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Kumar, Uday
Publications (10 of 360) Show all publications
Liu, B., Lin, J., Zhang, L. & Kumar, U. (2019). A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation. IEEE Access, 7, 94941-94943, Article ID 8762155.
Open this publication in new window or tab >>A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation
2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 94941-94943, article id 8762155Article in journal (Refereed) Published
Abstract [en]

This paper develops a dynamic maintenance strategy for a system subject to aging and degradation. The influence of degradation level and aging on system failure rate is modeled in an additive way. Based on the observed degradation level at the inspection, repair or replacement is carried out upon the system. Previous researches assume that repair will always lead to an improvement in the health condition of the system. However, in our study, repair reduces the system age but on the other hand, increases the degradation level. Considering the two-fold influence of maintenance actions, we perform reliability analysis on system reliability as a first step. The evolution of system reliability serves as a foundation for establishing the maintenance model. The optimal maintenance strategy is achieved by minimizing the long-run cost rate in terms of the repair cycle. At each inspection, the parameters of the degradation processes are updated with maximum a posteriori estimation when a new observation arrives. The effectiveness of the proposed model is illustrated through a case study of locomotive wheel-sets. The maintenance model considers the influence of degradation and aging on system failure and dynamically determines the optimal inspection time, which is more flexible than traditional stationary maintenance strategies and can provide better performance in the field.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Aging and degradation process, dynamic maintenance strategy, locomotive wheel-sets, prescriptive maintenance, sequential schedule
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-75614 (URN)10.1109/ACCESS.2019.2928587 (DOI)000478676600061 ()2-s2.0-85070235312 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-08-20 (svasva)

Available from: 2019-08-20 Created: 2019-08-20 Last updated: 2019-08-28Bibliographically approved
Illankoon, P., Tretten, P. & Kumar, U. (2019). A prospective study of maintenance deviations using HFACS-ME. International Journal of Industrial Ergonomics, 74, Article ID 102852.
Open this publication in new window or tab >>A prospective study of maintenance deviations using HFACS-ME
2019 (English)In: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 74, article id 102852Article in journal (Refereed) Published
Abstract [en]

The factors initiating aviation accidents are usually hidden behind various steps, systems, and tasks, and systematic root-cause analysis is required to uncover the initial factor(s). To reduce the risk of unfavourable events, it is more appropriate to study their causal factors. We argue that an in-depth study on maintenance process deviations could assist in uncovering hidden causal factors. We therefore analyse reported maintenance deviations from an aviation organisation using the Human Factor Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy to aggregate and map hidden causal factors. We find attention and memory errors and inadequacy of processes and documentation are major causal factors. We argue a well-run organisation can capture hidden causal factors and reduce the risk of incidents and accidents. More specifically, we show how situation awareness (SA) interventions can assist in the mitigation of maintenance deviations and capture hidden causal factors.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Aviation maintenance, Incidents, Active error, Latent condition, Situation awareness
National Category
Production Engineering, Human Work Science and Ergonomics Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-76338 (URN)10.1016/j.ergon.2019.102852 (DOI)
Funder
Luleå Railway Research Centre (JVTC), 167522
Note

Validerad;2019;Nivå 2;2019-10-15 (johcin)

Available from: 2019-10-10 Created: 2019-10-10 Last updated: 2019-10-15Bibliographically approved
Garmabaki, A. S., Thaduri, A., Hedström, A., Kumar, U., Laue, J., Marklund, S., . . . Indahl, S. (2019). A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections. In: Michael beer, Enrico Zio (Ed.), ESREL-2019: . Paper presented at ESREL 2019 | European Safety and Reliability Conference.
Open this publication in new window or tab >>A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections
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2019 (English)In: ESREL-2019 / [ed] Michael beer, Enrico Zio, 2019Conference paper, Published 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.

Keywords
Underground Pipelines, Transportation Infrastructure, Railway, Maintenance, FMEA
National Category
Reliability and Maintenance Water Engineering Geotechnical Engineering
Research subject
Structural Engineering; Traffic Engineering
Identifiers
urn:nbn:se:ltu:diva-76471 (URN)10.3850/978-981-11-2724-3_0037-cd (DOI)978-981-11-2724-3 (ISBN)
Conference
ESREL 2019 | European Safety and Reliability Conference
Projects
PipeXrail
Funder
Vinnova, 2016-033113
Note

We gratefully acknowledge the funding provided by Sweden’s Innovation Agency, Vinnova, through the Strategic Innovation Programme InfraSweden2030. The funding was granted in competition within the Open Call “Condition assessment and maintenance of transport infrastructure – Grant No. 2016-033113”. In addition, the technical support and collaboration of, Arrsleff Rörteknik, Luleå Railway Research Center (JVTC) and the Swedish Transport Administration (Trafikverket) are greatly appreciated

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-11-22
Kansal, Y., Kapur, P. & Kumar, U. (2019). Coverage-based vulnerability discovery modeling to optimize disclosure time using multiattribute approach. Quality and Reliability Engineering International, 35(1), 62-73
Open this publication in new window or tab >>Coverage-based vulnerability discovery modeling to optimize disclosure time using multiattribute approach
2019 (English)In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 35, no 1, p. 62-73Article in journal (Refereed) Published
Abstract [en]

Software vulnerabilities trend over time has been proposed by various researchers and academicians in recent years. But none of them have considered operational coverage function in vulnerability discovery modeling. In this research paper, we have proposed a generalized statistical model that determines the relationship between operational coverage function and the number of expected vulnerabilities. During the operational phase, possible vulnerable sites are covered and vulnerabilities present at a particular site are discovered with some probability. We have assumed that the proposed model follows the nonhomogeneous Poisson process properties; thus, different distributions are used to formulate the model. The numerical illustration shows that the proposed model performs better and has the good fitness to the Google Chrome data. The second focus of this research paper is to evaluate the total cost incurred by the developer after software release and to identify the optimal vulnerability disclosure time through multiobjective utility function. The proposed vulnerability discovery helps in optimization. The optimal time problem depends on the combined effect of cost, risk, and effort.

Place, publisher, year, edition, pages
John Wiley & Sons, 2019
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-71123 (URN)10.1002/qre.2380 (DOI)000458675300005 ()2-s2.0-85053695158 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-01-25 (johcin)

Available from: 2018-10-05 Created: 2018-10-05 Last updated: 2019-03-08Bibliographically approved
Zhang, C., Gao, Y., Yang, L., Kumar, U. & Gao, Z. (2019). Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors. Omega: The International Journal of Management Science, 87, 86-104
Open this publication in new window or tab >>Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors
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2019 (English)In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 87, p. 86-104Article in journal (Refereed) Published
Abstract [en]

Regular maintenances on high-speed railway facilities are performed in every night in China, and during regular maintenances, high-speed railway is not available for the sunset-departure and sunrise-arrival trains (SDSA-trains). In order to reduce the influence of regular maintenances on SDSA-trains, three operation modes are used in practice, which mainly consist of route selections between high-speed railway and normal-speed railway. In this paper, we use some linearization techniques to formulate a mixed integer linear programming (MILP) model to identify the operation modes and the timetable of SDSA-trains, by integrating the time window selection of regular maintenances on high-speed railways. The objective of the model is to minimize the total travel time of SDSA-trains. In the formulation of the model, we introduce state variables to indicate whether a train is running on high-speed railway or not, which makes it conveniently express the selection of operation modes. Based on the real data of Beijing-Guangzhou high-speed and normal-speed railway corridors in China, numerical experiments are carried out to test the proposed model and optimization method.

Place, publisher, year, edition, pages
Elsevier, 2019
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-70744 (URN)10.1016/j.omega.2018.08.005 (DOI)000474319000008 ()2-s2.0-85052095984 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-07-10 (johcin)

Available from: 2018-09-04 Created: 2018-09-04 Last updated: 2019-08-16Bibliographically approved
Illankoon, P., Tretten, P. & Kumar, U. (2019). Modelling human cognition of abnormal machine behaviour. Human-Intelligent Systems Integration, 1(1), 3-26
Open this publication in new window or tab >>Modelling human cognition of abnormal machine behaviour
2019 (English)In: Human-Intelligent Systems Integration, ISSN 2524-4876, Vol. 1, no 1, p. 3-26Article in journal (Refereed) Published
Abstract [en]

Despite the advances in intelligent systems, there is no guarantee that those systems will always behave normally. Machine abnormalities, unusual responses to controls or false alarms, are still common; therefore, a better understanding of how humans learn and respond to abnormal machine behaviour is essential. Human cognition has been researched in many domains. Numerous theories such as utility theory, three-level situation awareness and theory of dual cognition suggest how human cognition behaves. These theories present the varieties of human cognition including deliberate and naturalistic thinking. However, studies have not taken into consideration varieties of human cognition employed when responding to abnormal machine behaviour. This study reviews theories of cognition, along with empirical work on the significance of human cognition, including several case studies. The different propositions of human cognition concerning abnormal machine behaviour are compared to dual cognition theories. Our results show that situation awareness is a suitable framework to model human cognition of abnormal machine behaviour. We also propose a continuum which represents varieties of cognition, lying between explicit and implicit cognition. Finally, we suggest a theoretical approach to learn how the human cognition functions when responding to abnormal machine behaviour during a specific event. In conclusion, we posit that the model has implications for emerging waves of human-intelligent system collaboration.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Cognition, Machine abnormities, Situation awareness, Explicit, Implicit, Cognitive continuum
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-73796 (URN)10.1007/s42454-019-00002-x (DOI)
Funder
Luleå Railway Research Centre (JVTC)
Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-10-28Bibliographically approved
Kansal, Y., Kapur, P. K., Kumar, U. & Kumar, D. (2019). Prioritizing Vulnerabilities using ANP and Evaluating their Optimal Discovery and Patch Release Time. International Journal of Mathematics in Operational Research (IJMOR), 14(2), 236-267
Open this publication in new window or tab >>Prioritizing Vulnerabilities using ANP and Evaluating their Optimal Discovery and Patch Release Time
2019 (English)In: International Journal of Mathematics in Operational Research (IJMOR), ISSN 1757-5850, E-ISSN 1757-5869, Vol. 14, no 2, p. 236-267Article in journal (Refereed) Published
Abstract [en]

Method for filtering and identifying a vulnerability class that has high probability of occurrence is needed by organisations to patch their software in a timely manner. In this paper, our first step is to filter the most frequently observed vulnerability type/class through a multi-criteria decision making that involves dependency among various criteria and feedback from various alternatives, known as analytic network process. We will also formulate a cost model to provide a solution to the developers facing high revenue debt because of the occurrence of highly exploited vulnerabilities belonging to the filtered group. The main aim of formulating the cost model is to evaluate the optimal discovery and patch release time such that the total developer's cost could be minimised subject to risk constraints. To illustrate the proposed approach, reported vulnerabilities of Google Chrome with high exploitability have been examined at its source level.

Place, publisher, year, edition, pages
InderScience Publishers, 2019
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-66589 (URN)10.1504/IJMOR.2019.097758 (DOI)2-s2.0-85061331859 (Scopus ID)
Note

Validerad;2019;Nivå 1;2019-03-01 (johcin) 

Available from: 2017-11-15 Created: 2017-11-15 Last updated: 2019-03-01Bibliographically 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
Block, J., Ahmadi, A., Xun, X. & Kumar, U. (2019). Spares Provisioning Strategy for Periodically Replaced Units within the Fleet Retirement Period. International Journal of Systems Assurance Engineering and Management, 10(3), 299-315
Open this publication in new window or tab >>Spares Provisioning Strategy for Periodically Replaced Units within the Fleet Retirement Period
2019 (English)In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, no 3, p. 299-315Article in journal (Refereed) Published
Abstract [en]

Within aviation enterprises, the process of dismantling an aircraft at the end of its life is referred to as parting-out. Obviously, the asset value of the units and materials parted out from the retired airframes can be considerable. The benchmarked best practice within the aviation industry is to dismantle the retired aircraft and use the parted-out spares to support the remaining fleet or to offer them on the surplus market. Part-out-based spares provisioning (PBSP) has been a major focus of attention for aviation companies. The PBSP approach is a complex task that requires a multidisciplinary and integrated decision-making process. In order to control the stock level and fulfil the decision criteria within PBSP, it is necessary to make decisions on the termination, at specific times, of both the parting-out process and the maintenance and repair actions performed on the units.

This paper considers repairable units and introduces a computational model to identify the applicable alternatives for repair termination times that will minimize the number of remaining spares at the end of the retirement period, while fulfilling the availability requirement for spares during the PBSP period, at the lowest possible cost.  The feasible alternatives are compared with regard to their respective costs, and the most cost-effective solution is selected. The cost model uses estimates of future maintenance requirements, the turn-around times, the cost of the various maintenance tasks, the future spares consumption, and the estimated salvage of spares from retired aircraft. The output of the model is a set of applicable alternatives which satisfy the availability requirements for spares for the active fleet. The method is illustrated using a case study performed on the Saab-105 training aircraft. 

The results show that the proposed PBSP approach and computational model provide added value from a sustainability point of view, since the use of existing resources is maximized during the retirement process, through the process of reclaiming units and the applicable maintenance termination alternatives. The implementation of the proposed computational model in a PBSP programme provides a detailed and situation-based overview of the stock level dynamics, and contributes to the spares provisioning process by providing solutions to issues such as obsolescence, last-time buys and cannibalization.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Provisioning, Spare parts, End-of-Life, Maintenance, Retirement, Parting-out, Repairable units, Stock level, Dismantling.
National Category
Civil Engineering Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-66222 (URN)10.1007/s13198-019-00791-z (DOI)000474561200001 ()2-s2.0-85066897265 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-07-12 (johcin)

Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2019-08-16Bibliographically approved
Soltanali, H., Garmabaki, A. S., Thaduri, A., Parida, A., Kumar, U. & Rohani, A. (2019). Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing. Journal of Risk and Reliability, 233(4), 682-697
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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2019 (English)In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, no 4, p. 682-697Article in journal (Refereed) Published
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, 2019
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)000478598600015 ()2-s2.0-85059945405 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-08-28 (johcin)

Available from: 2019-01-02 Created: 2019-01-02 Last updated: 2019-08-28Bibliographically approved
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