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Kumar, Uday
Publications (10 of 349) Show all publications
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
Jena, J. K., Verma, A. K., Kumar, U. & Ajit, S. (2019). Tunnel QRA: Present and Future Perspectives. In: P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh (Ed.), System Performance and Management Analytics: (pp. 387-403). Springer
Open this publication in new window or tab >>Tunnel QRA: Present and Future Perspectives
2019 (English)In: System Performance and Management Analytics / [ed] P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh, Springer, 2019, p. 387-403Chapter in book (Refereed)
Abstract [en]

With the vision of faster in-land transportation of humans and goods, long tunnels with increasing engineering complexities are being designed, constructed and operated. Such complexities arise due to terrain (network of small tunnels) and requirement of multiple entries and exits (network of traffics leading to non-homogenous behaviour). Increased complexities of such tunnels throw unique challenges for performing QRA for such tunnels, which gets compounded due to handful number of experiments performed in real tunnels, as they are costly and dangerous. A combined approach of CFD modelling of scaled down tunnels could be a relatively less resource intensive solution, nevertheless, associated with its increased uncertainties due to introduction of scaling multiplication factors. Further, with the advent of smart system designs and cheap computational cost, a smart tunnel which manages its own traffic of both dangerous goods carriers and other passenger vehicles based on continuously updated dynamic risk estimate, is not far from reality.

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-70277 (URN)10.1007/978-981-10-7323-6_31 (DOI)978-981-10-7322-9 (ISBN)978-981-10-7323-6 (ISBN)
Available from: 2018-08-08 Created: 2018-08-08 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
Kansal, Y., Kapur, P., Kumar, U. & Kumar, D. (2018). Effort and coverage dependent vulnerability discovery modeling. In: : . Paper presented at 2nd International Conference on Telecommunication and Networks, TEL-NET 2017, Amity University, Noida, India, 10-17 August 2017. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Effort and coverage dependent vulnerability discovery modeling
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, our primary focus is to propose a generalized mathematical model that can discover potential vulnerabilities on the basis of two key factors: operational effort rate and operational coverage rate. Here, the term operational effort rate refers to the proportion of manpower required to discover vulnerabilities. The operational coverage rate refers to the proportion of software covered by the effort in discovering vulnerabilities. It is assumed that the proposed model follows the Non-Homogeneous Poisson process properties thus different distribution are used to formulate multiple cases. To evaluate the operational effort function, exponential and Weibull distribution are used considering coverage rate either to be a constant or logistic. For model validation, a case study of real commercial software data set has been used

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-70272 (URN)10.1109/TEL-NET.2017.8343550 (DOI)2-s2.0-85049065956 (Scopus ID)9781509067107 (ISBN)
Conference
2nd International Conference on Telecommunication and Networks, TEL-NET 2017, Amity University, Noida, India, 10-17 August 2017
Available from: 2018-08-08 Created: 2018-08-08 Last updated: 2018-08-08Bibliographically approved
Kansal, Y., Kumar, U., Kumar, D. & Kapur, P. K. (2018). Fixing of Faults and Vulnerabilities via Single Patch. In: Kapur P., Kumar U., Verma A. (Ed.), Quality, IT and Business Operations: Modeling and Optimization (pp. 175-190). Singapore: Springer
Open this publication in new window or tab >>Fixing of Faults and Vulnerabilities via Single Patch
2018 (English)In: Quality, IT and Business Operations: Modeling and Optimization / [ed] Kapur P., Kumar U., Verma A., Singapore: Springer, 2018, p. 175-190Chapter in book (Refereed)
Abstract [en]

Users’ demand of reliable software in zero time has made the software development more complex. If software industry fails in fulfilling the demands, then it may undergo big penalties and revenue loss. The developers are pressurized subject to resource constraints provided by the management. Despite such fact, software experiences various validation (testing) processes before its release; faults and vulnerabilities are still left undetected that later lack the quality of the product. The only feasible solution for resisting from the lack after the release of software is patch development. Generally, the patches developed for fixing faults and vulnerabilities are a separate process which requires extra resources that increases the total development cost and time. In this paper, we have proposed a cost framework that solves the problem of optimizing the patch release time with two different approaches. Here, the first approach has considered the release of a single patch that fixes both faults and vulnerabilities jointly. As the severity of vulnerabilities is much higher than the faults, the second approach considered the release of two patches where the first patch has fixed both faults and vulnerabilities jointly and other patch specifically fixed only vulnerabilities. The detailed illustration of the method is presented in the proposed paper. The case study is presented at the end for the validation purpose.

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-65953 (URN)10.1007/978-981-10-5577-5_15 (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
Kumar, U. & Galar, D. (2018). Maintenance in the Era of Industry 4.0: Issues and Challenges. In: Kapur P., Kumar U., Verma A. (Ed.), Quality, IT and Business Operations: Modeling and Optimization (pp. 231-250). Singapore: Springer
Open this publication in new window or tab >>Maintenance in the Era of Industry 4.0: Issues and Challenges
2018 (English)In: Quality, IT and Business Operations: Modeling and Optimization / [ed] Kapur P., Kumar U., Verma A., Singapore: Springer, 2018, p. 231-250Chapter in book (Refereed)
Abstract [en]

The fourth generation of industrial activity enabled by smart systems and Internet-based solutions is known as Industry 4.0. Two most important characteristic features of Industry 4.0 are computerization using cyber-physical systems and the concept of “Internet of Things” adopted to produce intelligent factories. As more and more devices are instrumented, interconnected and automated to meet this vision, the strategic thinking of modern-day industry has been focused on deployment of maintenance technologies to ensure failure-free operation and delivery of services as planned.

Maintenance is one of the application areas, referred to as Maintenance 4.0, in the form of self-learning and smart system that predicts failure, makes diagnosis and triggers maintenance. The paper addresses the new trends in manufacturing technology based on the capability of instrumentation, interconnection and intelligence together with the associated maintenance challenges in the era of collaborative machine community and big data environment.

The paper briefly introduces the concept of Industry 4.0 and presents maintenance solutions aligned to the need of the next generation of manufacturing technologies and processes being deployed to realize the vision of Industry 4.0.The suggested maintenance approach to deal with new challenges due to the implementation of industry 4.0 is captured within the framework of eMaintenance solutions developed using maintenance analytics. The paper is exploratory in nature and is based on literature review and study of the current development in maintenance practices aligned to industry 4.0.

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-65958 (URN)10.1007/978-981-10-5577-5_19 (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
Soleimanmeigouni, I., Xiao, X., Ahmadi, A., Xie, M., Nissen, A. & Kumar, U. (2018). Modelling the evolution of ballasted railway track geometry by a two-level piecewise model. Structure and Infrastructure Engineering, 14(1), 33-45
Open this publication in new window or tab >>Modelling the evolution of ballasted railway track geometry by a two-level piecewise model
Show others...
2018 (English)In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 14, no 1, p. 33-45Article in journal (Refereed) Published
Abstract [en]

Accurate prediction and efficient simulation of the evolution of track geometry condition is a prerequisite for planning effective railway track maintenance. In this regard, the degradation and tamping effect should be equipped with proper and efficient probabilistic models. The possible correlation induced by the spatial structure also needs to be taken into account when modelling the track geometry degradation. To address these issues, a two-level piecewise linear model is proposed to model the degradation path. At the first level, the degradation characteristic of each track section is modelled by a piecewise linear model with known break points at the tamping times. At the second level, Autoregressive Moving Average models are used to capture the spatial dependences between the parameters of the regression lines indexed by their locations. To illustrate the model, a comprehensive case study is presented using data from the Main Western Line in Sweden

Place, publisher, year, edition, pages
Taylor & Francis, 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63815 (URN)10.1080/15732479.2017.1326946 (DOI)000415674800003 ()2-s2.0-85019663898 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-11-01 (andbra)

Available from: 2017-06-09 Created: 2017-06-09 Last updated: 2018-06-28Bibliographically approved
Soleimanmeigouni, I., Ahmadi, A. & Kumar, U. (2018). Track geometry degradation and maintenance modelling: A review (ed.). Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, 232(1), 73-102
Open this publication in new window or tab >>Track geometry degradation and maintenance modelling: A review
2018 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 232, no 1, p. 73-102Article in journal (Refereed) Published
Abstract [en]

Increased demand for railway transportation is creating a need for higher train speeds and axle loads. These, in turn,increase the likelihood of track degradation and failures. Modelling the degradation behaviour of track geometry anddevelopment of applicable and effective maintenance strategies has become a challenging concern for railway infrastructuremanagers. During the last three decades, a number of track geometry degradation and maintenance modellingapproaches have been developed to predict and improve the railway track geometry condition. In this paper, existingtrack geometry measures are identified and discussed. Available models for track geometry degradation are reviewedand classified. Tamping recovery models are also reviewed and discussed to identify the issues and challenges of differentavailable methodologies and models. Existing track geometry maintenance models are reviewed and critical observationson each contribution are provided. The most important track maintenance scheduling models are identified and discussed.Finally, the paper provides directions for further research.

Place, publisher, year, edition, pages
Sage Publications, 2018
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-14797 (URN)10.1177/0954409716657849 (DOI)000419833100006 ()2-s2.0-85040348348 (Scopus ID)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (Local ID)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (Archive number)e3794ef4-cb25-49e0-b55c-a579ff2ea6f5 (OAI)
Note

Validerad;2018;Nivå 2;2018-01-18 (svasva)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-06-28Bibliographically approved
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
Ghodrati, B., Hoseinie, H. & Kumar, U. (2017). Context-driven mean residual life estimation of mining machinery. International Journal of Surface Mining, Reclamation and Environment
Open this publication in new window or tab >>Context-driven mean residual life estimation of mining machinery
2017 (English)In: International Journal of Surface Mining, Reclamation and Environment, ISSN 1389-5265Article in journal (Refereed) Epub ahead of print
Abstract [en]

Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-63100 (URN)10.1080/17480930.2017.1308067 (DOI)
Available from: 2017-04-21 Created: 2017-04-21 Last updated: 2017-11-29
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