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  • 1. Barabady, Javad
    et al.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability analysis of mining equipment: a case study of a crushing plant at Jajarm Bauxite Mine in Iran2008In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 93, no 4, p. 647-653Article in journal (Refereed)
    Abstract [en]

    The performance of mining machines depends on the reliability of the equipment used, the operating environment, the maintenance efficiency, the operation process, the technical expertise of the miners, etc. As the size and complexity of mining equipments continue to increase, the implications of equipment failure become ever more critical. Therefore, reliability analysis is required to identify the bottlenecks in the system and to find the components or subsystems with low reliability for a given designed performance. It is important to select a suitable method for data collection as well as for reliability analysis. This paper presents a case study describing reliability and availability analysis of the crushing plant number 3 at Jajarm Bauxite Mine in Iran. In this study, the crushing plant number 3 is divided into six subsystems. The parameters of some probability distributions, such as Weibull, Exponential, and Lognormal distributions have been estimated by using ReliaSoft's Weibull++6 software. The results of the analysis show that the conveyer subsystem and secondary screen subsystem are critical from a reliability point of view, and the secondary crusher subsystem and conveyer subsystem are critical from an availability point of view. The study also shows that the reliability analysis is very useful for deciding maintenance intervals.

  • 2.
    Bergman, Bo
    et al.
    Linköping Institute of Technology.
    Klefsjö, Bengt
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Letter to the editors1988In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 21, no 2, p. 155-160Article in journal (Other academic)
  • 3.
    Garmabaki, Amir
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Block, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pham, Hoang
    Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A Reliability Decision Framework for Multiple Repairable Units2016In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 150, p. 78-88Article in journal (Refereed)
    Abstract [en]

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

  • 4. Kumar, Dhananjay
    et al.
    Klefsjö, Bengt
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Proportional hazards model: a review1994In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 44, no 2, p. 177-188Article in journal (Refereed)
    Abstract [en]

    The proportional hazards model was introduced in 1972 by D. R. Cox in order to estimate the effects of different covariates influencing the times to the failures of a system. The model has been used rather extensively in biomedicine and, recently, interest in its application in reliability engineering has increased. The main purpose of this expository paper is to review the existing literature on the proportional hazards model. At first, the characteristics of the method are explained and its importance in reliability analysis is presented. Subsequently, methods for estimating parameters, along with the small and large sample properties of the estimators, are briefly discussed. Afterwards, work carried out so far on topics such as the effects of interaction, omission, measurement error, misclassification, monotonicity, multicolinearity and time dependency of covariates on the estimator are summarized. Some goodness-of-fit tests, especially those based on graphical methods, are described. We also describe some possible extensions of this model considered so far and available computer programs and packages for estimating the parameters of this model. Finally, some areas for further research are also discussed. (100 refs.)

  • 5. Kumar, Saurabh
    et al.
    Chattopadhyay, Gopi
    Queensland University of Technology School of Engineering Systems.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability improvement through alternative designs: a case study2007In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 92, no 7, p. 983-991Article in journal (Refereed)
    Abstract [en]

    In today's competitive world, reliability of equipment is extremely important to maintain quality and delivery deadlines. This is achieved by using proper maintenance and design changes for unreliable subsystems and components of a complex system. It is significant to develop a strategy for maintenance, replacement and design changes related to those subsystems and components. An analysis of down time along with causes is essential to identify the unreliable components and subsystems. This paper presents an analysis of failure data of solenoid coils of automatic internal grinding machine used in a bearing manufacturing plant. It analyses various replacement and change of design options such as introduction of pneumatic system in place of electromagnetic solenoids for improvement of reliability of the plunger movement mechanism.

  • 6.
    Kumar, Uday
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Klefsjö, Bengt
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Reliability analysis of hydraulic systems of LHD machines using the power law process model1992In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 35, no 3, p. 217-224Article in journal (Refereed)
    Abstract [en]

    Previously, a preliminary study of the reliability characteristics of a fleet of load-haul-dump (LHD) machines deployed at Kiruna mine showed that the engine and the hydraulics are the two most critical subsystems. Hydraulic systems are selected for further study because such systems are still under a development phase. Maintenance data for two years for these machines are analyzed. The tests for trends and serial correlation show that times between successive failures for the hydraulic systems are in most cases not independent and identically distributed. Goodness-of-fit tests show that the power law process model provides a good fit to the failure data of the hydraulic systems. Methods for parameter estimation in the power law process model and estimation of optimal maintenance intervals for such systems are presented. Emphasis is on the use of graphical methods for data analysis (14 refs.)

  • 7.
    Kumar, Uday
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Klefsjö, Bengt
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Granholm, Sven
    Luleå tekniska universitet.
    Reliability investigation for a fleet of load-haul-dump machines in a Swedish mine1989In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 26, no 4, p. 341-361Article in journal (Refereed)
    Abstract [en]

    The recent trends of deployment of complex and capital intensive equipment in mines has created interest in the field of maintenance and operational reliability of this equipment. The failure consequences associated with random equipment failures have considerable influence on the total operating cost of a highly mechanized mining system. Keeping this in view, a reliability investigation was initiated for a fleet of diesel operated load-haul-dump (LHD) machines in a Swedish mine. The goal is to estimate the operational reliability of these machines, locate items or assemblies which need improvement in design to enhance the reliability and to decide the duration of optimal preventive maintenance. Failure data for one year of LHD machines are analysed using the recently developed graphical technique of total time on test (TTT) plotting. Analytical methods like Kolmogorov-Smirnov test and maximum likelihood estimation are used in the analysis. The importance of testing the reliability data for the presence of trends and serial correlation is also emphasized.

  • 8.
    Kumer, Dhananjay
    et al.
    Luleå tekniska universitet.
    Klefsjö, Bengt
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability analysis of power transmission cables of electric mine loaders using the proportional hazards model1992In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 37, no 3, p. 217-222Article in journal (Refereed)
    Abstract [en]

    The proportional hazards model (PHM) is a powerful technique which can be used to investigate the effects of operating environment and the diagnostic variables (covariates) associated with an item on its life length. The effects of two different designs and maintenance on the reliability of a power transmission cable of an electric mine loader is investigated using PHM. The purpose is to illustrate the application of this model in making decisions about selecting the proper material or designing an item to meet the required purpose efficiently. (11 refs.)

  • 9.
    Lin, Jing
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Pulido, Julio
    ReliaSoft Corporation.
    Asplund, Matthias
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Reliability Analysis for Preventive Maintenance based on Classical and Bayesian Semi-parametric Degradation Approaches using Locomotive Wheel-sets as a Case Study2015In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 134, p. 143-156Article in journal (Refereed)
    Abstract [en]

    This paper undertakes a general reliability study using both classical and Bayesian semi-parametric degradation approaches. The goal is to illustrate how degradation data can be modelled and analysed to flexibly determine reliability to support preventive maintenance strategy making, based on a general data-driven framework. With the proposed classical approach, both Accelerated Life Tests (ALT) and Design of Experiments (DOE) technology are used to determine how each critical factor affects the prediction of performance. With the Bayesian semi-parametric approach, a piecewise constant hazard regression model is used to establish the lifetime using degradation data. Gamma frailties are included to explore the influence of unobserved covariates within the same group. Ideally, results from the classical and Bayesian approaches will complement each other. To demonstrate these approaches, this paper considers a case study of locomotive wheel-set reliability. The degradation data are prepared by considering an Exponential and a Power degradation path separately. The results show that both classical and Bayesian semi-parametric approaches are useful tools to analyse degradation data and can, therefore, support a company in decision making for preventive maintenance. The approach can be applied to other technical problems (e.g. other industries, other components).

  • 10.
    Mishra, Madhav
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Martinsson, Jesper
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Rantatalo, Matti
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Goebel, Kai
    NASA Ames Research Center, Intelligent Systems Division, Moffett Field, CA.
    Bayesian hierarchical model-based prognostics for lithium-ion batteries2018In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 172, p. 25-35Article in journal (Refereed)
    Abstract [en]

    To optimise operation and maintenance, knowledge of the ability to perform the required functions is vital. The ability is governed by the usage of the system (operational issues) and availability aspects like reliability of different components. This paper proposes a Bayesian hierarchical model (BHM)-based prognostics approach applied to Li-ion batteries, where the goal is to analyse and predict the discharge behaviour of such batteries with variable load profiles and variable amounts of available discharge data. The BHM approach enables inferences for both individual batteries and groups of batteries. Estimates of the hierarchical model parameters and the individual battery parameters are presented, and dependencies on load cycles are inferred. A BHM approach where the operational and reliability aspects end of life (EoD) and end of life (EoL) is studied where its shown that predictions of EoD can be made accurately with a variable amount of battery data. Without access to measurements, e.g. predicting a new battery, the predictions are based only on the prior distributions describing the similarity within the group of batteries and their dependency on the load cycle. A discharge cycle dependency can also be identified in the result giving the opportunity to predict the battery reliability.

  • 11.
    Murthy, D.N.P
    et al.
    School of Mechanical and Mining Engineering, The University of Queensland, St Lucia.
    Karim, M.R.
    Department of Statistics, University of Rajshahi.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Data management in maintenance outsourcing2015In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 142, p. 100-110Article in journal (Refereed)
    Abstract [en]

    Most businesses view maintenance as tasks carried out by technicians and the data collected is mostly cost related. There is a growing trend towards outsourcing of maintenance and the data collection issues are not addressed properly in most maintenance service contracts. Effective maintenance management requires proper data management - data collection and analysis for decision-making. This requires a proper framework and when maintenance is outsourced it raises several issues and challenges. The paper develops a framework for data management when maintenance is outsourced and looks at a real case study that highlights the need for proper data management.

  • 12.
    Sierra, G.
    et al.
    Department of Electrical Engineering, University of Chile, Santiago.
    Orchard, M.
    Department of Electrical Engineering, University of Chile, Santiago.
    Goebel, Kai
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. NASA Ames Research Center, Moffett Field, CA.
    Kulkarni, C.
    SGT Inc., NASA Ames Research Center, Moffett Field, CA.
    Battery Health Management for Small-size Battery-powered Rotary-wing Unmanned Aerial Vehicles: An Efficient Approach for Constrained Computing Platforms2018In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836Article in journal (Refereed)
    Abstract [en]

    This article presents a holistic framework for the design, implementation and experimental validation of Battery Management Systems (BMS) in rotatory-wing Unmanned Aerial Vehicles (UAVs) that allows to accurately (i) estimate the State of Charge (SOC), and (ii) predict the End of Discharge (EOD) time of lithium-polymer batteries in small-size multirotors by using a model-based prognosis architecture that is efficient and feasible to implement in low-cost hardware. The proposed framework includes a simplified battery model that incorporates the electric load dependence, temperature dependence and SOC dependence by using the concept of Artificial Evolution to estimate some of its parameters, along with a novel Outer Feedback Correction Loop (OFCL) during the estimation stage which adjusts the variance of the process noise to diminish bias in Bayesian state estimation and helps to compensate problems associated with incorrect initial conditions in a non-observable dynamic system. Also, it provides an aerodynamic-based characterization of future power consumption profiles. A quadrotor has been used as validation platform. The results of this work will allow making decisions about the flight plan and having enough confidence in those decisions so that the mission objectives can be optimally achieved.

  • 13.
    Söderholm, Peter
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A system view of the No Fault Found (NFF) phenomenon2007In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 92, no 1, p. 1-14Article in journal (Other academic)
    Abstract [en]

    When a unit is tested outside a technical system, it has normally been removed due to a fault. However, in some cases the external test may not discover any fault and a No Fault Found (NFF) event may occur. The NFF phenomenon is a major problem when dealing with complex technical systems, and its consequences may be manifested in decreased safety and dependability and increased life cycle costs. There are multiple interacting causes of NFF, demanding tough requirements for successful solutions. The purpose of this paper is to describe the phenomenon of NFF and to highlight possible improvements for the prevention of causes of NFF and the reduction of its consequences. The study was performed as an explorative literature study, and the analysis was based on a holistic system view. The identified causes and solutions are related to life cycle stages, availability performance factors, and system stakeholders.

  • 14. Talreja, Ramesh
    Fatigue reliability under random loads1983In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 5, no 2, p. 87-90Article in journal (Refereed)
  • 15.
    Zhang, Liangwei
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lin, Janet
    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.
    An Angle-based Subspace Anomaly Detection Approach to High-dimensional Data: With an Application to Industrial Fault Detection2015In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 142, p. 482-497Article in journal (Refereed)
    Abstract [en]

    The accuracy of traditional anomaly detection techniques implemented on full-dimensional spaces degrades significantly as dimensionality increases, thereby hampering many real-world applications. This work proposes an approach to selecting meaningful feature subspace and conducting anomaly detection in the corresponding subspace projection. The aim is to maintain the detection accuracy in high-dimensional circumstances. The suggested approach assesses the angle between all pairs of two lines for one specific anomaly candidate: the first line is connected by the relevant data point and the center of its adjacent points; the other line is one of the axis-parallel lines. Those dimensions which have a relatively small angle with the first line are then chosen to constitute the axis-parallel subspace for the candidate. Next, a normalized Mahalanobis distance is introduced to measure the local outlier-ness of an object in the subspace projection. To comprehensively compare the proposed algorithm with several existing anomaly detection techniques, we constructed artificial datasets with various high-dimensional settings and found the algorithm displayed superior accuracy. A further experiment on an industrial dataset demonstrated the applicability of the proposed algorithm in fault detection tasks and highlighted another of its merits, namely, to provide preliminary interpretation of abnormality through feature ordering in relevant subspaces.

  • 16.
    Zhang, Yang
    et al.
    Resilience Engineering Research Group, University of Nottingham.
    Andrews, John
    Resilience Engineering Research Group, University of Nottingham.
    Reed, Sean
    Resilience Engineering Research Group, University of Nottingham.
    Karlberg, Magnus
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Maintenance Processes Modelling and Optimisation2017In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 168, p. 150-160Article in journal (Refereed)
    Abstract [en]

    A Maintenance Procedure is conducted in order to prevent the failure of a system or to restore the functionality of a failed system. Such a procedure consists of a series of tasks, each of which has a distribution of times to complete and a probability of being performed incorrectly. The inclusion of tests can be used to identify any maintenance errors which have occurred. When an error is identified it can be addressed through a corresponding correction sequence which will have associated costs and add to the maintenance process completion time. A modified FMEA approach has been used to identify the possible tests. By incorporating any selection of tests into the maintenance process it can then analysed using a discrete-event simulation to predict the expected completion time distribution. The choice of tests to perform and when to do them is then made to successfully complete the maintenance objective in the shortest possible time using a genetic algorithm. The methodology is demonstrated by applying it to the repair process for a car braking system. The developed method is suitable for application in abroad range of industries.

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