology, the physics-of-failure (PoF), emphasizes the root cause of failure, failure analysis, and failure mechanisms based on the analysis of parameter characteristics. It involves a focused examination of failure point locations, considering the fabrication technology, process, materials and circuit layout obtained from the manufacturer. This methodology is capable of providing recommendations for the increased reliability of components using intuitive analysis.However, there is a limitation: it is sometimes difficult to obtain manufacturer’s details for failure analysis and quality information. Several statistical and probability modeling methods can be performed on the experimental data of these components to measure the time to failure. These experiments can be conducted using the accelerated-testing of dominant stress parameters such as Voltage, Current, Temperature, Radiation etc.In this thesis, the combination of qualitative data from PoF approach and quantitative data from the statistical analysis is used to create a modified physics-of-failure approach. This methodology overcomes the limitations of the standard PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is created to select the best option from failure data models, failure mechanisms, failure criteria and other factors to ensure a growth in reliability.In this study, the critical electronic components used in certain safety systems from different technologies are chosen for reliability prediction: Optocoupler, Constant Fraction Discriminator, BJT Transistor, Voltage Comparator, Voltage Follower and Instrumentation amplifier. The study finds that the modified physics-of-failure methodology provides more accurate reliability indices than the traditional approaches using field data. Stress based degradation models are developed for each of the components. The modified PoF models developed using Response Surface Regression and Support Vector Machine (SVM) show better performance.

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  • 38.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Al-Jumaili, Mustafa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kour, Ravdeep
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences2019In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, no 2, p. 149-159Article in journal (Refereed)
    Abstract [en]

    Recently, due to the advancements in the ICT (Information and Communication Technology), there has been lot of emphasis on digitization of the existing and newly developed infrastructure. In transportation infrastructure, in general, 80% of the assets are already in place and there has been tremendous push to move to the digital era. For efficient and effective design, construction, operation and maintenance of the infrastructure, due to this digitization, there is increasing research trend in data-driven decision-making algorithms that are proved to be effective because of several advantages. Since railway is the backbone of the society, the data-driven approaches will ensure the continuous operation, efficient maintenance, planning and potential future investments. The breach and leak of this potential data to the wrong hands might result in havoc, risk, trust, hazards and serious consequences. Hence, the main purpose of this paper is to stress the potential challenges, consequences, threats, vulnerabilities and risk management of data security in the railway infrastructure in context of eMaintenance. In addition, this paper also identifies the research methods to obtain and secure this data for potential possible research.

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  • 39.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Evolution of Maintenance Processes in Industry 4.02020In: 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.

  • 40.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Processing mining for maintenance decision support2017In: Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden / [ed] Diego Galar, Dammika Seneviratne, Luleå: Luleå tekniska universitet, 2017, p. 179-Conference paper (Refereed)
    Abstract [en]

    Process mining is gaining importance for the classification, clustering, workflow models, process discovery, predictions and planning and scheduling in a process or events in especially business oriented fields. On the other hand, there are several events that are required to perform a maintenance action in various industries. There is a need to understand the process flow of events to reduce the delays to increase the performance of the maintenance action. This paper applies the concept of process mining to understand the events in a typical maintenance action (repair or replacement,). We implemented the process mining for administrative, logistic and repair delays for one section in Swedish Railway. We identified the bottlenecks in this process fordifferent subsystems for productive feedback to the railway industry.

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  • 41.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences, Haugesund .
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Process Mining for Maintenance Decision Support2019In: System Performance and Management Analytics / [ed] P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh, Springer, 2019, p. 279-293Chapter in book (Refereed)
    Abstract [en]

    In carrying out maintenance actions, there are several processes running simultaneously among different assets, stakeholders, and resources. Due to the complexity of maintenance process in general, there will be several bottlenecks for carrying out actions that lead to reduction in maintenance efficiency, increase in unnecessary costs and a hindrance to operations. One of the tools that is emerging to solve the above issues is the use Process Mining tools and models. Process mining is attaining significance for solving specific problems related to process such as classification, clustering, discovery of process, prediction of bottlenecks, developing of process workflow, etc. The main objective of this paper is to utilize the concept of process mining to map and comprehend a set of maintenance reports mainly repair or replacement from some lines on the Swedish railway network. To attain the above objective, the reports were processed to extract out time related maintenance parameters such as  administrative, logistic and repair times. Bottlenecks are identified in the maintenance process and this information will be useful for maintenance service providers, infrastructure managers, asset owners and other stakeholders for improvement and maintenance effectiveness.

  • 42.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Railway Assets: A Potential Domain for Big Data Analytics2015In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 53, p. 457-467, article id 53Article in journal (Refereed)
    Abstract [en]

    Two concepts currently at the leading edge of todays information technology revolution are Analytics and Big Data. The public transportation industry has been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data. The more that public transportation professionals and decision makers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. This paper gives an overview of Big Data technologies in context of transportation with specific to Railways. This paper also gives an insight on how the existing data modules from the transport authority combines Big Data and how can be incorporated in providing maintenance decision making.

  • 43.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Space weather climate impacts on railway infrastructure2020In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 11, no 2, p. 267-281Article in journal (Refereed)
    Abstract [en]

    Space weather is a phenomenon in which radioactivity and atomic particles is caused by emission from the Sun and stars. It is one of the extreme climate events that could potentially has short-term and long-term impacts on infrastructure. The effects of this phenomenon are a multi-fold process that include electronic system, equipment and component failures, short-term and long-term hazards and consequences to astronauts and aircraft crews, electrostatic charge variation of satellites, disruptions in telecommunications systems, navigational systems, power transmission failures and disturbances to the rail traffic and power grids. The critical infrastructures are becoming interdependent to each other and these infrastructures are vulnerable if one of them is affected due to space weather. Railway infrastructure could be affected by the extreme space weather events and long-term evolution due to direct and indirect effects on system components, such as track circuits, electronic components in-built in signalling systems or indirectly via interdependencies on power, communications, etc. While several space weather-related studies focus on power grids, Global Navigation Satellite System (GNSS) and aviation sectors, a little attention has focused towards probability of railway infrastructure disruptions. Nevertheless, disruptions due to space weather on signalling and train control systems has documented but other systems that railway infrastructure dependent upon are not very well studied. Due to the advancements in digitalization, cloud storage, Internet of Things (IoT), etc., that are embedded with electronic equipment are also possible to prone to these effects and it is even become more susceptible to the extreme space weather events. This paper gives a review of space weather effects on railways and other transportation systems and provide some of the mitigation measures to the infrastructure and societal point of view.

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  • 44.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Department of Electrical Engineering, Indian Institute of Technology, Bombay, International Institute of Information Technology, P-14, Pune Infotech Park, Phase-1, Hinjawadi, Stord/Haugesund University College, Haugesund.
    Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 67-81Conference paper (Refereed)
    Abstract [en]

    Maintenance of moving vehicles is quite challenging because they may disrupt the normal flow of transportation due to unexpected breakdowns, slowdowns and stoppages. In order to avoid stoppages and to minimize the downtime, maintenance and condition monitoring systems must be optimized. On one hand the condition monitoring on board should provide automatic failure detection, identification and localization together with a prognostic of the future failures. On the other hand maintenance logistics and product supportability must be also optimized since the onboard system should provide a suggestion of a repair shop that depends on location, cost and availability of spare parts, technicians’ skills and queuing time for repairs. However the vehicles are independent assets interacting among them within the traffic system and also interacting with the infrastructure (roads, rails etc.) seriously affected by weather, maintenance of infra, regulations etc. Therefore the proposed solution is to equip the vehicles with a context-aware system that monitors the condition and maintenance schedules of parts and alarm the driver of the parts that are in near to repair cycle. This system will perform risk analysis and will communicate with the cloud propose a decision of selection of repair shop on the location and path of vehicle depending on weather, road and traffic, cost and availability of spare parts at respective repair shops based on risk assessment and prediction. The information contained in the cloud will also communicate the workshop that will book time slot and block the necessary spare parts for the coming vehicle minimizing waiting time. This mechanism will help in reducing unexpected stoppages, vehicle degradation and efficient spare parts management combining in a successful way the workload of the workshops from both natural sources, the time based inspections and repairs together with the reactive maintenance coming from unexpected breakdown

  • 45.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Garmabaki, Amir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Impact of climate change on railway operation and maintenance in Sweden: A State-of-the-art review2021In: Maintenance, Reliability and Condition Monitoring (MRCM), E-ISSN 2669-2961, Vol. 1, no 2, p. 52-70Article in journal (Refereed)
    Abstract [en]

    Increased intensity and frequency of extreme weather conditions caused by climate change can have a negative impact on rail service performance and also increases total ownership costs. Research has shown that adverse weather conditions are responsible for 5 to 10 % of total failures and 60 % of delays on the railway infrastructure in Sweden. The impact of short-term and long-term effects of climate change and extreme weather events depends on the design characteristics of the railway assets, geographical location, operational profile, maturity of the climate adaptation, etc. These extreme events will have major consequences such as traffic disruption, accidents, and higher maintenance costs during the operation and maintenance (O&M) phase. Therefore, a detailed assessment of the effects of climate change on the O&M phase requires a more comprehensive review of the previous studies reported from different parts of the world. The paper provides a state-of-the-art review of the effects of extreme weather events and their impacts on the operation and maintenance of railway infrastructure. This paper also provides a list of vulnerable railway assets that can have an impact due to extreme weather events.

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  • 46.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Integrated RAMS, LCC and Risk Assessment for Maintenance Planning for Railways2020In: Advances in RAMS Engineering: In Honor of Professor Ajit Kumar Verma on His 60th Birthday / [ed] Durga Rao Karanki, Gopika Vinod, Srividya Ajit, Springer, 2020, p. 261-292Chapter in book (Other academic)
    Abstract [en]

    As of today, about 70% of the transportation infrastructure has already built for the needs of customers, business and society, where Railways is the major infrastructure. Due to huge investment for renewal and overhaul, there is emergent need to maintain the infrastructure with high availability with minimum cost and risk, being, transportation is the backbone of the economy. These infrastructures normally lead to degradation due to operational loads, environmental factors and frequent interventions. Hence, planning and optimization of the maintenance actions with the constrained resources is implemented properly for the efficient operation. Due to the hierarchical nature of Railways, there is necessary for railway infrastructure managers to design a generic framework for the decision-making process when planning maintenance and interventions, which is an important functional block of asset management in railway infrastructures. This chapter proposes an integrated methodology to perform maintenance decision making using definitive “building blocks” namely Reliability, Availability, Maintainability and Safety (RAMS), Life Cycle Costing (LCC) and Risk assessment. It has to incorporates the “building blocks” at different planning levels in asset hierarchy; namely network, route, line and component and planning hierarchy; namely Strategic Asset Management Plan (SAMP), Route Asset Plan (RAP), Route Delivery Plan (RDP) and Implementation of Asset Maintenance Plan (IAMP) as proposed in IN2SMART which was renamed from ISO 55000 Asset Management Framework.

  • 47.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Haugesund University College, Haugesund, Norway.
    Computational intelligence framework for context-aware decision making2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no Supp. 4, p. 2146-2157Article in journal (Refereed)
    Abstract [en]

    Learning of context-aware systems is necessary in building up knowledge on the characteristics of the environment to provide efficient decision making within multi-objective requirements. As the industrial systems becomes complex day-by-day, intelligent machine learning techniques need to be implemented at respective context-aware situations to facilitate recommendations using soft computing methods based on dynamic user specifications. In this paper, a framework is designed for a meta-database that is generated by contextual information of several peers with what-if conditions and rule-based approaches and thus by provide decision making utilizing several existing soft computing algorithms.

  • 48.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Indian Institute of Technology, Bombay.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Gopinath, Rajesh
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Study of reliability aspects in constant fraction discriminator2011In: 5th International Conference on Quality, Reliability and Information Technology (ICQRIT), Kathmandu, 2011, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Reliability prediction using conventional constant failure models by standard books in early phases of electronics dominates wide acceptance. But after 1980s, there was wide variation in electronic technology which made above models obsolete. Physics of Failure approach provides information on basic failure phenomenon with failure mechanisms and failure modes becomes prominent as it entirely depends on materials, processes, technology etc. Constant fraction discriminators which are failing frequently in the field need to be studied and this paper provides information on failure characteristics using physics of failure approach. Apart from that, we combined statistical methods such as Design of Experiments, Accelerated testing and failure distribution models to quantify time to failure of this electronic component by radiation and temperature as stress parameters.

  • 49.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Patwardhan, Amit
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kour, Ravdeep
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Predictive maintenance of mobile mining machinery: A case study for dumpers2023In: 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 Services , 2023, p. 3481-3488, article id P298Conference paper (Refereed)
  • 50.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pecht, Michael
    University of Maryland, USA.
    Electronics Parts Change Control and Supply Chain Responsibilities2015Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    The rapid growth of the information and automation industries has spurred dramatic changes in the parts that make up electronic products and systems. In particular, changes are continuously being made to increase performance, reduce feature size and power, and of course reduce costs while meeting environmental and other legal regulations. 

    All changes introduce uncertainty and this uncertainty can affect the operation of the supply chain, as well as the final results. The more frequent changes are made, the more complex the operations of the supply chain become and the more attention is required to assess the changes. 

    This presentation will discuss some of the key issues with changes and how advanced supply chain methods are being used to address the changes. Issues concerning obsolescence, the use of application specific parts, counterfeit parts, qualification, reliability and operational availability will also be presented.

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