editorial mathematical applications to reliability and … · 2019. 8. 9. · editorial...
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EditorialMathematical Applications to Reliability and MaintenanceProblems in Engineering Systems
Wenbin Wang,1,2 Philip Scarf,3 Shaomin Wu,4 and Enrico Zio5,6
1Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China2Faculty of Business and Law, Manchester Metropolitan University, Manchester M15 6BH, UK3Salford Business School, University of Salford, Salford M5 4WT, UK4Kent Business School, University of Kent, Canterbury CT2 7PE, UK5CentraleSupelec, 92295 Chatenay-Malabry, France6Department of Energy, Polytechnic University of Milan, 20133 Milano, Italy
Correspondence should be addressed to Wenbin Wang; [email protected]
Received 8 March 2015; Accepted 8 March 2015
Copyright © 2015 Wenbin Wang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reliability and maintenance are well known concepts, whichcontribute to retaining engineering systems in their func-tioning states. Reliability is one of the fundamental criteriain engineering systems design and maintenance serves tosupport it throughout the systems life. As such, maintenanceacts in parallel to production and can have a great impact onthe availability and capacity of production and on the qualityof the products. For this reason, it deserves great attention,careful planning, and continuous improvement.
To inform the strategic decision-making on reliability andmaintenance of engineering systems, mathematical modelsand optimization techniques have long been used. Thesemodels and techniques can help in achieving the desiredtarget of system reliability and retain it with cost-effectivemaintenance.
The interest in themathematicalmodels and optimizationtechniques for system reliability and maintenance is demon-strated by the over 90 papers submitted to this special issue.Finally after an intense and rigorous reviewing process, 13papers were selected for publication.
The paper entitled “Prognostics andHealthManagement:A Review on Data Driven Approaches” presents an extensivereview on the stochastic processes and regression-basedmodels for Prognostics and Health Management (PHM),based on available monitored data. Some practical examplesand applications are also illustrated.
The paper entitled “Accelerated Testing with Multi-ple Failure Modes under Several Temperature Conditions”
illustrates an accelerated testing procedure, in which bothhigh temperatures and low temperatures are applied to aproduct. This allows building the reliability function of theproduct by statistical analysis, accounting for multiple failuremodes and variable working conditions.
The work by M. Kayid et al. introduces and studies a newstochastic order called proportional mean residual life order.Several characterizations and preservation properties of thenew order under some reliability operations are discussed.
The paper by Y. Chen et al. addresses the reliabilityanalysis of a two-component, cold-standby system with asingle repairman, whomay have vacations.The paper derivesa number of classical reliability indices under such condition:system availability, system reliability, the rate of occurrenceof system failures, and the mean time to the first failure of thesystem.
In the paper entitled “Gear Crack Level ClassificationBased on EMD and EDT,” the authors use Empirical ModeDecomposition to process vibration signals and, then, theEuclidean Distance Technique to measure the (Euclidean)similarity between the test sample and samples from fourclasses, for gear crack fault classification.The results obtainedshow that the proposed method has high accuracy rates inclassifying different crack levels and in adaptive to differentconditions.
X. Li and C. Zhang present a paper titled “Delayed AgeReplacement Policy with Uncertain Lifetime.” The authorsconsider the delayed age replacement policy with uncertain
Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2015, Article ID 629497, 2 pageshttp://dx.doi.org/10.1155/2015/629497
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2 Mathematical Problems in Engineering
lifetimes and find that the optimal replacement time isirrelevant to the uncertain distribution of lifetime of the firstunit, over the infinite time span.
Y. Gao et al. propose a new scheme of health indexprediction, which utilizes multiple relevant time series toenhance the completeness of the information and adopta prediction model based on least squares support vectorregression to perform the health trend prediction.
Z. Hajej et al. in their paper develop a mathematicalmodel to study the lease contract with basic and extendedwarranty, based on a win-win relationship between the lesseeand the lessor. The influence of the production rates isconsidered to determine a theoretical condition under whicha compromise-pricing zone exists, under different schemes ofmaintenance policies.
P. Gao and L. Xie develop a fuzzy dynamic reliabilitymodel for parallel mechanical systems, with respect to stressand strength parameters. A practical example is chosen todemonstrate the proposed model.
Y. Tang et al. develop a delay time-based model for opti-mization of inspection intervals, which is completely basedon maintenance data for estimating the model parameters.Then, they illustrate the method on a filter and a blowoutpreventer rubber core.
The availability of sufficient data for reliability and main-tenance modeling is always a problem in applications. Inthis regard, Y. Peng et al. present a method to estimatethe uncertainty intervals of the failure probability estimateby Weibull distributions, in the case of no available failuredata. Some engineering experience or hypothesis testing isrequired for the set-up of the shape parameter.
Y. Zhang et al. present an active learning Kriging solu-tion to calculate moment-independent importance measuresbased on the failure probability. Two numerical examples andtwo engineering examples are analyzed to demonstrate thesignificance of the proposed parametric sensitivity index, aswell as the efficiency and precision of the calculationmethod.
A. Kibria et al. address the problem of estimating thefailure rate of a component and provide a simulation-basedoptimizationmethod for theminimization of the discrepancybetween the simulated and the historical percentages offailures for turbine engine components. The method can beconsidered as a decision-making tool formaintenance, repair,and overhaul.
Acknowledgments
First, we would like to thank all authors for their excellentcontributions to this special issue. Of course, sincere thanksgo also to all reviewers for their careful (and voluntary)review work, which has helped to improve the quality of thepapers published and thus the significance of the special issue.
Wenbin WangPhilip ScarfShaomin Wu
Enrico Zio
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