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  • 1.
    Galar, Diego
    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.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Context awareness for maintenance decision making: A diagnosis and prognosis approach2015In: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 67, p. 137-150Article in journal (Refereed)
    Abstract [en]

    All assets necessarily suffer wear and tear during operation. Prognostics can assess the current health of a system and predict its remaining life based on features capturing 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 but has become an important part of Condition-based Maintenance (CBM) of systems. Broadly stated, prognostic methods are either data-driven, rule based, or model-based. Each approach has advantages and disadvantages; 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 fault state. In this context, it is important to evaluate the consistency and reliability of the measurement data obtained during laboratory testing and the prognostic/diagnostic monitoring of the system under examination.This approach is especially relevant in systems where the maintainer and operator know some of the failure mechanisms with a sufficient amount of data, but the sheer complexity of the assets precludes the development of a complete model-based approach. This paper addresses the process of data aggregation into a contextual awareness hybrid model to get Residual Useful Life (RUL) values within logical confidence intervals so that the life cycle of assets can be managed and optimised.

  • 2.
    Galar, Diego
    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.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pascual, Rodrigo
    Pontificia Universidad Católica de Chile.
    SMART maintenance and prescriptive asset management for mining2016Conference paper (Refereed)
    Abstract [en]

    Operation and maintenance (O&M) activities are commonly organized into scheduled and unscheduled actions. Scheduled maintenance is undertaken during pre-programmed inspections. Such maintenance operations try to minimize the risk of deterioration based on a priori knowledge of failure mechanisms and their timing. However, in complex systems it is not always possible to schedule maintenance actions to mitigate all undesired effects, and SMART systems, which monitor selected parameters, propose actions to correct any deviation in normal behaviour. Indeed, SMARTness is one step beyond the prediction of failure time but also a proposition of operation and maintenance profiles in order to fulfill the company goals. Therefore prognosis and RUL estimation become a part of the process in order to achieve prescriptive actions and control the degradation and operational aspects of the asset as per expected demand and customer request. These O&M decisions must be made on the basis of accepted risk. Performed or unperformed scheduled tasks as well as deferred corrective actions can have positive or negative consequences for the company, technicians, and machines. These three risks should be properly assessed and prioritized as a function of the goals to be achieved. This paper focuses on the SMARTness of assets in order to go one step forwards and propose prescriptive O&M decisions based on a self-risk assessment as a trade-off for asset integrity and company goals.

  • 3.
    Galar, Diego
    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.
    Simon, Victor
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Prognostic Hybrid Modelling from Data Fusion on Machine Tools2016In: Measurement, ISSN 1536-6367, E-ISSN 1536-6359Article in journal (Other (popular science, discussion, etc.))
    Abstract [en]

    This paper proposes an enhancement of remaining useful life (RUL) prediction method based on degradation trajectory tracking under the scope of machine tools. The operational condition data of the machine over time provides the potential degradation state at the next estimation iteration step, based on data-driven techniques. The model-based approach is considered as long-term prognostics method assuming that a physical model describing the degradation behaviour is available. Fusing the aforementioned techniques outputs a hybrid model for RUL estimation.

  • 4.
    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.

  • 5.
    Kans, Mirka
    et al.
    Linnaeus University.
    Galar, Diego
    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.
    Maintenance 4.0 in railway transportation industry2015Conference paper (Refereed)
    Abstract [en]

    Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organizations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerized systems, such as computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by applying operation and maintenance activities. Indeed safety becomes a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilizing cyber-physical systems and intelligent factories that are based on the concept of "internet of things". Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry. This paper also discusses the positive effects on technology; organisation and operations from a systems perspective.

  • 6.
    Kans, Mirka
    et al.
    Linnaeus University.
    Galar, Diego
    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.
    Maintenance 4.0 in Railway Transportation Industry2016In: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015) / [ed] Kari T. Koskinen; Helena Kortelainen; Jussi Aaltonen; Teuvo Uusitalo; Kari Komonen; Joseph Mathew; Jouko Laitinen, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 317-331Conference paper (Refereed)
    Abstract [en]

    Transportation systems are complex with respect to technology and operations with involvement in a wide range of human actors, organisations and technical solutions. For the operations and control of such complex environments, a viable solution is to apply intelligent computerised systems, such as computerised traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by applying operation and maintenance activities. Indeed safety becomes a more difficult goal to achieve using traditional maintenance strategies and computerised solutions come into the picture as the only option to deal with complex systems interacting among them trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Industry 4.0 is a term that describes the fourth generation of industrial activity which is enabled by smart systems and Internet-based solutions. Two of the characteristic features of Industry 4.0 are computerization by utilising cyber-physical systems and intelligent factories that are based on the concept of “internet of things”. Maintenance is one of the application areas, referred to as maintenance 4.0, in form of self-learning and smart systems that predicts failure, makes diagnosis and triggers maintenance by making use of “internet of things”. This paper discusses the possibilities that lie within applying the maintenance 4.0 concept in the railway transportation industry and the positive effects on technology, organisation and operations from a systems perspective.

  • 7.
    Mishra, Madhav
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Odelius, Johan
    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.
    Nissen, Arne
    Trafikverket, Luleå.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Particle filter-based prognostic approach for railway track geometry2017In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 96, p. 226-238Article in journal (Refereed)
    Abstract [en]

    Track degradation of ballasted railway track systems has to be measured on a regular basis, and these tracks must be maintained by tamping. Tamping aims to restore the geometry to its original shape to ensure an efficient, comfortable and safe transportation system. To minimize the disturbance introduced by tamping, this action has to be planned in advance. Track degradation forecasts derived from regression methods are used to predict when the standard deviation of a specific track section will exceed a predefined maintenance or safety limit. This paper proposes a particle filter-based prognostic approach for railway track degradation; this approach is demonstrated by examining different railway switches. The standard deviation of the longitudinal track degradation is studied, and forecasts of the maintenance limit intersection are derived. The particle filter-based prognostic results are compared with the standard regression method results for four railway switches, and the particle filter method shows similar or better result for the four cases. For longer prediction times, the error of the proposed method is equal to or smaller than that of the regression method. The main advantage of the particle filter-based prognostic approach is its ability to generate a probabilistic result based on input parameters with uncertainties. The distributions of the input parameters propagate through the filter, and the remaining useful life is presented using a particle distribution.

  • 8.
    Mishra, Madhav
    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.
    Ontology based diagnosis for maintenance decisions of Paper Mill roller using dynamic response2016In: 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. 187-196Conference paper (Refereed)
    Abstract [en]

    Context-aware systems have been applied in several fields like Information Technology, mobile, web services, travel guidance etc. These systems deliver decisions based on a ‘context’ by using contextual models. In paper industries, the failures of rollers were prominent and rolling element bearing is one of the critical components. The failure occurs due to the varying levels of the loads and external parameters that defines context. This paper demonstrates the ontology contextual modeling for the diagnosis of rollers as a context by using dynamic response. The roller is modeled using physical models and applying runs of different parameters and its levels. Then contextual models are generated for rollers to show relation among input contextual parameters with different features. This paper shows that this conceptual idea of decision based on different contexts using ontology models is for effective diagnosis facilitates maintenance strategies and further prospects in prognosis.

  • 9.
    Papic, Ljubisa
    et al.
    University of Kragujevac.
    Kovacevic, Srdja
    University of Kragujevac.
    Galar, Diego
    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.
    Investigation of Causes of Mining Machines Maintenance Problems2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, p. 283-299Conference paper (Refereed)
    Abstract [en]

    Human errors in the area of mining engineering are of critical issue that has serious concerns in safety, operation and production performance. There is a need for finding cause and effect relations with respect to the maintenance issues in order to detect, scrutinize and take necessary actions to reduce it. This paper deals with the human errors in the mining machines for the maintenance problems using fishbone cause and effect analysis. The investigation of these causes and effects are carried out during different operating conditions in typical mining industry and potential problems are assessed. There are several recommendations are provided to reduce the effect of human error so as to increase production by careful consideration of maintenance activities. .

  • 10.
    Papic, Ljubisa
    et al.
    University of Kragujevac.
    Kovacevic, Srdja
    University of Kragujevac.
    Galar, Diego
    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.
    Safety Analysis of Mining Machines Specific Maintenance Operations2016In: 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. 485-496Conference paper (Refereed)
    Abstract [en]

    By the rule, the object of the safety analysis is the technical system, for example, production or transportation, as the mining machines or their technological equipment are. The maintenance operations, up to present days, haven’t been investigated as the subject of safety analysis. However, as the practice of the technical systems maintenance shows so far many maintenance operations contain causes of danger. It means that it is useful to analyze such operations from the safety standpoint. From the standpoint of the mining machines safety, it should be stressed that in some researches, the expression “specific” is used for the critical maintenance operations. Therefore, the safety analysis of maintenance operations should precede the stage of maintenance operations. The possible approaches to the safety analysis in the area of maintenance on the basis of the method Failure Modes, Effects and Criticality Analysis are presented in the paper

  • 11.
    Parida, Aditya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    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.
    Guest Editorial2017In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 258-259Article in journal (Other academic)
  • 12.
    Rajesh, M.G.
    et al.
    Electronics Division, BARC, Mumbai.
    Vinod, Gopika
    Reactor Safety Division, BARC, Mumba.
    Das, D.
    Electronics Division, BARC, Mumbai.
    Bhatnagar, P.V.
    Electronics Division, BARC, Mumbai.
    Pithawa, C.K.
    Electronics Division, BARC, Mumbai.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Department of Electrical Engineering, IIT Bombay .
    Verma, Ajit Kumar
    Department of Electrical Engineering, IIT Bombay .
    A study of failure mechanisms in CMOS & BJT ICs and their effect on device reliability2010In: Proceedings of 2nd International Conference on Reliability, Safety and Hazard - ICRESH 2010: Mumbai Dec 15-16, 2010, Piscataway, NJ: IEEE Communications Society, 2010, p. 425-430Conference paper (Refereed)
    Abstract [en]

    The reliability of electronic systems, used in nuclear power plants, is traditionally estimated with empirical databases such as MIL-HDBK-217, PRISM etc. These methods assign a constant failure rate to electronic devices, during their useful life. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. The constant failure rate assumption stems from treating failures as random events. Electronics division of BARC is engaged in design & fabrication of CMOS and BJT ICs for nuclear pulse processing and signal conditioning. New microelectronic devices often exhibit infant mortality and wear-out phenomena while in operation. It points to competing degradation mechanisms-electro migration, hot carrier injection, dielectric breakdown etc. - that make a device's useful life different from that predicted by empirical methods. Understanding the dominant mechanisms that lead to device failure - Physics of Failure - is a more realistic approach to reliability prediction. This paper describes common failure mechanisms- encountered in CMOS and BJT ICs and the efforts being taken to quantify these effects in an optical-isolator IC - 4N36 - which forms a part of the trip generation circuit in neutron flux monitoring systems.

  • 13.
    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 manufacturing2018In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078Article 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.

  • 14.
    Thaduri, Adithya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Physics-of-failure based performance modeling of critical electronic components2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The traditional reliability prediction methods that draw on standard handbooks such as MIL-HDBK 217F, Telcordia, PRISM etc., are not appropriate to determine the reliability indices of these components. For one thing, technology is constantly advancing; for another, the empirical data do not always match the actual working environment.The newest reliability prediction methodology, the physics-of-failure (PoF), emphasizes the root cause of failure, failure analysis, and failure mechanisms based on the analysis of parameter characteristics. It involves a focused examination of failure point locations, considering the fabrication technology, process, materials and circuit layout obtained from the manufacturer. This methodology is capable of providing recommendations for the increased reliability of components using intuitive analysis.However, there is a limitation: it is sometimes difficult to obtain manufacturer’s details for failure analysis and quality information. Several statistical and probability modeling methods can be performed on the experimental data of these components to measure the time to failure. These experiments can be conducted using the accelerated-testing of dominant stress parameters such as Voltage, Current, Temperature, Radiation etc.In this thesis, the combination of qualitative data from PoF approach and quantitative data from the statistical analysis is used to create a modified physics-of-failure approach. This methodology overcomes the limitations of the standard PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is created to select the best option from failure data models, failure mechanisms, failure criteria and other factors to ensure a growth in reliability.In this study, the critical electronic components used in certain safety systems from different technologies are chosen for reliability prediction: Optocoupler, Constant Fraction Discriminator, BJT Transistor, Voltage Comparator, Voltage Follower and Instrumentation amplifier. The study finds that the modified physics-of-failure methodology provides more accurate reliability indices than the traditional approaches using field data. Stress based degradation models are developed for each of the components. The modified PoF models developed using Response Surface Regression and Support Vector Machine (SVM) show better performance.

  • 15.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Al-Jumaili, Mustafa
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kour, Ravdeep
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences2019In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, no 2, p. 149-159Article in journal (Refereed)
    Abstract [en]

    Recently, due to the advancements in the ICT (Information and Communication Technology), there has been lot of emphasis on digitization of the existing and newly developed infrastructure. In transportation infrastructure, in general, 80% of the assets are already in place and there has been tremendous push to move to the digital era. For efficient and effective design, construction, operation and maintenance of the infrastructure, due to this digitization, there is increasing research trend in data-driven decision-making algorithms that are proved to be effective because of several advantages. Since railway is the backbone of the society, the data-driven approaches will ensure the continuous operation, efficient maintenance, planning and potential future investments. The breach and leak of this potential data to the wrong hands might result in havoc, risk, trust, hazards and serious consequences. Hence, the main purpose of this paper is to stress the potential challenges, consequences, threats, vulnerabilities and risk management of data security in the railway infrastructure in context of eMaintenance. In addition, this paper also identifies the research methods to obtain and secure this data for potential possible research.

  • 16.
    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.
    Processing mining for maintenance decision support2017In: Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden / [ed] Diego Galar, Dammika Seneviratne, Luleå: Luleå tekniska universitet, 2017, p. 179-Conference paper (Refereed)
    Abstract [en]

    Process mining is gaining importance for the classification, clustering, workflow models, process discovery, predictions and planning and scheduling in a process or events in especially business oriented fields. On the other hand, there are several events that are required to perform a maintenance action in various industries. There is a need to understand the process flow of events to reduce the delays to increase the performance of the maintenance action. This paper applies the concept of process mining to understand the events in a typical maintenance action (repair or replacement,). We implemented the process mining for administrative, logistic and repair delays for one section in Swedish Railway. We identified the bottlenecks in this process fordifferent subsystems for productive feedback to the railway industry.

  • 17.
    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.

  • 18.
    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.
    Railway Assets: A Potential Domain for Big Data Analytics2015In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 53, p. 457-467, article id 53Article in journal (Refereed)
    Abstract [en]

    Two concepts currently at the leading edge of todays information technology revolution are Analytics and Big Data. The public transportation industry has been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally closed systems that involve sophisticated processing of large volumes of data. The more that public transportation professionals and decision makers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. This paper gives an overview of Big Data technologies in context of transportation with specific to Railways. This paper also gives an insight on how the existing data modules from the transport authority combines Big Data and how can be incorporated in providing maintenance decision making.

  • 19.
    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

  • 20.
    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
    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.
    Comparison of failure characteristics of different electronic technologies by using modified physics-of-failure approach2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 198-205Article in journal (Refereed)
    Abstract [en]

    The electronic components are used in several safety and maintenance systems that require accurate reliability prediction for higher availability. The traditional reliability prediction methods that draw on standard handbooks such as MIL-HDBK 217F, Telcordia, CNET etc., are inappropriate to determine the reliability indices of these components due to empirical methods does not comply with operating life cycle and technology advancements. The progressive reliability prediction methodology, the physics-of-failure (PoF), emphasizes the root cause of failure, failure analysis, and failure mechanisms based on the analysis of parameter characteristics. However, there is a limitation: it is sometimes difficult to obtain manufacturer’s details for failure analysis and quality information. Several statistical and probability modeling methods can be performed on the experimental data of these components to measure the time to failure. These experiments can be conducted using the accelerated-testing of dominant stress parameters such as voltage, current, temperature, radiation etc. In this paper, the combination of qualitative data from PoF approach and quantitative data from the statistical analysis is used to create a modified physics-of-failure approach. The critical electronic components used in certain safety systems from different technologies are chosen for reliability prediction: optocoupler, constant fraction discriminator, BJT transistor, voltage comparator, voltage follower and instrumentation amplifier is studied. The failure characteristics of each of the technologies are studied and compared according to operating conditions

  • 21.
    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.

  • 22.
    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
    Stord/Haugesund University College.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Gopinath, Rajesh
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Failure modeling of constant fraction discriminator using physics of failure approach2013In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 20, no 3Article in journal (Refereed)
    Abstract [en]

    Due to several advancements in the technology trends in electronics, the reliability prediction by the constant failure methods and standards no longer provide accurate time to failure. The physics of failure methodology provides a detailed insight on the operation, failure point location and causes of failure for old, existing and newly developed components with consideration of failure mechanisms. Since safety is a major criteria for the nuclear industries, the failure modeling of advanced custom made critical components that exists on signal conditioning module are need to be studied with higher confidence. One of the components, constant fraction discriminator, is the critical part at which the failure phenomenon and modeling by regression is studied in this paper using physics of failure methodology.

  • 23.
    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
    Stord/Haugesund University College.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Gopinath, Rajesh
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Stress factor and failure analysis of constant fraction discriminator using design of experiments2013In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 20, no 3Article in journal (Refereed)
    Abstract [en]

    Reliability prediction using traditional approaches were implemented at earlier stages of electronics. But due to advancements in science and technology, the above models are outdated. The alternative approach, physics of failure provides exhaustive information on basic failure phenomenon with failure mechanisms, failure modes and failure analysis becomes prominent because this method depends on factors like materials, processes, technology, etc., of the component. Constant fraction discriminators which is important component in NFMS needs to study failure characteristics and this paper provides this information on failure characteristics using physics of failure approach. Apart from that, the combined physics of failure approach with the statistical methods such as design of experiments, accelerated testing and failure distribution models to quantify time to failure of this electronic component by radiation and temperature as stress parameters. The SEM analysis of the component is carried out by decapsulating the samples and studied the impact of stress parameters on the device layout.

  • 24.
    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
    Indian Institute of Technology, Bombay.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Gopinath, Rajesh
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Study of reliability aspects in constant fraction discriminator2011In: 5th International Conference on Quality, Reliability and Information Technology (ICQRIT), Kathmandu, 2011, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Reliability prediction using conventional constant failure models by standard books in early phases of electronics dominates wide acceptance. But after 1980s, there was wide variation in electronic technology which made above models obsolete. Physics of Failure approach provides information on basic failure phenomenon with failure mechanisms and failure modes becomes prominent as it entirely depends on materials, processes, technology etc. Constant fraction discriminators which are failing frequently in the field need to be studied and this paper provides information on failure characteristics using physics of failure approach. Apart from that, we combined statistical methods such as Design of Experiments, Accelerated testing and failure distribution models to quantify time to failure of this electronic component by radiation and temperature as stress parameters.

  • 25.
    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.

  • 26.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Stord/Haugesund University.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Comparison of reliability prediction methods using life cycle cost analysis2013In: Proceedings on the 59th Annual Reliability and Maintainability Symopsium (RAMS 2013), 2013Conference paper (Refereed)
    Abstract [en]

    In this paper, it was discussed on the several reliability prediction models for electronic components and comparison of these methods was also illustrated. A combined methodology for comparing the cost incurring for prediction was designed and implemented with an instrumentation amplifier and a BJT transistor. By using the physics of failure approach, the dominant stress parameters were selected on basis of research study and were subjected to both instrumentation amplifier and BJT transistor. The procedure was implemented using the methodology specified in this paper and modeled the performance parameters accordingly. From the prescribed failure criteria, mean time to failure was calculated for both the components. Similarly, using 217 plus reliability prediction book, MTTF was also calculated and compared with the prediction using physics of failure. Then, the costing implications of both the components were discussed and compared them. From the results, it was concluded that for critical components like instrumentation amplifier though the initial cost of physics of failure prediction is too high, the total cost incurred including the penalty costs were lower than that of traditional reliability prediction method. But for non-critical components like BJT transistor, the total cost of physics of failure approach was too higher than traditional approach and hence traditional approach was much efficient. Several other factors were also compared for both reliability prediction methods.

  • 27.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, AjitStord/Haugesund University College.Kumar, UdayLuleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Analytics for Maintenance of Transportation in Smart Cities2015Conference proceedings (editor) (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 the urban space has led to a rich ecosystem of data producers and data consumers. 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 provides a base for a sustainable smart city. This work considers an overview of different challenges that utilizes different technologies for within a smart city maintenance with respect to the 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.

  • 28.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, Ajit Kumar
    Stord/Haugesund University College, Haugesund.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Gopinath, Rajesh
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability prediction of semiconductor devices using modified physics of failure approach2013In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 4, no 1, p. 33-47Article in journal (Refereed)
    Abstract [en]

    Traditional approaches like MIL-HDBK, Telcordia, and PRISM etc. have limitation in accurately predicting the reliability due to advancement in technology, process, materials etc. As predicting the reliability is the major concern in the field of electronics, physics of failure approach gained considerable importance as it involves investigating the root-cause which further helps in reliability growth by redesigning the structure, changing the parameters at manufacturer level and modifying the items at circuit level. On the other hand, probability and statistics methods provide quantitative data with reliability indices from testing by experimentation and by simulations. In this paper, qualitative data from PoF approach and quantitative data from the statistical analysis is combined to form a modified physics of failure approach. This methodology overcomes some of the challenges faced by PoF approach as it involves detailed analysis of stress factors, data modeling and prediction. A decision support system is added to this approach to choose the best option from different failure data models, failure mechanisms, failure criteria and other factors.

  • 29.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, A.K.
    Stord/Haugesund University College, Haugesund.
    Gopika, V.
    RSD, BARC, Trombay, Bombay.
    Gopinath, Rajesh
    RSD, BARC, Trombay, Bombay.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modified physics of failure approach for reliability prediction of electronic components2012In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, p. 181-190Conference paper (Refereed)
  • 30.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, A.K.
    Stord/Haugesund University College.
    Gopika, V.
    RSD, BARC, Trombay, Bombay.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Degradation modelling of voltage comparator using modified physics of failure approach2012In: Communications in Dependability and Quality Management, ISSN 1450-7196, Vol. 15, no 1, p. 76-87Article in journal (Refereed)
    Abstract [en]

    There are several electronic systems running continuously to control and monitor the various activities in the nuclear industry and reliability and safety of these systems is taken care of utmost importance. The Neutron Flux Monitoring System has individual electronic components is one of the modules present in the signal processing unit. This unit consists of numerous components such as Optocoupler, Constant fraction discriminator, Voltage Comparator, Instrumentation Amplifier etc., and this paper studies the degradation aspects of the Voltage comparator. The prediction of reliability was conducted at earlier phases of electronics but in the present advances in the technology that methods were no longer obsolete. Hence, the other alternative, physics of failure approach laid emphasis on the root cause analysis and degradation of the performance parameters. Apart from that, we combined physics of failure approach with the statistical methods such as Design of Experiments, Accelerated testing and failure distribution models to quantify time to failure of this electronic component by radiation and temperature as stress parameters. The degradation of the performance parameter is modelled and compared using regression analysis, parametric analysis, several response plots and response surface method.

  • 31.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, A.K.
    Stord/Haugesund University.
    Gopika, V.
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability prediction of constant fraction discriminator using modified PoF approach2013In: Proceedings on the 59th Annual Reliability and Maintainability Symopsium (RAMS 2013), 2013Conference paper (Refereed)
    Abstract [en]

    In this paper, the introduction, functioning and importance of constant fraction discriminator in nuclear field was studied. Furthermore, reliability and degradation mechanisms that affects the performance of output pulse with temperature and dose rates acts as input characteristics was properly explained and verified with the experiments. Accelerated testing was carried out to define the life testing of the component with respect to degradation in output TTL pulse amplitude. Time to failure was to be properly quantified and modelled accordingly.

  • 32.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, A.K.
    Stord/Haugesund University College.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Gopika, V.
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Rajesh, Gopinath
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Datta, D.
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Support vector regression degradation modeling for constant fraction discriminator2012In: Communications in Dependability and Quality Management, ISSN 1450-7196, Vol. 15, no 1, p. 101-122Article in journal (Refereed)
    Abstract [en]

    In the nuclear industries, the electronic signal processing unit plays a key role in the data processing, data analysis, control mechanism and more importantly safety of the nuclear reactor. The processing unit comprises of different modules that process pulse and current signals from detector and constant fraction discriminator which has higher criticality is one of them. Earlier the reliability was calculated using MilHdbk 217 standard and found discrepancies to the field failure. This paper studies the failure phenomenon using physics of failure approach by studying degradation and failure analysis and conducting the experiments using modified physics of failure methodology. Support vector machine (SVM) is a machine learning phenomenon using statistical learning theory. In this paper, failure data is fed to SVM for regression models intended for life prediction. From the parametric analysis, it was found that Sequential minimal optimization with RBF kernel represent the best model for degradation of the CFD. This method provides higher accuracy compared to response surface methodology.

  • 33.
    Thaduri, Adithya
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Verma, A.K.
    Department of Electrical Engineering, Indian Institute of Technology, Bombay.
    Vinod, G.
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Rajesh, M.
    Bhabha Atomic Research Centre, Trombay, Mumbai.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Two-stage design of experiments approach for prediction of reliability of optocouplers2012In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 19, no 2Article in journal (Refereed)
    Abstract [en]

    Conventionally, reliability prediction of electronic components is carried out using standard handbooks such as MIL STD 217 plus, Telcordia, etc. But these methods fail to provide a realistic estimate of reliability for upcoming technologies. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. Industries employ different technologies like CMOS, BJT and BICMOS for various applications. The possibility of chance of failure at interdependencies of materials, processes, and characteristics under operating conditions is the major concern which affects the performance of the devices. They are characterized by several failure mechanisms at various stages such as wafer level, interconnection, etc. For this, the dominant failure mechanisms and stress parameters needs to be identified. Optocouplers are used in input protection of several instrumentation systems providing safety under over-stress conditions. Hence, there is a need to study the reliability and safety aspects of optocouplers. Design of experiments is an efficient and prominent methodology for finding the reliability of the item, as the experiment provides a proof for the hypothesis under consideration. One of the important techniques involved is Taguchi method which is employed for finding the prominent failure mechanisms in semiconductor devices. By physics of failure approach, the factors that are affecting the performance on both environmental and electrical parameters with stress levels for optocouplers are identified. By constructing a 2-stage Taguchi array with these parameters where output parameters decides the effect of top two dominant failure mechanisms and their extent of chance of failure can be predicted. This analysis helps us in making the appropriate modifications considering both the failure mechanisms for the reliability growth of these devices. This paper highlights the application of design of experiments for finding the dominant failure mechanisms towards using physics of failure approach in electronic reliability prediction of optocouplers for application of instrumentation

  • 34.
    Thaduri, Adithya
    et al.
    Department of Electrical Engineering, Indian Institute of Technology, Bombay.
    Verma, A.K.
    Department of Electrical Engineering, Indian Institute of Technology, Bombay.
    Vinod, Gopika
    Bhabha Atomic Research Centre, Trombay.
    Geoplan, Rejesh
    Bhabha Atomic Research Centre, Trombay.
    Reliability prediction of optocouplers for the safety of digital instrumentation2011In: 2011 IEEE International Conference on Quality and Reliability (ICQR), Piscataway, NJ, 2011, p. 491-495Conference paper (Refereed)
    Abstract [en]

    Conventionally, reliability prediction of electronic components is carried out using standard handbooks such as MIL STD 217plus, Telecordia, etc. But these methods fail to provide a realistic estimate of reliability for upcoming technologies. Currently, electronic reliability prediction is moving towards applying the Physics of Failure approach which considers information on process, technology, fabrication techniques, materials used, etc. Industries employ different technologies like CMOS, BJT and BICMOS for various applications. The possibility of chance of failure at interdependencies of materials, processes, and characteristics under operating conditions is the major concern which affects the performance of the devices. They are characterized by several failure mechanisms at various stages such as wafer level, interconnection, etc. For this, the dominant failure mechanisms and stress parameters needs to be identified. Optocouplers are used in input protection of several instrumentation systems providing safety under over-stress conditions. Hence, there is a need to study the reliability and safety aspects of optocouplers. Design of experiments is an efficient and prominent methodology for finding the reliability of the item, as the experiment provides a proof for the hypothesis under consideration. One of the important techniques involved is Tagauchi method which employs for finding the prominent failure mechanisms in semiconductor devices. By physics of failure approach, the factors that are affecting the performance on both environmental and electrical parameters with stress levels for optocouplers are identified. By constructing a 2-stage tagauchi array with these parameters where output parameters decides the effect of top two dominant failure mechanisms and their extent of chance of failure can be predicted. This analysis helps us in making the appropriate modifications considering both the failure mechanisms for the reliability growth of these devices. Thi- - s paper highlights the application of design of experiments for finding the dominant failure mechanisms towards using physics of failure approach in electronic reliability prediction of optocouplers for application of instrumentation.

1 - 34 of 34
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