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Thaduri, A., Al-Jumaili, M., Kour, R. & Karim, R. (2019). Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences. International Journal of Systems Assurance Engineering and Management, 10(2), 149-159
Open this publication in new window or tab >>Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences
2019 (English)In: 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) Published
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.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
eMaintenance, Cybersecurity, Risks, consequences, Railways
National Category
Reliability and Maintenance Computer Systems Other Civil Engineering
Research subject
Centre - Luleå Railway Research Center (JVTC); Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-73186 (URN)10.1007/s13198-019-00778-w (DOI)000464861200001 ()
Note

Validerad;2019;Nivå 2;2019-04-23 (marisr)

Available from: 2019-03-13 Created: 2019-03-13 Last updated: 2019-05-02Bibliographically approved
Thaduri, A., Famurewa, S. M., Verma, A. K. & Kumar, U. (2019). Process Mining for Maintenance Decision Support. In: P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh (Ed.), System Performance and Management Analytics: (pp. 279-293). Springer
Open this publication in new window or tab >>Process Mining for Maintenance Decision Support
2019 (English)In: 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.

Place, publisher, year, edition, pages
Springer, 2019
Series
Asset Analytics, ISSN 2522-5162
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-70280 (URN)10.1007/978-981-10-7323-6_23 (DOI)978-981-10-7322-9 (ISBN)978-981-10-7323-6 (ISBN)
Available from: 2018-08-09 Created: 2018-08-09 Last updated: 2018-08-09Bibliographically approved
Thaduri, A., Verma, A. K. & Kumar, U. (2018). Analytics for Maintenance of Transportation in Smart Cities. In: Kapur P., Kumar U., Verma A. (Ed.), Quality, IT and Business Operations: Modeling and Optimization (pp. 81-91). Singapore: Springer
Open this publication in new window or tab >>Analytics for Maintenance of Transportation in Smart Cities
2018 (English)In: Quality, IT and Business Operations: Modeling and Optimization / [ed] Kapur P., Kumar U., Verma A., Singapore: Springer, 2018, p. 81-91Chapter in book (Refereed)
Abstract [en]

Cities typically face a wide range of management and maintenance problems. They are complex environments in which digital technologies are more and more pervasive; this digitization of urban environment provided a scope for enriched environment that has capability for data-driven methods. The connections and exchange of data increase and the need for data acquisition, processing, and management become an extremely important added value to the community. The inclusion of digitization and incorporation of predictive analytics provide a base for a sustainable smart city. This work considers an overview of different challenges that utilizes different technologies within a smart city maintenance with respect to transportation. A conceptual framework is proposed to handle the generated data for decision for control, monitoring, fault diagnosis, and maintenance of more and more complex systems.

Place, publisher, year, edition, pages
Singapore: Springer, 2018
Series
Springer Proceedings in Business and Economics, ISSN 2198-7246
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-65959 (URN)10.1007/978-981-10-5577-5_7 (DOI)978-981-10-5576-8 (ISBN)978-981-10-5577-5 (ISBN)
Available from: 2017-10-04 Created: 2017-10-04 Last updated: 2017-11-24Bibliographically approved
Soltanali, H., Garmabaki, A. S., Thaduri, A., Parida, A., Kumar, U. & Rohani, A. (2018). Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing. Journal of Risk and Reliability
Open this publication in new window or tab >>Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing
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2018 (English)In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078Article in journal (Refereed) Epub ahead of print
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.

Place, publisher, year, edition, pages
Sage Publications, 2018
Keywords
Automotive manufacturing, conveying process, opportunistic maintenance, reliability, availability, and maintainability methodologies, multi-attribute utility theory
National Category
Reliability and Maintenance Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-72427 (URN)10.1177/1748006X18818266 (DOI)
Available from: 2019-01-02 Created: 2019-01-02 Last updated: 2019-01-30
Thaduri, A., Kumar, U. & Verma, A. K. (2017). Computational intelligence framework for context-aware decision making (ed.). International Journal of Systems Assurance Engineering and Management, 8(Supp. 4), 2146-2157
Open this publication in new window or tab >>Computational intelligence framework for context-aware decision making
2017 (English)In: 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) Published
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.

Place, publisher, year, edition, pages
Springer, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-12534 (URN)10.1007/s13198-014-0320-8 (DOI)bb19a94c-2a20-4100-9168-55e7b1d8dead (Local ID)bb19a94c-2a20-4100-9168-55e7b1d8dead (Archive number)bb19a94c-2a20-4100-9168-55e7b1d8dead (OAI)
Note

Validerad;2017;Nivå 2;2017-11-27 (rokbeg)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-27Bibliographically approved
Parida, A., Karim, R. & Thaduri, A. (2017). Guest Editorial. Journal of Quality in Maintenance Engineering, 23(3), 258-259
Open this publication in new window or tab >>Guest Editorial
2017 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 258-259Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-65111 (URN)10.1108/JQME-05-2017-0039 (DOI)2-s2.0-85027990510 (Scopus ID)
Available from: 2017-08-15 Created: 2017-08-15 Last updated: 2017-11-24Bibliographically approved
Mishra, M., Odelius, J., Thaduri, A., Nissen, A. & Rantatalo, M. (2017). Particle filter-based prognostic approach for railway track geometry. Mechanical systems and signal processing, 96, 226-238
Open this publication in new window or tab >>Particle filter-based prognostic approach for railway track geometry
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2017 (English)In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 96, p. 226-238Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63143 (URN)10.1016/j.ymssp.2017.04.010 (DOI)000401886800015 ()2-s2.0-85019145932 (Scopus ID)
Note

Validerad; 2017; Nivå 2; 2017-04-25 (andbra)

Available from: 2017-04-25 Created: 2017-04-25 Last updated: 2018-09-13Bibliographically approved
Thaduri, A. & Famurewa, S. M. (2017). Processing mining for maintenance decision support. In: Diego Galar, Dammika Seneviratne (Ed.), Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden. Paper presented at Maintenance Performance and Measurement and Management 2016(MPMM 2016). November 28, Luleå, Sweden (pp. 179-). Luleå: Luleå tekniska universitet
Open this publication in new window or tab >>Processing mining for maintenance decision support
2017 (English)In: 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, Oral presentation with published abstract (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.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63905 (URN)978-91-7583-841-0 (ISBN)
Conference
Maintenance Performance and Measurement and Management 2016(MPMM 2016). November 28, Luleå, Sweden
Available from: 2017-06-12 Created: 2017-06-12 Last updated: 2018-06-25Bibliographically approved
Thaduri, A., Galar, D., Kumar, U. & Verma, A. K. (2016). Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle (ed.). In: (Ed.), Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde (Ed.), Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective. Paper presented at International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015 (pp. 67-81). : Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle
2016 (English)In: 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, Published 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

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-27114 (URN)10.1007/978-3-319-23597-4_6 (DOI)073fe446-2596-4d21-8ba1-6479eddcb45c (Local ID)978-3-319-23596-7 (ISBN)978-3-319-23597-4 (ISBN)073fe446-2596-4d21-8ba1-6479eddcb45c (Archive number)073fe446-2596-4d21-8ba1-6479eddcb45c (OAI)
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Note
Godkänd; 2016; Bibliografisk uppgift: Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management. Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field. ; 20151222 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Papic, L., Kovacevic, S., Galar, D. & Thaduri, A. (2016). Investigation of Causes of Mining Machines Maintenance Problems (ed.). In: (Ed.), Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde (Ed.), Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective. Paper presented at International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015 (pp. 283-299). : Encyclopedia of Global Archaeology/Springer Verlag
Open this publication in new window or tab >>Investigation of Causes of Mining Machines Maintenance Problems
2016 (English)In: 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, Published 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. .

Place, publisher, year, edition, pages
Encyclopedia of Global Archaeology/Springer Verlag, 2016
Series
Lecture Notes in Mechanical Engineering, ISSN 2195-4356
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-28233 (URN)10.1007/978-3-319-23597-4_21 (DOI)1f4a20ea-54b5-4763-a143-7c02dbe2ecba (Local ID)978-3-319-23596-7 (ISBN)978-3-319-23597-4 (ISBN)1f4a20ea-54b5-4763-a143-7c02dbe2ecba (Archive number)1f4a20ea-54b5-4763-a143-7c02dbe2ecba (OAI)
Conference
International Conference ICRESH-ARMS 2015 : 01/06/2015 - 04/06/2015
Note
Godkänd; 2016; Bibliografisk uppgift: Containing selected papers from the ICRESH-ARMS 2015 conference in Lulea, Sweden, collected by editors with years of experiences in Reliability and maintenance modeling, risk assessment, and asset management, this work maximizes reader insights into the current trends in Reliability, Availability, Maintainability and Safety (RAMS) and Risk Management. Featuring a comprehensive analysis of the significance of the role of RAMS and Risk Management in the decision making process during the various phases of design, operation, maintenance, asset management and productivity in Industrial domains, these proceedings discuss key issues and challenges in the operation, maintenance and risk management of complex engineering systems and will serve as a valuable resource for those in the field. ; 20151223 (andbra)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2017-11-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1938-0985

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