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  • 1.
    Al-Douri, Yamur K.
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Information security in e-maintenance: a study of Scada security2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    eMaintenance solutions are spreading increasingly due to the continuous evolution in the different Information and Communication Technology (ICT) tools. In general, most of the available eMaintenance solutions are depending on Internet infrastructure what makes them vulnerable to all security threats that affect the Internet. One of the important eMaintenance solutions is Supervisory Control and Data Acquisition (SCADA) system as it has been used in most of the industrial processes. SCADA systems were designed without security considerations as they were mainly installed into isolated networks. Nowadays, SCADA systems are mainly connected to Internet and other networks. Therefore, SCADA systems have been exposed to wide range of network security threats. Hence, SCADA security has become an important aspect that needs to be investigated. In this paper, a study of SCADA security issues will be done. The main contribution of this paper is to address SCADA security issues and challenges related to eMaintenance.

  • 2.
    Aljumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data Quality Assessment: Applied in Maintenance2016Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
  • 3.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data quality assessment using multi-attribute: maintenance perspective2018Ingår i: International Journal of Information and Decision Sciences, ISSN 1756-7017, E-ISSN 1756-7025, Vol. 10, nr 2, s. 147-161Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The paper proposes a model for data quality (DQ) assessment in maintenance. Data has become an increasingly important since most of the maintenance planning and implementations are based on data analysis. Poor DQ reduces customer satisfaction, leading to poor decision making, and has negative impacts on strategy execution. To improve DQ as well as to evaluate the current status, DQ needs to be measured. A measure for DQ could be an important support for decision makers. Multi-criteria decision-making (MCDM) methods can provide a framework for DQ assessment, however, they are not used in literature for DQ assessment. In order to assess DQ, the attributes or KPIs need to be defined, their hierarchy should be designed and the assessment model is proposed to evaluate these attributes. A case study is also presented in this paper. The study shows that MCDM methods could provide qualitative estimation for the quality of DQ attributes.

  • 4.
    Aljumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Metadata-Based Data Quality Assessment2016Ingår i: Vine: The Journal of Information and Knowledge Management Systems, ISSN 0305-5728, E-ISSN 1474-1032, Vol. 46, nr 2, s. 232-250Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    High quality data and data quality assessment can support the decision-makingprocess. In the literature, discussions of the assessment process are mainly focused on theoretical approaches to content analysis or on user evaluations. Metadata is important source for quality information in any database system, however, it is not considered for data quality assessment. Metadata contains information that describes the data in a database, including the constraints and the database schema. High quality data can be produced by designing a database system with accurate metadata descriptions. Having accurate and detailed metadata will reduce the errors in data values which can lead to data quality issues. In this study, data quality assessment model is proposed based on both content and metadata analysis. The model is validated by developing an application tool to assess the quality of the data in a database based on the proposed model. The results show that metadata can provide important information about the quality of the database and its adoption can help togive faster, more accurate and user independent assessment of data quality.

  • 5.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Multi-Criteria Data Quality Assessment Maintenance perspective2014Ingår i: Proceedings of the 3rd international workshop and congress on eMaintenance: June 17-18 Luleå, Sweden : eMaintenance, Trends in technologies & methodologies, challenges, possibilites and applications / [ed] Uday Kumar; Ramin Karim; Aditya Parida; Philip Tretten, Luleå: Luleå tekniska universitet, 2014, s. 153-158Konferensbidrag (Refereegranskat)
    Abstract [en]

    Data quality (DQ) in maintenance has become an increasinglyimportant aspect to many firms as most of the maintenanceplanning and implementations are based on data analysis. PoorDQ has adverse effects at the operational, tactical, and strategiclevels of any organization. Respectively, poor DQ reducescustomer satisfaction, leading to poor decision making, and hasnegative impacts on strategy execution. To improve DQ as well asto evaluate the current status, DQ need to be measured followingthe fact that only what can be measured can be improved. Ameasure for DQ could be an important support for decisionmakers. In order to assess DQ, related attributes should bedefined. These attributes could be related to the data itself, to themetadata, or to the data representation schemes. After definingthese attributes, an assessment model should be used to evaluatethese attributes. The purpose of this paper is to propose a modelfor DQ assessment. Therefore, a study of DQ attributes and thepossible metrics that could be used to measure these attributes wasundertaken. The proposed model will be applied on datasetprovided by the Swedish Transport Administration (Trafikverket)for validation and to find an estimation measure of the DQ.

  • 6.
    Aljumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Quality of Streaming Data in Condition Monitoring Using ISO 80002016Ingår i: 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, s. 703-715Konferensbidrag (Refereegranskat)
    Abstract [en]

    The purpose of this paper is to propose a Data Quality Measurement Model based on ISO 8000 standard. This paper deals about the concepts implied in the measurement process, not about the measures themselves. Poor quality information causes customer dissatisfaction, lost revenue and higher costs associated with additional time to reconcile information. An understanding of the characteristics of the data that determine its quality, and an ability to measure, manage and report on data quality is required. Measurement is a major activity in data quality management. In literature, there are many proposals contributing somehow to the measurement of data quality. However, these measurement methods lack the unification. ISO 8000 provides a framework for improving data quality that can be used independently or in conjunction with quality management systems. ISO 8000 defines characteristics that can be tested by any organization in the data supply chain to objectively determine conformance of the data to ISO 8000.

  • 7.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Wandt, Karina
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    eMaintenance Ontologies for Data Quality Support2015Ingår i: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 21, nr 3, s. 358-374Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose – The purpose of this paper is to explore the main ontologies related to eMaintenance solutions and to study their application area. The advantages of using these ontologies to improve and control data quality will be investigated.Design/methodology/approach – A literature study has been done to explore the eMaintenance ontologies in the different areas. These ontologies are mainly related to content structure and communication interface. Then, ontologies will be linked to each step of the data production process in maintenance.Findings – The findings suggest that eMaintenance ontologies can help to produce a high quality data in maintenance. The suggested maintenance data production process may help to control data quality. Using these ontologies in every step of the process may help to provide management tools to provide high quality data.Research limitations/implications – Based on this study, it can be concluded that further research could broaden the investigation to identify more eMaintenance ontologies. Moreover, studying these ontologies in more technical details may help to increase the understandability and the use of these standards. Practical implications – It has been concluded in this study that applying eMaintenance ontologies by companies needs additional cost and time. Also the lack or the ineffective use of eMaintenance tools in many enterprises is one of the limitations for using these ontologies.Originality/value – Investigating eMaintenance ontologies and connecting them to maintenance data production is important to control and manage the data quality in maintenance.Paper type Research Paper

  • 8.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Mahmood, Yasser Ahmed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Assessment of railway frequency converter performance and data quality using the IEEE 762 Standard2014Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, nr 1, s. 42694-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reliability, availability and maintainability analysis is one of the most important tools for measuring system performance. The performance of a traction power supply system (TPSS) can be measured using the data collected from frequency converters, as these converters constitute the main part of the TPSS. The quality of the collected data should be good enough to provide the correct and complete information necessary for assessment of frequency converter performance. Many methods can be used to assess the performance of converters such as neural networks, fuzzy logic and standards. The IEEE 762 Standard offers a methodology that can provide key performance indicators for power generation units. This standard has been chosen for its widespread acceptance and applicability. To be able to evaluate a converter’s performance, IEEE 762 indexes should be calculated using data such as the downtime, reserve shutdown hours and service hours. Therefore, the purpose of this study is to assess the performance of the Swedish TPSS frequency converters using IEEE 762, and to assess the quality of data by inspecting their compatibility with this standard. In this study, an application has been developed to generate the missing information and to calculate the indexes provided by the standard, in order to evaluate the power converters’ performance. A case with sample data is also discussed in this paper.

  • 9.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Rauhala, Ville
    Kemi-Tornio University of Applied Science.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Jonsson, Katrin
    Department of Informatics, Umeå University.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Aspects of data quality in eMaintenance: a case study of process industry in northern Europe2014Ingår i: Engineering Asset Management 2011: Proceedings of the Sixth World Congress on Engineering Asset Management / [ed] Jay Lee; Jun Ni; Jagnathan Sarangapani; Joseph Mathew, London: Encyclopedia of Global Archaeology/Springer Verlag, 2014, s. 41-51Konferensbidrag (Refereegranskat)
    Abstract [en]

    Increased environmental awareness in the industry combined with the globalized market economy makes increasing demands for sustainable and efficient resource utilization. In this context, maintenance plays a critical role by linking business objectives to the strategic and operational activities aimed at retaining the system’s availability performance, cost-efficiency and sustainability. Performing maintenance effectively and efficiently requires corresponding infrastructure for decision-support provided through eMaintenance solutions. A proper eMaintenance solution needs to provide services for data acquisition, data processing, data aggregation, data analysis, data visualization, context-sensing etc. To en Quality of Service (QoS) in eMaintenance solutions, the performance of both system-of-interest, enabling systems and related processes have to be measured and managed. However, the QoS has to be considered on all aggregation levels and encompass the aspects of Content Quality (CQ), Data Quality (DQ) and Information Quality (IQ). Hence, the purpose of this paper is to study and describe some aspects of DQ in eMaintenance related to process industry in northern Europe

  • 10.
    Aljumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Rauhala, Ville
    Kemi-Tornio University of Applied Science Technology.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data quality in eMaintenance: a call for research2011Ingår i: MPMM 2011: Maintenance Performance Measurement & Management: Conference Proceedings / [ed] Diego Galar; Aditya Parida; Håkan Schunnesson; Uday Kumar, Luleå: Luleå tekniska universitet, 2011, s. 69-73Konferensbidrag (Refereegranskat)
    Abstract [en]

    Effective and efficient maintenance requires a proper information logistics, which can be delivered through eMaintenance solutions. Development of eMaintenance solutions faces extensive challenges. One of these challenges is how to ensure the quality of data used in different eMaintenance solutions. Data Quality (DQ) concerns all phases of the maintenance process. The purpose of this paper is to answer the research question: how should DQ be considered and managed when developing eMaintenance solutions. To deal with such challenges a case study was conducted at a mining company. Empirical data has been collected through interviews, observations, archival records and workshops. The data analysis has been based on an empirical framework that supports the identification of required information services. Conditions that support the DQ and the information logistics, along with that, support the maintenance process have been presented. These aspects have also been related to the phases of a generic maintenance process.

  • 11.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Study of aspects of data quality in e-maintenance2012Ingår i: International Journal of COMADEM, ISSN 1363-7681, Vol. 15, nr 4, s. 3-14Artikel i tidskrift (Refereegranskat)
  • 12.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Wandt, Karina
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    eMaintenance ontologies and data production2012Ingår i: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, s. 191-196Konferensbidrag (Refereegranskat)
  • 13.
    Al-Jumaili, Mustafa
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Wandt, Karina
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser.
    eMaintenance Related Ontologies2012Rapport (Övrigt vetenskapligt)
  • 14.
    Hamodi, Hussan
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Aljumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data Quality of Maintenance Data: A Case Study in MAXIMO CMMS2017Ingår i: 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, s. 105-110Konferensbidrag (Refereegranskat)
    Abstract [en]

    Computerised maintenance management systems (CMMS) are software packages; their data include information on an organisation’s maintenance, operations and costs. MAXIMO is recognised as a leading CMMS for asset management. It helps to manage maintenance data, improving data quality, making maintenance more efficient, and supporting decision making. However, MAXIMO systems have problems of data quality, with a resulting impact on efficiency and the validity of decisions based on those data. This paper investigates the quality of maintenance data in MAXIMO using the Swedish Transport Agency (Trafikverket) as a case study. It discusses the results before and after data cleaning to show the impact of data quality problems on data analysis.

  • 15.
    Kour, Ravdeep
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    eMaintenance in railways: Issues and challenges in cybersecurity2019Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 233, nr 10, s. 1012-1022Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The convergence of information technology and operation technology and the associated paradigm shift toward Industry 4.0 in complex systems, such as railways has brought significant benefits in reliability, maintainability, operational efficiency, capacity, as well as improvements in passenger experience. However, with the adoption of information and communications technologies in railway maintenance, vulnerability to cyber threats has increased. It is essential that organizations move toward security analytics and automation to improve and prevent security breaches and to quickly identify and respond to security events. This paper provides a statistical review of cybersecurity incidents in the transportation sector with a focus on railways. It uses a web-based search for data collection in popular databases. The overall objective is to identify cybersecurity challenges in the railway sector.

  • 16.
    Mahmood, Yasser Ahmed
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Assessment of reliability data for traction frequency converters using IEEE Std 762: a study at Swedish railway2012Ingår i: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, s. 171-174Konferensbidrag (Refereegranskat)
  • 17.
    Stenström, Christer
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Computerised Analysis of Text Entry Fields in Maintenance Work Orders Data2014Ingår i: Proceedings of the 3rd international workshop and congress on eMaintenance: June 17-18 Luleå, Sweden : eMaintenance, Trends in technologies & methodologies, challenges, possibilites and applications / [ed] Uday Kumar; Ramin Karim; Aditya Parida; Phillip Tretten, Luleå: Luleå tekniska universitet, 2014, s. 97-100Konferensbidrag (Refereegranskat)
    Abstract [en]

    Enterprise resource planning systems and computerised maintenance management systems are commonly used by organisations for handling of maintenance work orders through a graphical user interface. A work order consists of a number of data fields, such as drop-down lists, list boxes, check boxes and text entry fields. In contrast to the other data fields, the operator has the freedom to type in any text in the text entry fields, to complement and make the work order description complete. Accordingly, the text entry fields of work orders can contain any words, in any number, as necessary.Data quality is crucial in statistical analysis of work orders data, and therefore manual analysis of work orders’ text entry fields is often necessary before any decision making. However, this may be a very tedious and resource consuming process.In this article, we apply computerised analysis of text entry fields of work orders data, to study if it can bring further value in the assessment of technical assets’ performance.Keywords:Data quality, eMaintenance, maintenance, work orders, failure, decision support, natural language processing

  • 18.
    Stenström, Christer
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Natural language processing of maintenance records data2015Ingår i: International Journal of COMADEM, ISSN 1363-7681, Vol. 18, nr 2, s. 33-37Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Enterprise resource planning systems and maintenance management systems are commonly used by organisations for handling of maintenance records, through a graphical user interface. A maintenance record consists of a number of data fields, such as drop-down lists, list boxes, check boxes and text entry fields. In contrast to the other data fields, the operator has the freedom to type in any text in the text entry fields, to complement and make the maintenance record as complete as possible. Accordingly, the text entry fields of maintenance records can contain any words, in any number.Data quality is crucial in statistical analysis of maintenance records, and therefore manual analysis of maintenance records’ text entry fields is often necessary before any decision making. However, this may be a very tedious and resource consuming process.In this article, natural language processing is applied to text entry fields of maintenance records in a case study, to show how it can bring further value in the assessment of technical assets’ performance.Keywords: Maintenance records, Natural language processing, Structured and unstructured data, Data quality, Rail infrastructure.

  • 19.
    Thaduri, Adithya
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kour, Ravdeep
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences2019Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, nr 2, s. 149-159Artikel i tidskrift (Refereegranskat)
    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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