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  • 1.
    Garmabaki, Amir Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Marklund, Stefan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hedström, Annelie
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Underground pipelines and railway infrastructure: failure consequences and restrictions2020In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 16, no 3, p. 412-430Article in journal (Refereed)
    Abstract [en]

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

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

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

  • 2.
    Liu, B.
    et al.
    Department of Management Science, University of Strathclyde, Glasgow, United Kingdom.
    Lin, Jing
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Zhang, Liangwei
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 94941-94943, article id 8762155Article in journal (Refereed)
    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.

  • 3.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A prospective study of maintenance deviations using HFACS-ME2019In: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 74, article id 102852Article in journal (Refereed)
    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.

  • 4.
    Garmabaki, Amir Soleimani
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hedström, Annelie
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Laue, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Marklund, Stefan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Architecture and Water.
    Odelius, Johan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bansal, Tarun
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Asplund, Matthias
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Indahl, Stefan
    A Survey on Underground Pipelines and Railway Infrastructure at Cross-Sections2019In: ESREL-2019 / [ed] Michael beer, Enrico Zio, 2019Conference 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.

  • 5.
    Kansal, Y.
    et al.
    Amity Institute of Information Technology, Amity University, Noida, India.
    Kapur, P.K.
    Amity Centre for Interdisciplinary Research, Amity University, Noida, India.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Coverage-based vulnerability discovery modeling to optimize disclosure time using multiattribute approach2019In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 35, no 1, p. 62-73Article in journal (Refereed)
    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.

  • 6.
    Alsyouf, Imad
    et al.
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Al-Ash, Lubna
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Al-Hammadi, Muna
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Improving baggage flow in the baggage handling system at a UAE-based airline using lean Six Sigma tools2019In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 30, no 3, p. 432-452Article in journal (Refereed)
    Abstract [en]

    This paper presents a real successful implementation of lean six sigma methodology to continuously improve the baggage flow in a baggage handling system (BHS), by identifying the causes of mishandled baggage, and deriving solutions to enhance BHS performance. The results show that the main critical problems were low system reliability and the high number of bags passing through manual-encoding-stations. This research illustrates how to avoid baggage congestion and provides applicable and cost-effective solutions. The success of this project made the organisation aware of the opportunities that the application of lean Six Sigma methodology created in the aviation and airport sector.

  • 7.
    Zhang, Chuntian
    et al.
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Gao, Yuan
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Yang, Lixing
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Gao, Ziyou
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors2019In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 87, p. 86-104Article in journal (Refereed)
    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.

  • 8.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modelling human cognition of abnormal machine behaviour2019In: Human-Intelligent Systems Integration, ISSN 2524-4876, Vol. 1, no 1, p. 3-26Article in journal (Refereed)
    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.

  • 9.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University.
    Kapur, Parmad Kumar
    Amity Center for Interdisciplinary Research, Amity University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Deepak
    Amity Institute of Information Technology, Amity University.
    Prioritizing Vulnerabilities using ANP and Evaluating their Optimal Discovery and Patch Release Time2019In: 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)
    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.

  • 10.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences, Haugesund .
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Process Mining for Maintenance Decision Support2019In: System Performance and Management Analytics / [ed] P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh, Springer, 2019, p. 279-293Chapter in book (Refereed)
    Abstract [en]

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

  • 11.
    Block, Jan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Saab Support and Services, Logistics Analysis and Fleet Monitoring, Lifecycle Logistics Division, Linköping, Sweden.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Xun, Xiao
    School of Fundamental Sciences, Massey University, Palmerston North, New Zealand.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Spares Provisioning Strategy for Periodically Replaced Units within the Fleet Retirement Period2019In: 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)
    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.

  • 12.
    Soltanali, Hamzeh
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Ferdowsi University of Mashhad, Mashhad, Iran.
    Garmabaki, Amir Soleimani
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Rohani, Abbas
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing2019In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, no 4, p. 682-697Article in journal (Refereed)
    Abstract [en]

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

  • 13.
    Jena, Jajati K.
    et al.
    Cyient Limited Hyderabad.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences, Haugesund .
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ajit, Srividya
    Tunnel QRA: Present and Future Perspectives2019In: 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.

  • 14.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences, Haugesund .
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Analytics for Maintenance of Transportation in Smart Cities2018In: 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.

  • 15.
    Ghodrati, Behzad
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hoseinie, Hadi
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Context-driven mean residual life estimation of mining machinery2018In: International Journal of Surface Mining, Reclamation and Environment, ISSN 1389-5265, p. 486-494Article in journal (Refereed)
    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.

  • 16.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University, Noida.
    Kapur, P.K.
    Amity Centre of Interdisciplinary Research, Amity University, Noida.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Deepak
    Amity Institute of Information Technology, Amity University.
    Effort and coverage dependent vulnerability discovery modeling2018Conference 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

  • 17.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Deepak
    Amity Institute of Information Technology, Amity University.
    Kapur, Parmad Kumar
    Amity Centre for Interdisciplinary Research, Amity University, Noida.
    Fixing of Faults and Vulnerabilities via Single Patch2018In: 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.

  • 18.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Identifying significance of human cognition in future maintenance operations2018In: Advances in Intelligent Systems and Computing, ISSN 2194-5357, E-ISSN 2194-5365, Vol. 722, p. 550-556Article in journal (Refereed)
    Abstract [en]

    Industrial maintenance in future will operate heavily with intelligent systems. Advanced sensor networks on machines will enable them communicate and learn about failure types, predict consequences and share solutions. Humans on the other hand are equipped with intuitive cognition that facilitates acquisition of knowledge about unique characteristics of individual machines, and use this knowledge in maintenance problem solving. In this article, we identify two major opportunities to collaborate human intuitive cognition with intelligent systems for future maintenance solutions.

  • 19.
    Kumar, Uday
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance in the Era of Industry 4.0: Issues and Challenges2018In: 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.

  • 20.
    Soleimanmeigouni, Iman
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Xiao, Xun
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Xie, Min
    Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon.
    Nissen, Arne
    Trafikverket, Luleå.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modelling the evolution of ballasted railway track geometry by a two-level piecewise model2018In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 14, no 1, p. 33-45Article in journal (Refereed)
    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

  • 21.
    Kapur, P.K.
    et al.
    Amity Center for Interdisciplinary Research, Amity University.
    Kumar, UdayLuleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.Verma, Ajit KumarWestern Norway University of Applied Sciences, Haugesund .
    Quality, IT and Business Operations: Modeling and Optimization2018Collection (editor) (Refereed)
    Abstract [en]

    This book discusses action-oriented, concise and easy-to-communicate goals and challenges related to quality, reliability, infocomm technology and business operations. It brings together groundbreaking research in the area of software reliability, e-maintenance and big data analytics, highlighting the importance of maintaining the current growth in information technology (IT) adoption in businesses, while at the same time proposing process innovations to ensure sustainable development in the immediate future. In its thirty-seven chapters, it covers various areas of e-maintenance solutions, software architectures, patching problems in software reliability, preventive maintenance, industrial big data and reliability applications in electric power systems.

    The book reviews the ways in which countries currently attempt to resolve the conflicts and opportunities related to quality, reliability, IT and business operations, and proposes that internationally coordinated research plans are essential for effective and sustainable development, with research being most effective when it uses evidence-based decision-making frameworks resulting in clear management objectives, and is organized within adaptive management frameworks. Written by leading experts, the book is of interest to researchers, academicians, practitioners and policy makers alike who are working towards the common goal of making business operations more effective and sustainable.

  • 22.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Sustaining implicit learning in locomotive operation2018In: 20th Nordic Seminar on Railway Technology: Abstracts, Gothenburg, Sweden, 2018, p. 59-Conference paper (Refereed)
    Abstract [en]

    Modern trains are capable of monitoring health status in real time and infer behaviour of various systems. This trend will grow with advancements of machine learning those will produce feedback for continuously improving the prediction models. Despite reduced physical connectivity of human with locomotive systems, human interference will be required for critical decision-making. Human implicit learning involves the largely unconscious learning of dynamic statistical patterns and features, which leads to the development of tacit knowledge1. Pirsig2 argued that “each machine has its own, unique personality which probably could be defined as the intuitive sum total of everything you know and feel about it”. Theses suggest that humans employ an intuitive cognition ability that leads to developing implicit knowledge and interactions with machines. In this study, we focus on signifying the implicit knowledge in locomotive operation context and seek ways to facilitate effective decision-making

  • 23.
    Soleimanmeigouni, Iman
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Track geometry degradation and maintenance modelling: A review2018In: 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)
    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.

  • 24.
    Seneviratne, Dammika
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Boyang, Shi
    Tecnalia Research and Innovation, Industry and Transport Division, San-Sebastian.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Autonomous inspection and maintenance of linear assets2017In: 15th IMEKO TC10 Workshop on Technical Diagnostics 2017: "Technical Diagnostics in Cyber-Physical Era", 2017, p. 194-199Conference paper (Refereed)
    Abstract [en]

    Linear assets have linear properties, for instance, similar underlying geometry and characteristics over a distance. They show specific patterns of continuous inherent deteriorations and failures. Therefore, remedial inspection and maintenance actions will be similar along the length of a linear asset, but because it is distributed over a large area, the execution costs are greater. Autonomous robots can be programmed for repetitive and specific tasks. Unmanned aerial vehicles and remotely operated vehicles are currently used in different industrial settings in ad-hoc manner for inspection and maintenance purposes. This manuscript provides a conceptual framework for the use of autonomous inspection and maintenance practices for linear assets to reduce maintenance costs, human involvement, etc., whilst improving the availability of linear assets by effective utilization of autonomous robots and data from different sources

  • 25.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Haugesund University College, Haugesund, Norway.
    Computational intelligence framework for context-aware decision making2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no Supp. 4, p. 2146-2157Article in journal (Refereed)
    Abstract [en]

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

  • 26.
    Garmabaki, Amir
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Mahdieh
    Barabadi, Abbas
    Tromsø University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Data driven RUL estimation of rolling stock using intelligent functional test2017In: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, London: CRC Press, 2017, p. 1994-1999Conference paper (Refereed)
    Abstract [en]

    The rolling stock health condition is important for both passenger and freight trains in terms of safety, availability, punctuality and efficiency. Various inspection and maintenance methodologies are per-formed on rolling stock equipment to fulfill the above performance measures. This paper suggests a new approach, namely, intelligent functional test (IFTest) to estimate the remaining useful life (RUL) of the equipment, sub-systems and systems of rolling stock dynamically by data driven methods. IFTest generates a baseline of the current operational abilities in contrast to the required abilities. The test integrates the historical and new set of data to track the trend of degradation of equipment. With this approach, the operation and maintenance personnel have ample time to make decisions for the maintenance and failure consequences. In addition, it is supposed that by using such data we are achieving a more accurate result for the estimation of reliability and RUL of critical rolling stock equipment.

  • 27.
    Lin, Jing (Janet)
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    IN2CLOUD: A novel concept for collaborative management of big railway data2017In: Frontiers of Engineering Management, ISSN 2095-7513, Vol. 4, no 4, p. 428-436Article in journal (Refereed)
    Abstract [en]

    In the EU Horizon 2020 Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called “IN2CLOUD,” which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other (including domain knowledge and experience) but do not want to share their raw data or information. IN2CLOUD will help the movement of railway industry systems from “local” to “global” optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology (IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.

  • 28.
    Ghodrati, Behzad
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, UdayLuleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.Schunnesson, HåkanLuleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Proceeding of the 26th International Symposium on Mine Planning and Equipment Selection: MPES 20172017Conference proceedings (editor) (Refereed)
  • 29.
    Morant, Amparo
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Gustafson, Anna
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Söderholm, Peter
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Larsson-Kråik, Per-Olof
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Safety and availability evaluation of railway operation based on the state of signalling systems2017In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 231, no 2, p. 226-238Article in journal (Refereed)
    Abstract [en]

    A framework is presented to evaluate the safety and availability of the railway operation, and quantifying the probability of the signalling system not to supervise the railway traffic. Since a failure of the signalling systems still allows operation of the railway, it is not sufficient to study their effect on the railway operation by considering only the failures and delays. The safety and availability are evaluated, handling both repairs and replacements by using a Markov model. The model is verified with a case study of Swedish railway signalling systems with different scenarios. The results show that the probability of being in a state where operation is possible in a degraded mode is greater than the probability of not being operative at all, which reduces delays but requires other risk mitigation measures to ensure safe operation. The effects that different improvements can have on the safety and availability of the railway operation are simulated. The results show that combining maintenance improvements to reduce the failure rate and increase the repair rate is more efficient at increasing the probability of being in an operative state and reducing the probability of operating in a degraded state.

  • 30.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University.
    Kapur, P.K.
    Amity Centre for Interdisciplinary Research, Amity University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Deepak
    Amity Institute of Information Technology, Amity University.
    User-dependent vulnerability discovery model and its interdisciplinary nature2017In: Life Cycle Reliability and Safety Engineering, ISSN 2520-1352, Vol. 6, no 1, p. 23-29Article in journal (Refereed)
    Abstract [en]

    Software Vulnerability is a broad discipline that cannot be controlled only by the technologies. The holistic framework is required that statistically encompasses the entire security issues of IT organizations regardless of individual projects. Earlier researchers have developed several mathematical models that determined the vulnerabilities trend over time. Besides that, the most common victims of the vulnerabilities i.e., the software buyers or users were addressed theoretically without considering their impact on vulnerability discovery modeling. In this research paper, we examined the vulnerability discovery rate on the basis of potential users of commercial software. Here we propose an interdisciplinary model that highlights the relationship between the vulnerability intensity and the number of users of the software. The numerical illustration based on several real data sets is provided to validate the proposed user-dependent vulnerability discovery model.

  • 31.
    Garmabaki, Amir
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Block, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pham, Hoang
    Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A Reliability Decision Framework for Multiple Repairable Units2016In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 150, p. 78-88Article in journal (Refereed)
    Abstract [en]

    In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplines. This paper presents a decision framework to identify an appropriate reliability model for massive multiple repairable units. It splits non-homogeneous failure data into homogeneous groups and classifies them based on their failure trends using statistical tests. The framework discusses different scenarios for analysing multiple repairable units, according to trend, intensity, and dependency of the units’ failure data. The proposed framework has been verified in a fleet of aircraft and in two simulated data sets. The results show a reliability model of multiple repairable units may contain a mixture of different stochastic models. Considering single reliability models for such populations may cause erroneous calculation of the time to failure of a particular unit, which can, in turn, lead to faulty conclusions and decisions. When dealing with massive and non-homogeneous multiple repairable units, the application of the proposed framework can facilitate the selection of an appropriate reliability model.

  • 32.
    Patwardhan, Amit
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Department of Electrical Engineering, Indian Institute of Technology, Bombay, International Institute of Information Technology, P-14, Pune Infotech Park, Phase-1, Hinjawadi, University College, Haugesund.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A Survey on Predictive Maintenance Through Big Data2016In: 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. 437-445Conference paper (Refereed)
    Abstract [en]

    Modern manufacturing systems use thousands of sensors retrieving information at hundreds to thousands of samples per second. The real time data being generated is mostly used for monitoring the processes and the equipment condition. Data processing techniques applied to this data to detect anomalies and thus applying preventive maintenance have been used in the industry. Currently available technologies which were developed during the last two decade for scanning the Internet and providing computational services, working at very large scale can be re-targeted to fulfil the requirements of maintenance of complex systems. These systems can support storage and processing of current as well as historical data. Ability to access and process these large data sets will lead from preventive to predictive maintenance and eventually to smart manufacturing..

  • 33.
    Jack, N.
    et al.
    Springfield, Cupar, Fife.
    Murthy, D.N.P
    School of Mechanical and Mining Engineering, The University of Queensland, St Lucia.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Application of Game Theory to Railway Decision Making2016In: 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. 395-408Conference paper (Refereed)
    Abstract [en]

    Over the last few decades various forms of railway privatization have taken place in many different countries. As a result, it is now common for several parties to be involved in the ownership, operation and maintenance of railway system assets. The decisions made by each impact on all others. Game theory (GT) provides the framework to obtain the optimal decisions taking into account the various interactions. This paper gives a brief introduction to GT and its application to railway decision-making.

  • 34.
    Famurewa, Stephen Mayowa
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Juntti, Ulla
    Luleå Railway Research Centre.
    Nissen, Arne
    Trafikverket.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Augmented utilisation of possession time: Analysis for track geometry maintenance2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 4, p. 1118-1130Article in journal (Refereed)
    Abstract [en]

    The demand for increased capacity on existing railway networks is a challenge for many Europe-based infrastructure managers; addressing this challenge requires augmented utilisation of track possession time. It is considered that large-scale maintenance tasks such as geometry maintenance can be improved; thus, reducing the on-track maintenance time and allowing more traffic. In this study, an analysis of track geometry maintenance was performed with the objective of reducing the required possession time. The procedure and models for planning and optimizing track geometry maintenance are presented. A statistical model that uses a simulation approach was used to determine the condition of the track geometry, and a schedule optimization problem was formulated to support intervention decisions and optimize the track possession time. The results of the case study show that optimizing the maintenance shift length and cycle length are opportunities to reduce the extent of track possession required for the maintenance of the track geometry. In addition, continuous improvement of the tamping process through lean analysis promises about a 45% reduction in the required possession time for a tamping cycle.

  • 35.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Department of Electrical Engineering, Indian Institute of Technology, Bombay, International Institute of Information Technology, P-14, Pune Infotech Park, Phase-1, Hinjawadi, Stord/Haugesund University College, Haugesund.
    Context-Based Maintenance and Repair Shop Suggestion for a Moving Vehicle2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 67-81Conference paper (Refereed)
    Abstract [en]

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

  • 36.
    Villarejo, Roberto
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Johansson, Carl-Anders
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Sandborn, Peter
    University of Maryland, Department of Mechanical Engineering.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Context-driven decisions for railway maintenance2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 5, p. 1469-1483Article in journal (Refereed)
    Abstract [en]

    Railway assets suffer wear and tear during operation. Prognostics can be used to assess the current health of a system and predict its remaining life, based on features that capture the gradual degradation of its operational capabilities. Prognostics are critical to improve safety, plan successful work, schedule maintenance, and reduce maintenance costs and down time. Prognosis is a relatively new area; however, it has become an important part of condition-based maintenance of systems. As there are many prognostic techniques, usage must be tuned to particular applications. Broadly stated, prognostic methods are either data driven, or rule or model based. Each approach has advantages and disadvantages, depending on the hierarchical level of the analysed item; consequently, they are often combined in hybrid applications. A hybrid model can combine some or all model types; thus, more-complete information can be gathered, leading to more-accurate recognition of the impending fault state. However, the amount of information collected from disparate data sources is increasing exponentially and has different natures and granularity; therefore, there is a real need for context engines to establish meaningful data links for further exploration. This approach is especially relevant in railway systems where the maintainer and operator know some of the failure mechanisms, but the sheer complexity of the infrastructure and rolling stock precludes the development of a complete model-based approach. Hybrid models are extremely useful for accurately estimating the remaining useful life (RUL) of railway systems. This paper addresses the process of data aggregation into a contextual awareness hybrid model to obtain RUL values within logical confidence intervals so that the life cycle of railway assets can be managed and optimized.

  • 37.
    Soleimanmeigouni, Iman
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Letot, Christophe
    Machine Design and Production Engineering Lab, Research Institute for the Science and Management of Risks, University of Mons.
    Nissen, Arne
    Trafikverket.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cost-Based Optimization of Track Geometry Inspection2016Conference paper (Refereed)
    Abstract [en]

    Track geometry bear huge static and dynamic forces that accelerate degradation process. As a result, railway track should be inspected regularly to detect geometry faults and to plan maintenance actions in advanced. An inspection plan that minimizes track maintenance cost is highly desirable by infrastructure managers. This paper proposes constructing an integrated model to identify the optimum track geometry inspection interval. To this end, it develops a long term prediction model combining degradation, shock event, and tamping recovery models. It applies the Wiener process to model track geometry degradation, simulates shock event times using an exponential distribution, and uses a probabilistic model to model recovery after tamping. With the proposed integrated model and simulation, it is possible to identify the optimum track geometry inspection frequencies that minimize total track maintenance costs.

  • 38.
    Arasteh khouy, Iman
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Larsson-Kråik, Per-Olof
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Nissen, Arne
    Trafikverket.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cost-effective track geometry maintenance limits2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 2, p. 611-622Article in journal (Refereed)
    Abstract [en]

    In the past, railway maintenance actions were usually planned based on the knowledge and experience of the infrastructure owner. The main goal was to provide a high level of safety, and there was little concern about economic and operational optimisation issues. Today, however, a deregulated competitive environment and budget limitations are forcing railway infrastructures to move from safety limits to cost-effective maintenance limits to optimise operation and maintenance procedures. By so doing, one widens the discussion to include both operational safety and cost-effectiveness for the whole railway transport system. In this study, a cost model is proposed to specify the cost-effective maintenance limits for track geometry maintenance. The proposed model considers the degradation rates of different track sections and takes into account the costs associated with inspection, tamping, delay time penalties, and risk of accidents due to poor track quality. It draws on track geometry data from the Iron Ore Line (Malmbanan) in northern Sweden, used by both passenger and freight trains, to estimate the geometrical degradation rate of each section. The methodology is based on reliability and cost analysis and facilitates the maintenance decision-making process to identify cost-effective maintenance thresholds.

  • 39.
    Kumar, Uday
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, AlirezaLuleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.Verma, Ajit KumarDepartment of Electrical Engineering, Indian Institute of Technology, Bombay, International Institute of Information Technology, P-14, Pune Infotech Park, Phase-1, Hinjawadi.Varde, PrabhakarBhabha Atomic Research Centre, Trombay, Mumbai.
    Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective2016Collection (editor) (Refereed)
  • 40.
    Morant, Amparo
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Larsson-Kråik, Per-Olof
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Data-driven model for maintenance decision support: A case study of railway signalling systems2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 1, p. 220-234Article in journal (Refereed)
    Abstract [en]

    Signalling systems ensure the safe operation of the railway network. Their reliability and maintainability directly affect the capacity and availability of the railway network, in terms of both infrastructure and trains, as a line cannot be fully operative until a failure has been repaired. The purpose of this paper is to propose a data-driven decision support model which integrates the various parameters of corrective maintenance data and to study maintenance performance by considering different RAMS parameters. This model is based on failure analysis of historical events in the form of corrective maintenance actions. It has been validated in a case study of railway signalling systems and the results are summarised. The model allows the creation of maintenance policies based on failure characteristics, as it integrates the information recorded in the various parameters of the corrective maintenance work orders. The model shows how the different failures affect the dependability of the system: the critical failures indicate the reliability of the system, the corrective actions give information about the maintainability of the components, and the relationship between the corrective maintenance times measures the efficiency of the corrective maintenance actions. All this information can be used to plan new strategies of preventive maintenance and failure diagnostics, reduce the corrective maintenance, and improve the maintenance performance.

  • 41.
    Ghosh, Rajib
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Schunnesson, Håkan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Evaluation of operating life length of rotary tricone bits using Measurement While Drilling data2016In: International Journal of Rock Mechanics And Mining Sciences, ISSN 1365-1609, E-ISSN 1873-4545, Vol. 83, p. 41-48Article in journal (Refereed)
  • 42.
    Xin, Tao
    et al.
    School of Civil Engineering, Beijing Jiaotong University, People’s Republic of China.
    Famurewa, Stephen Mayowa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Gao, Liang
    School of Civil Engineering, Beijing Jiaotong University, People’s Republic of China.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Zhang, Qi
    School of Civil Engineering, Beijing Jiaotong University, People’s Republic of China.
    Grey-system-theory-based model for the prediction of track geometry quality2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 7, p. 1735-1744Article in journal (Refereed)
    Abstract [en]

    The quality of track geometry is an important aspect in railway engineering, as it reflects any deviations and thus the actual condition of a track. Monitoring and prediction of a relevant geometry quality parameter provides an opportunity for effective maintenance, thus creating the advantages of extending the life of the asset, reducing maintenance costs and minimizing possession time requirements. Effective maintenance practice requires a good understanding of the behaviour of track structures over time and also prediction of its condition using only a few inputs. This paper presents a grey-system-theory-based model for predicting track irregularity. Three variants of the grey model are presented and their performances are compared with simple linear and exponential models. Regression models and the grey-system-theory-based models are used to obtain the standard deviation of the longitudinal level from a series of geometry inspection data. The overall performances of the models are evaluated in terms of the regression and prediction accuracies, and it is shown that a Fourier series modification of the grey model has the best performance and the minimum error. The contribution of this paper is the creation of a prediction model for track geometry quality, which is essential for planning and scheduling of preventive geometry maintenance.

  • 43.
    Ghodrati, Behzad
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hoseinie, Hadi
    Hamedan University of Technology.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lean mining2016In: The Routledge companion to lean management / [ed] Torbjørn H Netland; Daryl J Powell, New York: Routledge, 2016, p. 302-310Chapter in book (Refereed)
  • 44.
    Karim, Ramin
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Westerberg, Jesper
    eMaintenance365 AB.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance Analytics: The New Know in Maintenance2016In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 49, no 28, p. 214-219Article in journal (Refereed)
    Abstract [en]

    Decision-making in maintenance has to be augmented to instantly understand and efficiently act, i.e. the new know. The new know in maintenance needs to focus on two aspects of knowing: 1) what can be known and 2) what must be known, in order to enable the maintenance decision-makers to take appropriate actions. Hence, the purpose of this paper is to propose a concept for knowledge discovery in maintenance with focus on Big Data and analytics. The concept is called Maintenance Analytics (MA). MA focuses in the new knowledge discovery in maintenance. MA addresses the process of discovery, understanding, and communication of maintenance data from four time-related perspectives, i.e. 1) “Maintenance Descriptive Analytics (monitoring)”; 2) “Maintenance Diagnostic Analytics”; 3) “Maintenance Predictive Analytics”; and 4) “Maintenance Prescriptive analytics”.

  • 45.
    Rai, Piyush
    et al.
    Department of Mining Engineering, Indian Institute of Technology (BHU), Varanasi, Banaras Hindu University, Varanasi.
    Schunnesson, Håkan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Lindqvist, Per-Arne
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Measurement-while-drilling technique and its scope in design and prediction of rock blasting2016In: International Journal of Mining Science and Technology, ISSN 2095-2686, Vol. 26, no 4, p. 711-719Article in journal (Refereed)
    Abstract [en]

    With rampant growth and improvements in drilling technology, drilling of blast holes should no longer be viewed as an arduous sub-process in any mining or excavation process. Instead, it must be viewed as an important opportunity to quickly and accurately measure the geo-mechanical features of the rock mass on-site, much in advance of the downstream operations. It is well established that even the slightest variation in lithology, ground conditions, blast designs vis-à-vis geologic features and explosives performance, results in drastic changes in fragmentation results. Keeping in mind the importance of state-of-the-art measurement-while-drilling (MWD) technique, the current paper focuses on integrating this technique with the blasting operation in order to enhance the blasting designs and results. The paper presents a preliminary understanding of various blasting models, blastability and other related concepts, to review the state-of-the-art advancements and researches done in this area. In light of this, the paper highlights the future needs and implications on drill monitoring systems for improved information to enhance the blasting results.

  • 46.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Measuring and Monitoring Operational Availability of Rail Infrastructure2016In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 5, p. 1457-1468Article in journal (Refereed)
    Abstract [en]

    In reliability and maintenance engineering, availability can be described as the ability of an item to be in a state to perform a required function at a given time. Availability is commonly given as a measure between zero and one, where one means the probability of an item to be available for use at a given time is 100%. Availability is measured in many areas, such as electronics, information technologies, military equipment, electrical grids and the industry. Various indicators related to availability of railways have been examined by academia and industry. However, there is some ambiguity about how to define and measure the availability of rail infrastructure, given railways' semi-continuous operation, besides data quality issues. This article considers the application of common definitions of availability to rail infrastructure. It includes a case study comparing various approaches for measuring availability. The case study ends with a section on how availability as a function of train frequency and maintenance time can be simulated. The results show rail infrastructure availability correlates well with train delay, but this depends on how infrastructure failure data and outliers are treated.Keywords: availability, reliability, dependability, maintenance engineering, railways, linear assets, condition monitoring

  • 47.
    Garmabaki, Amir
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Seneviratne, Dammika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Opportunistic inspection planning for Railway eMaintenance2016In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 49, no 28, p. 197-202Article in journal (Refereed)
    Abstract [en]

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

  • 48.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University.
    Singh, Gurinder
    Amity International Business School, Amity University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kapur, P.K.
    Amity Center for Interdisciplinary Research, Amity University, .
    Optimal release and patching time of software with warranty2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 462-468Article in journal (Refereed)
    Abstract [en]

    As we know in a competitive market, software firms are looking to sell their products at the earliest for maximum gains. Early delivery of a product is beneficial in terms of gaining market potential but may include some defects in it. On the other hand late delivery of a product ensures reliability but may results into disinterest of the customers. Thus, a vendor must focus on the best time for releasing the software. In recent times, early software release and updating it by providing patches in the operational phase is in trend. Also to satisfy customer’s primary concern of reliable software, firms are providing warranty on their products. Warranty period is the time in which firm provide assurance to the customers that under this period product will work properly and if any defect is found, firm will either repair or replace the software without charging the customer. But servicing during warranty period by updating with patches is also not economical from firm’s point of view. Hence it is important to find the optimal patch release time. In this paper we have proposed a generalized framework to find out the optimal release and patching time of software under warranty so that the total cost is minimized. Numerical example is given at the end to validate the proposed cost model.

  • 49.
    Stenström, Christer
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Norrbin, Per
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Preventive and corrective maintenance: cost comparison and cost–benefit analysis2016In: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980, Vol. 12, no 5, p. 603-617Article in journal (Refereed)
    Abstract [en]

    Maintenance can represent a significant portion of the cost in asset intensive organisations, as breakdowns have an impact on the capacity, quality and cost of operation. However, the formulation of a maintenance strategy depends on a number of factors, including the cost of down time, reliability characteristics and redundancy of assets. Consequently, the balance between preventive maintenance (PM) and corrective maintenance (CM) for minimising costs varies between organisations and assets. Nevertheless, there are some rules of thumb on the balance between PM and CM, such as the 80/20 rule. Studies on the relationship between PM and CM in practice are rare. Therefore, PM and CM costs are studied in this article by analysing historical maintenance data. A case study of rail infrastructure historical data is carried out to determine the shares of PM and CM, together with a cost–benefit analysis (CBA) to assess the value of PM. The results show that the PM represents 10% to 30% of the total maintenance cost when user costs, i.e. train delays, are included as a CM cost. The CBA shows the benefit of PM is positive with a benefit–cost ratio at 3.3. However, the results depend on the inclusion/exclusion of user costs, besides individual organisational parameters.

  • 50.
    Hoseinie, Seyed Hadi
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ghodrati, Behzad
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability Centered Maintenance (RCM) for Automated Mining Machinery2016Report (Other academic)
    Abstract [en]

    Reliability centered maintenance (RCM) was initiated on 1960s in Boeing company to optimize the maintenance process of aircrafts. Since that date, this method has been applied in wide range of industries and has provided a completely positive results and recommendations for implementation in other industries. RCM is a systematic approach to quantitatively assess and optimize the performance of preventive maintenance tasks and to eliminate non-value adding maintenance actions. It provides considerable cost savings due to optimum maintenance effort, increased safety and productivity. This research considers the feasibility of applying the RCM methodology to fully-automated underground mining machineries as one of the vital requirement of early future modern mining. For this purpose, a literature review has been done to clarify the advantages, requirements, issues and challenges of RCM in other industries such as aviation, marine, nuclear, oil and gas, and process industries. It has been tried to analyze the RCM procedure in detailed and to have a look on the adoption issues and requirement for RCM implementation in fully-automated mining. Mainly, in this research, following RCM documents and standards were used for feasibility study: • Classic RCM in Aviation industry (SAE-JA1011, SAE-JA1012)• NASA RCM guidelines • USA’s military standards MIL-STD-2173• International Atomic Energy Agency (IAEA) RCM documentUsing the above mentioned documents, an implementation issues and challenges in developing a RCM program for fully-automated underground mining machineries has been presented. The result of this study shows that RCM is applicable in maintenance planning for fully-automated underground mining machinery. Because, serious safety restrictions are associated with this kind of mining operation and RCM can properly help the engineers to analyze the safety consequences of any failure and make the best decision for maintenance tasks. However, practical application of RCM has some differences in mining context which in this project are discussed in detail. The investigations show the risk priority number is the suitable measure to select the RCM target component/system. Since, there is no operation in site, detective the some evident failures are become impossible in automated mining. Therefore, we have to consider the smartness level and capabilities of agent-based supervisors to get the real feeling of machinery health and operation condition. Internet of Thing platforms are also required in fully automated mine to develop the machine-to-machine communication and to reduce the risk of failures and failure propagation in fleet level. RCM could apply the outcomes of these advanced technologies to optimize the maintenance actions in automated mines.

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