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  • 1.
    Aalipour, Mojgan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ayele, Yonas Zewdu
    Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø.
    Barabadi, Abbas
    Tromsø University, Department of Engineering and Safety, UiT The Arctic University of Norway, Tromsø.
    Human reliability assessment (HRA) in maintenance of production process: a case study2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 2, p. 229-238Article in journal (Refereed)
    Abstract [en]

    Human reliability makes a considerable contribution to the maintenance performance, safety, and cost-efficiency of any production process. To improve human reliability, the causes of human errors should be identified and the probability of human errors should be quantified. Analysis of human error is very case-specific; the context of the field should be taken into account. The aim of this study is to identify the causes of human errors and improve human reliability in maintenance activities in the cable manufacturing industry. The central thrust of this paper is to employ the three most common HRA techniques—human error assessment and reduction technique, standardized plant analysis risk-human reliability, and Bayesian network—for estimating human error probabilities and then to check the consistency of the results obtained. The case study results demonstrated that the main causes of human error during maintenance activities are time pressure, lack of experience, and poor procedure. Moreover, the probabilities of human error, obtained by employing the three techniques, are similar and consistent

  • 2.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Remaining useful life estimation: Review2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 4, p. 461-474Article, book review (Other academic)
    Abstract [en]

    This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

  • 3.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Remaining useful life estimation: Review2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 4, p. 461-474Article in journal (Refereed)
    Abstract [en]

    This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

  • 4.
    Al-Jumaili, Mustafa
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Mahmood, Yasser Ahmed
    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.
    Assessment of railway frequency converter performance and data quality using the IEEE 762 Standard2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 42694-Article in journal (Refereed)
    Abstract [en]

    Reliability, availability and maintainability analysis is one of the most important tools for measuring system performance. The performance of a traction power supply system (TPSS) can be measured using the data collected from frequency converters, as these converters constitute the main part of the TPSS. The quality of the collected data should be good enough to provide the correct and complete information necessary for assessment of frequency converter performance. Many methods can be used to assess the performance of converters such as neural networks, fuzzy logic and standards. The IEEE 762 Standard offers a methodology that can provide key performance indicators for power generation units. This standard has been chosen for its widespread acceptance and applicability. To be able to evaluate a converter’s performance, IEEE 762 indexes should be calculated using data such as the downtime, reserve shutdown hours and service hours. Therefore, the purpose of this study is to assess the performance of the Swedish TPSS frequency converters using IEEE 762, and to assess the quality of data by inspecting their compatibility with this standard. In this study, an application has been developed to generate the missing information and to calculate the indexes provided by the standard, in order to evaluate the power converters’ performance. A case with sample data is also discussed in this paper.

  • 5. Barabady, Javad
    et al.
    Markeset, Tore
    University of Stavanger.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A framework for improvement of production plant performance using production assurance programs2010In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 1, p. 59-65Article in journal (Refereed)
    Abstract [en]

    The main objective of a production assurance program (PAP) for a production plant is to ensure that the planned production capacity is achieved. The assurance programs describe the activities necessary to fulfil the objectives, how they will be carried out, by whom, and when. These activities also provide input to decisions-making regarding design, manufacturing, construction, installation, operation, and maintenance of plants. It is a challenge to manage and improve production assurance. The aim of this paper is to present and discuss a methodology for improvement of production assurance performance through PAP, organized into four steps, namely data collection and information management, modeling and data analysis, generation of improvement alternatives and evaluation and decision-making.

  • 6.
    Famurewa, Stephen Mayowa
    et al.
    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.
    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.
    Implementation of performance based maintenance contracting in railway industries2013In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 4, no 3, p. 231-240Article in journal (Refereed)
    Abstract [en]

    The achievement of maintenance objectives to support the overall business objectives is the pursuit of any maintenance department. Using in-house or outsourced maintenance service provider is a decision which poses challenge in the management of maintenance function. Should the decision be for outsourcing, the next concern is the selection of the most appropriate strategy suitable for the business environment, structure and philosophy. In an effort to improve maintenance function so as to deliver set objectives, some infrastructure managers (IM) adopted the approach of outsourcing maintenance function, giving larger responsibilities to maintenance service providers called contractors. Moreover, such change requires adequate attention to meet the pressing need of achieving the designed capacity of the existing railway infrastructure and also support a competitive and sustainable transport system. This paper discusses performance based railway infrastructure maintenance contracting with its issues and challenges. The approach of this article is review of literature and as well as synthesis of practices. A framework to facilitate the successful implementation of Performance Based Railway Infrastructure Maintenance (PBRIM) is presented. Also a performance monitoring system is proposed to assess the outcome and identify improvement potentials of the maintenance outsourcing strategy. A case study is given to demonstrate the monitoring of a typical maintenance activity that can be outsourced using this outsourcing strategy.

  • 7.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. GKN Aerospace Engine Systems, Trollhättan, Sweden.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace Engine Systems, Trollhättan, Sweden.
    RUL estimation and maintenance optimization for aircraft engines: A system of system approach2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 450-461Article in journal (Refereed)
    Abstract [en]

    An aircraft engine is a system of systems with several degrees of complexity. It is important to perform the correct amount of maintenance at each individual maintenance event. A mathematical replacement model is used to ensure that the correct maintenance is performed. The reliability of the results from the mathematical replacement model will be improved if there is a better way to estimate the life length for on-condition engine parts.

  • 8.
    Fuqing, Yuan
    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.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering.
    Reliability prediction using support vector regression2010In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 3, p. 263-268Article in journal (Refereed)
    Abstract [en]

    Reliability prediction of machinery is crucial to schedule overhauls, spare parts replacement and maintenance interventions. Many AI tools have been used in order to provide these predictions for the industry. Support vector regression (SVR) is a nonlinear regression technique extended from support vector machine. SVR can fit data flexibly and it has a wide variety of applications. This paper utilizes SVR combining time series to predict the next failure time based on historical failure data. To solve the parameter selection problem a method has been proposed. This method approximates the widely used leave-one-out method. To bound the prediction error, a confidence interval is proposed based on the non-homogeneous poisson process. A numerical case from the mining industry is presented to demonstrate the developed approach.

  • 9.
    Galar, Diego
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pilar, Lamban
    Manufacturing and Design Engineering Department, University of Zaragoza.
    Luis, Berges
    Manufacturing and Design Engineering Department, University of Zaragoza.
    Application of dynamic benchmarking of rotating machinery for e-maintenance2010In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 3, p. 246-262Article in journal (Refereed)
    Abstract [en]

    The vibration analysis and condition monitoring technology is based on comparison of measurements obtained with benchmarks suggested by manufacturers or standards. In this case, the references provided by current rules are static and independent of parameters such as age, operational or environmental conditions in which the machine is analyzed. It creates false alarms and many unnecessary interventions. New communication technologies allow the integration of e-maintenance systems, production and real-time data or the result of vibration routes. The integration of all these data allows data mining and extraction of parameters to be incorporated into decision making typical of CBM, such as repairs, downtime, overhauls, etc. Absolute vibration data and spectral analysis of rotating machinery require the study of several signals by machine, which become hundreds of values and spectra to analyze where there, is a large number of machines. It is therefore necessary to find proper benchmark points to compare with vibration parameters. These parameters and benchmark points have to be adapted to the real status of the plant and vibratory conditions have to be automated to be easily understood by persons not connected with the detailed analysis of spectra. The trend of the measured data and its comparison with benchmarks should assess the success of the implementation of CBM and other decisions about implementation and changes in maintenance programs. This article proposes the use of two new indicators that result from data mining as a reference dynamic, not static as proposed by the standard, manufacturer or the expertise of maintenance technicians. These values show the real condition of the machine in terms of vibration. The application of these references to the decision making process of the maintenance manager and its inclusion in maintenance scorecard avoids unnecessary repairs caused by false alarms and thus prolongs the life of the equipment, resulting in the improvement of parameters such as the MTBF, in a e-maintenance system

  • 10.
    Gerdes, Mike
    et al.
    Aero - Aircraft Design and Systems Group, Hamburg University of Applied Sciences, Hamburg, Germany.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Division of Operation and Maintenance Engineering, Luleå University of Technology, Luleå, Sweden.
    Fuzzy condition monitoring of recirculation fans and filters2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 469-479Article in journal (Refereed)
    Abstract [en]

    A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.

  • 11.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Fuzzy condition monitoring of recirculation fans and filters2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 469-479Article in journal (Refereed)
    Abstract [en]

    A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.

  • 12.
    Gupta, Shashank
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Gupta, Piyush
    Inter-University Accelerator Centre, New Delhi.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modeling lean maintenance metric using incidence matrix approach2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no 4, p. 799-816Article in journal (Refereed)
    Abstract [en]

    Lean Maintenance (LM) enhances organizational profitability by identifying and eliminating maintenance related wastes. There exists no singular metric that measures maintenance related wastes. The paper identifies the LM features and models them using incidence-matrix. LM features are represented by diagonal elements, while its off-diagonal elements represent mutual influences among the LM features. The maintenance system leanness is quantified using the permanent of the matrix. The metric of leanness is proposed to be defined as Lean maintenance index (LMI) and is a ratio of the actual to the ideal values of permanent of actual and ideal maintenance system matrices. A high value of LMI indicates that the maintenance system is operating in a reduced waste scenario with respect to its resources. Among all the LM features, LMI was found to be most sensitive to management support including organizational processes. The results of the methodology are a good guide for managers. The shortcoming of the methodology is that, it relies on values and weights of the inter-relations among the features, which may not be necessarily true and may need further scientific rigor. The proposed methodology of using LMI as a singular metric to judge maintenance efficacy is expected to aid the operation managers in quantifying the maintenance leanness and may help them focus their efforts appropriately. There is no evidence to indicate existence of comprehensive list of LM features that culminate into a singular metric of maintenance productivity. This paper attempts to fill this gap.

  • 13.
    Gupta, Suprakash
    et al.
    Department of Mining Engineering, Indian Institute of Technology.
    Rahber, Anjum
    Department of Mining Engineering, Indian Institute of Technology.
    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.
    A vector-dissimilarity-based approach for multi-criteria decision making2013In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 4, no 3, p. 249-261Article in journal (Refereed)
    Abstract [en]

    Decision making in complex environments is influenced by a large number of conflicting and incommensurable factors. It is multidimensional and the influencing factors affect the decision process to varying degrees. The performance measurement of decision alternatives in multi-criteria decision making (MCDM) may be represented as a multidimensional vector in real space. The technique for order preference by similarity to ideal solution (TOPSIS) is a popular MCDM tool. However, sometimes this technique shows its inability to differentiate between decision alternatives. In this paper the limitations of TOPSIS are examined, and an improvement is suggested. The proposed new method uses the vector dissimilarity approach to remove the boundary restrictions and achieve greater sovereignty. The improved method has been demonstrated through a case study of maintenance design for dump trucks deployed in a large surface mine.

  • 14.
    Jonsson, Katrin
    et al.
    Umeå University, Faculty of Social Sciences, Department of Informatics.
    Holmström, Jonny
    Umeå University, Faculty of Social Sciences, Department of Informatics.
    Levén, Per
    Umeå University, Faculty of Social Sciences, Department of Informatics.
    Organizational dimensions of e-maintenance: a multi-contextual perspective2011In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 3, p. 210-218Article in journal (Refereed)
    Abstract [en]

    A key objective for e-maintenance efforts is to align maintenance processes with business- and operational processes in order to reach organizational objectives. In the context of the process- and manufacturing industry a key objective for firms is to avoid downtime and to make sure all critical production equipment is up and running. To this end, e-maintenance has become increasingly important for the process- and manufacturing industry. Successful e-maintenance is realized by the organizational use of advanced information technology-solutions which aims at moving maintenance work from being primarily reactive (e.g. to react and respond to equipment breakdowns) to predictive (e.g. to predict when equipment are in need of maintenance before it breaks down). Building on a collaborative project with industrial organizations in the pulp and paper and the mining industry this paper explores organizational opportunities and challenges associated with the design and implementation of IT-based services for remote diagnostics of industrial equipment. We observe opportunities and challenges related to organizational innovation and learning. The paper introduces a multi-contextual perspective to better understand the opportunities and challenges associated with organizational learning and innovation. We argue that in order for e-maintenance services to be successful it must not only build on leading-edge technological solutions but also be built on an explicit model for how the maintenance work is organized and how e-maintenance efforts are aligned with overall organizational objectives.

  • 15.
    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.

  • 16.
    Kapur, P.K.
    et al.
    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.
    Special issue on reliability, infocomm technology and business operations2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 399-Article in journal (Refereed)
  • 17. Kapur, P.K
    et al.
    Singh, Ompal
    Garmabaki, Amir Soleimani
    Singh, Jagvinder
    Multi up-gradation software reliability growth model with imperfect debugging.2010In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 4, p. 299-306Article in journal (Refereed)
    Abstract [en]

    Due to demand of new features and highly reliable software system, the software industries are speeding their up-gradations/add-ons in the software. The life of software is very short in the environment of perfect competition. Therefore the software developers have to come up with successive up gradations to survive. The reported bugs from the existing software and Features added to the software at frequent time intervals lead to complexity in the software system and add to the number of faults in the software. The developer of the software can lose on market share if it neglects the reported bugs and up gradation in the software and on the other hand a software company can lose its name and goodwill in the market if the reported bugs and functionalities added to the software lead to an increase in the number of faults in the software. To capture the effect of faults due to existing software and generated in the software due to add-ons at various points in time, we develop a multi up-gradation, multi release software reliability model. This model uniquely identifies the faults left in the software when it is in operational phase during the testing of the new code i.e. developed while adding new features to the existing software. Due to complexity and incomplete understanding of the software, the testing team may not be able to remove/correct the fault perfectly on observation/detection of a failure and the original fault may remain resulting in the phenomenon known as imperfect debugging, or get replaced by another fault causing error generation The model developed is validated on real data sets with software which has been released in the market with new features four times.

  • 18.
    Kayrbekova, Dina
    et al.
    University of Stavanger.
    Markeset, Tore
    University of Stavanger.
    Ghodrati, Behzad
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Activity based life cycle analysis as an alternative to conventional LCC in engineering design2011In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 2, no 3, p. 218-225Article in journal (Refereed)
    Abstract [en]

    Petroleum exploration and production in the Arctic region is becoming of increasing interest as the world needs more energy. However, since there is little experience and data on Arctic oil and gas production, the design of production facilities and equipment to be used in the Arctic region is fraught with high cost and risk. Conventional life cycle costing (LCC) approaches have been discussed in literature for many years, but it is difficult to perform such analysis due to the need of large amount of data and the inherent uncertainty in the results. There also is little evidence in the literature on practical usage of LCC. In this paper we discuss the differences between conventional LCC and activity-based LCC (AB-LCC) cost systems. Moreover, based on an analytical comparison between the two methodologies we find that the AB-LCC methodology may be a better alternative to use for cost analysis in the design of production facilities to be used in unfamiliar environments such as the Arctic. A simple numerical example is used to demonstrate the differences between conventional LCC and AB-LCC analysis.

  • 19.
    Kour, Ravdeep
    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.
    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.
    Applications of radio frequency identification (RFID) technology with eMaintenance cloud for railway system2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 99-106Article in journal (Refereed)
    Abstract [en]

    Radio Frequency Identification (RFID) helps automatic identification of objects using radio waves. This is not a new technology instead decades old and has been used during the World War II, when it was used by allied ground forces to track German bombers. It is a technology for wireless communication between a reader and a transponder/tag. This technology permits the transfer of data to the most diverse objects without the need for physical contact and uses intelligent barcodes to track items and have been successfully applied in military, security, healthcare, real time location tracking, vehicle identification and other areas. This paper is based on applications of radio frequency identification technology with eMaintenance cloud for railway system to analyze and visualize data of trains for the cost effective maintenance planning. Further, cloud computing is an emerging research area that can be utilised for acquiring an effective and efficient information logistics. Specifically, the widespread use of RFID will enable wagons to be tracked leading to better resource utilization, lower freight costs, and better maintenance. Therefore, it helps to provide greater control of the train carriages, making it easier to plan resources. However, RFID is a powerful tool that can help to improve industry proficiency, implementing this technology is not easy. Furthermore, operating RFID systems can be a challenging process. Thus, this paper is based on the application of RFID in the context of railway operation.

  • 20.
    Kumar, Uday
    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.
    Karim, Ramin
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Special issue on eMaintenance solutions and technologies: guest editorial2010In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, no 3, p. 187-188Article in journal (Refereed)
  • 21.
    Lundberg, Jan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bohlin, Alf
    Andreasen AB.
    Syk, Malin
    Trafikverket, Luleå.
    Blindfold tests on manganese crossing in railway application2011In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 2, no 2, p. 169-182Article in journal (Refereed)
    Abstract [en]

    Manganese crossings are widely used in the railway sector because of their self-hardening properties, but one major disadvantage is that maintenance actions using condition monitoring of internal flaws are problematic to perform. The reason is that manganese material is coarse-grained with internal reflections. In the present study, measurements on internal flaws with a spectrum of ultrasonic equipment were performed on a real manganese crossing. After the measurements, the crossing was cut up and inspected. Correlations with the measurements and the real flaws indicate that, independent of the equipment used, false echoes were common, as well as a low capacity to indicate real flaws.

  • 22.
    Lundberg, Jan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bohlin, Alf
    Syk, Malin
    Trafikverket, Luleå.
    Capacity test of ultrasonic equipment used for crack detection in railway application2011In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 2, no 2, p. 163-168Article in journal (Refereed)
    Abstract [en]

    Manganese crossings are widely used in the railway sector because of their self-hardening properties, but one major disadvantage is that maintenance actions using condition monitoring of internal flaws are problematic to perform since manganese material is coarse-grained with internal reflections. In the present study, spike- and square-pulsed ultrasonic apparatus, as well as phased aperture and time-corrected gain, together with suitable probes, was tested on manganese material in order to increase the understanding of the signal-noise ratio and the capacity to detect deeply placed internal flaws. Some of the most important results indicate that square pulses and timecorrected gain will increase the signal-noise ratio and also increase the capacity to find deeply placed flaws

  • 23.
    Mahmood, Yasser Ahmed
    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.
    Verma, Ajint
    Stord/Haugesund University College.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Fuzzy fault tree analysis: a review of concept and application2013In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 4, no 1, p. 19-32Article in journal (Refereed)
    Abstract [en]

    Fault tree analysis (FTA) is a widely used method for analyzing a system’s failure logic and calculating overall reliability. However, application of conventional FTA has some shortcomings, e.g. in handling the uncertainties, allowing the use of linguistic variables, and integrating human error in failure logic model. Hence, Fuzzy set theory has been proposed to overcome the limitation of conventional FTA. Fuzzy logic provides a framework whereby basic notions such as similarity, uncertainty and preference can be modeled effectively.The aim of this paper is to present a review of the concept of fuzzy theory with fault tree analysis and their applications since 1981, to reflect the current status of Fuzzy Fault Tree Analysis (FFTA) methodologies, their strengths, weaknesses, and their applications. This paper explains the fundamentals of fuzzy theory and describes application of fuzzy importance for using FFTA. The concept of the failure possibility and uncertainty analysis by using FFTA is discussed, and concludes with discussion on the application of FFTA in different fields. The review reveals the effectiveness of the FFTA in comparison with conventional FTA, when there is inadequate amount of accurate reliability oriented information.

  • 24.
    Nadakatti, Mahantesh
    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.
    Integrated machine health monitoring: a knowledge based approach2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 3, p. 371-382Article in journal (Refereed)
    Abstract [en]

    Machine health monitoring in today's complex plant systems has gained moreprominence than ever before because of steep increase in machinery costs, plant investments and maintenance expenses. A breakdown in any one machine or a component in a plant could mean huge losses coupled with safety and environmental threats as in the case of nuclear or chemical plants. The advances in manufacturing technology and the competition in the market necessitate the continuous availability of machinery for production. This has created a need for integrating maintenance with other manufacturing activities for better plant availability and efficiency. The objective of present research work is to present one such integrated machine health monitoring (IMHM) system developed using knowledge-based systems. The proposed model can be a useful maintenance tool in majority of small and medium scale manufacturing plants. A comprehensive knowledge based system (KBS)could bedeveloped over a period of time for industrial machinery which can monitor the major machinery faults and provide expert maintenance solutions through measurement and analysis of machine parameters such as power, vibration, noise, temperature, wear debris, lubricant condition, etc. A fault diagnosis system with KBS is based on computer programs interlinking fault symptoms, faults and remedies. These solutions are based on published information about permissible machine parameters in handbooks, journals, conferences besides the past maintenance experiences and from machine expert's knowledge regarding specific machinery problem and its solution. The paper outlines possible sub-modules for IMHM along with their features.

  • 25.
    Olsson, Ella
    et al.
    Saab AB Aerosystems, Sweden.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Andersson, Alf
    Volvo Car Corporation Manufacturing Engineering, Sweden.
    Case-based reasoning applied to geometric measurements for decision support in manufacturing2013In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 4, no 3, p. 223-230Article in journal (Refereed)
    Abstract [en]

    Measurements from products are continuously collected to allow adjustments in the production line to certify a feasible product quality. Case-based reasoning is a promising methodology for this type of quality assurance. It allows product measurements and its related adjustments to the production line to be stored as cases in a case-based reasoning system. The idea is to describe an event of adjustments based on deviations in geometric measurement points on a product and connect these measurements to their correlated adjustments done to the production line. Experience will implicitly be stored in each case in the form of uniquely weighted measurement points according to their positive influence on adjustments. Methods have been developed in order to find these positive correlations between measurements and adjustments by analysing a set of historical product measurement and their following adjustments. Each case saved in the case base will be “quality assured” according to this methods and only cases containing strong positive correlations will be used by the system. The correlations will be used to supply each case with its own set individual weights.

  • 26.
    Pourgol-Mohammad, Mohammad
    et al.
    Sahand University of Technology, Tabriz.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Special issue of IREC2016 conference selected papers2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no 3, p. 529-531Article in journal (Other academic)
  • 27.
    Pourgol-Mohammad, Mohammad
    et al.
    Department of Mechanical Engineering, Sahand University of Technology, Tabriz.
    Hejaz, Amirmohsen
    Department of Mechanical Engineering, Sahand University of Technology, Tabriz .
    Ghasemi, Pejman
    School of Engineering-Emerging Technologies, Tabriz University, Tabriz .
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Jalali-Vahid, Davoud
    Department of Mechanical Engineering, Sahand University of Technology, Tabriz.
    Design for reliability of automotive systems: case study of dry friction clutch2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no 3, p. 572-583Article in journal (Refereed)
    Abstract [en]

    Design and production of highly reliable and safer automotive systems with longer life has been a challenge. The pressure is outcome of high competitive market and recent safety issues of reputable car manufacturers. In this paper, an integrated methodology is proposed based on design for reliability of automotive systems and considering its reliability/safety critical sub-systems. In the proposed approach, the FMEA results are used in the process of failure mode/mechanism identification. The basic failure data, mostly obtained from generic databases, are adjusted by multiplicative corrective factors to account for the design and environment impacts on system failure characteristics. The system is modeled by reliability block diagram method, simulated by Monte Carlo technique. The results of FMEA and reliability evaluation are used for system improvement by reducing the components’ failure rates and potential change of system configuration. The components’ reliability is improved by increasing the quality of components by utilization of high quality materials and modern manufacturing techniques. Modification of system configuration, e.g., adding redundancy, is an alternative for system reliability improvement in some cases. The results show that the friction lining component is the most critical elements in terms of reliability importance. After completion of this phase, an assessment is done for system reliability by comparing the system reliability targets. As a case study, dry friction clutch is studied for assessment of the proposed method. In this study, the life test requirement is researched for each component using a reliability testing techniques. Finally, the uncertainties are computed associated with the failure data and final reliability estimations and the results were presented with a confidence interval.

  • 28.
    Sachdeva, Nitin
    et al.
    Department of Operational Research, University of Delhi, Faculty of Mathematical Sciences, Delhi, India.
    Singh, Ompal
    Department of Operational Research, University of Delhi, Faculty of Mathematical Sciences, Delhi, India.
    Kapur, P. K.
    Amity University, Noida, India.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Multi-criteria intuitionistic fuzzy group decision analysis with TOPSIS method for selecting appropriate cloud solution to manage big data projects2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 3, p. 316-324Article in journal (Refereed)
    Abstract [en]

    Today technology that learns from data to forecast future behavior of individuals, organizations, government and country as a whole, is playing a crucial role in the advancement of human race. In fact, the strategic advantage most of the companies today strive for are use of new available technologies like cloud computing and big data. However, today's dynamic business environment poses severe challenges in front of companies as to how to make use of the power of big data with the technical flexibility that cloud computing provides? Therefore, evaluating, ranking and selecting the most appropriate cloud solution to manage big data project is a complex concern which required multi criteria decision environment. In this paper we propose a hybrid TOPSIS method combined with intuitionistic fuzzy set to select appropriate cloud solution to manage big data projects in group decision making environment. In order to collate individual opinions of decision makers for rating the importance of various criteria and alternatives, we employed intuitionistic fuzzy weighted averaging operator. Lastly sensitivity analysis is performed so as to evaluate the impact of criteria weights on final ranking of alternatives.

  • 29.
    Seghiour, Abdellatif
    et al.
    Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
    Seghier, Tahar
    Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
    Zegnini, Boubakeur
    Laboratoire d’Etude et Développement des Matériaux Semi-Conducteurs et Diélectriques, Université Amar Telidji de Laghouat, Laghouat.
    Georgoulas, Georgios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Diagnosis of the combined rotor faults using air gap magnetic flux density spectrum for an induction machine2017In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no supp.2, p. 1503-1519Article in journal (Refereed)
    Abstract [en]

    This paper presents a method for the diagnosis of induction machines faults. The proposed method is capable to detect the presence of both dynamic eccentricity and broken rotor bar faults. Several studies have attempted to model an induction machine with isolated faults and provide methods for detecting them. However, the challenge begins, with the occurrence of combined defects which produce fault signatures that are difficult to separate. The novel proposed method is based on the measured air-gap magnetic flux density spectrum, which allows for the detection of combined faults. A finite element method is used for modelling the induction machine under faulty conditions, where the faults of rotor bars are created by a deleting operation of the boundary condition which is added to the air-gap part. Then, the dynamic eccentricity is formed by the movements of the rotating rotor’s centre with different ratings. From a modelling perspective, the contribution of the current work is the establishment of the relation of the air-gap of the rotor for modelling this kind of eccentricity fault. In addition, the proposed model of the air-gap includes two parts; one related to the stator and another one to the rotor, called statoric air-gap and rotoric air-gap respectively. The rotoric air-gap is employed for the dynamic eccentricity modelling. Computer simulations are presented using the air-gap magnetic vector and the magnetic field in X and Y components, to confirm the robustness of the proposed technique. Finally, the air-gap magnetic flux density spectrum is used for the analysis of combined rotor faults.

  • 30.
    Singh, Maneesh
    et al.
    Det Norske Veritas (DNV), Rosenberggata 99, 4007, Stavanger.
    Markeset, Tore
    University of Stavanger.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Some philosophical issues in modeling corrosion of oil and gas pipelines2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 55-74Article in journal (Refereed)
    Abstract [en]

    For the efficient design, installation, operation and maintenance of a plant, a reliable and robust mathematical model for predicting corrosion in pipelines can be a valuable asset. Such a model can help a plant supervisor to cut down on the expenditure arising from frequent inspections and unnecessary maintenance shutdowns and to take preventive maintenance action before an accident actually takes place. This paper discusses some of the philosophical issues related to the development of such a model. It also brings to the fore the limitations and value of such a model

  • 31.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Knowles, Michael
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Developing RCM strategy for wind turbines utilizing e-condition monitoring2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 150-156Article in journal (Refereed)
    Abstract [en]

    Renewable energy sources such as wind energy are available without any limitations. In order to extract this energy efficiency, the reliability of such technologies is critical if pay back periods and power generation requirements are to be met. Due to recent developments in the field of wind engineering and in particular the expansion of installed capacity around the world, the need for reliable and intelligent diagnostic tools is of greater importance. The number of offshore wind turbines installed in the seas around Britain’s coasts is likely to increase from just fewer than 150–7,500 over the next 10 years with the potential cost of £10 billion. Operation and Maintenance activities are estimated to be 35 % against the cost of electricity. However, the development of appropriate and efficient maintenance strategies is currently lacking in the wind industry. The current reliability and failure modes of offshore wind turbines are known and have been used to develop preventive and corrective maintenance strategies which have done little to improve reliability. In addition, the failure of one minor component can cause escalated damage to a major component, which can increase repair and or replacement costs. A reliability centered maintenance (RCM) approach offers considerable benefit to the management of wind turbine operations since it includes an appreciation of the impact of faults on operations. Due to the high costs involved in performing maintenance and the even higher costs associated with failures and subsequent downtime and repair, it is critical that the impacts are considered when maintenance is planned. This paper provides an overview of the application of RCM and on line e-condition monitoring to wind turbine maintenance management. Unplanned maintenance levels can be reduced by increasing the reliability of the gear box and individual gears through the analysis of lubricants. Finally the paper will discuss the development of a complete sensor-based processing unit that can continuously monitor the wind turbines lubricated systems and provide, via wireless technology, real time data enabling on shore staff with the ability to predict degradation anticipate problems and take remedial action before damage and failure occurs

  • 32.
    Singh, Sarbjeet
    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.
    Baglee, David
    Department of Computing, Engineering and Technology, Institute for Automotive and Manufacturing Advanced Practise, University of Sunderland.
    Björling, Sten-Erik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Self-maintenance techniques: a smart approach towards self-maintenance system2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 75-83Article in journal (Refereed)
    Abstract [en]

    The modern systems operating at varying conditions brought a new paradigm shift to in-machine renovation and repair. These systems often encounter an infinite collection of clumsy diagnostic tools and applications that decrease agility, increase time-to-repair, and increase management overheads. One approach is to remove the human and potential costly and time consuming human errors, from the diagnosis of faults and implementation of a maintenance strategy. In order to achieve this it is necessary to develop systems that support advanced intelligent maintenance systems or smart maintenance technologies. Self-maintenance machines can be a better option with the capabilities of condition monitoring, diagnosing, repair planning and executing in order to extend the life and performance of equipment. The objective of this paper is to discuss the concept of self-maintenance, need of self-maintenance, potential scenarios where self-maintenance can be successfully implemented and issues related to self-maintenance machines. It has been concluded that the aim is to have self-maintenance system in order to make a machine capable of reconfiguration, compensation, and self-maintenance.

  • 33.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Rupesh
    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 factors affecting human operator failure probability in railway maintenance tasks: an ISM-based analysis2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 129-138Article in journal (Refereed)
    Abstract [en]

    This paper investigates the factors affecting human operators’ probability of failure when performing railway maintenance tasks. The objective is to understand the interaction of the various factors and to identify driving and dependent factors. The factors are identified through a survey of the literature and ranked using a Likert scale. The reliability of measures is pretested by applying Cronbach’s alpha coefficient to responses to the questionnaire given to maintenance personnel. An interpretive structural model is presented, and factors are classified using matrice d’impacts croises-multiplication appliquéà un classement (MICMAC). The research may help maintenance management understand the interaction of factors affecting human failure probability in railway maintenance and help management devise policies and guidelines for railway maintenance related tasks.

  • 34.
    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

  • 35.
    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.

  • 36.
    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.

  • 37.
    Wijaya, Andi
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    The effect of the operator, the mine room and their interaction on the measured vibration level of a scaling machine2012In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 3, no 2, p. 145-152Article in journal (Refereed)
    Abstract [en]

    The objective of the present study is to find out the effect of the operator, the mine room and their interaction on the vibration measured on a scaling machine. Vibration measurements were conducted for three different mine rooms and three different drivers. The vector sum value of the root-mean-square acceleration, the vector sum value of the acceleration dose and the kurtosis sum were utilized to quantify the measured vibration. The unbalanced two-way ANOVA and the Kramer-Tukey test were utilized for the statistical analysis. The results show that the operating styles of the drivers in performing scaling activity and their interaction with the mine rooms have no significant effect on the vector sum value of the acceleration, the vector sum value of the acceleration dose and the kurtosis sum value. The mine rooms have a significant effect on the kurtosis sum value and the vector sum value of the acceleration dose, but not on the vector sum value of the acceleration

1 - 37 of 37
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