共查询到20条相似文献，搜索用时 0 毫秒
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Adílson J. Marcorin Alvaro J. Abackerli 《Quality and Reliability Engineering International》2006,22(7):851-862
Product reliability is a very important issue for the competitive strategy of industries. In order to estimate a product's reliability, parametric inferential methods are required to evaluate survival test data, which happens to be a fairly expensive data source. Such costly information usually imposes additional compromises in the product development and new challenges to be overcome throughout the product's life cycle. However, manufacturers also keep field failure data for warranty and maintenance purposes, which can be a low‐cost data source for reliability estimation. Field‐failure data are very difficult to evaluate using parametric inferential methods due to their small and highly censored samples, quite often representing mixed modes of failure. In this paper a method for reliability estimation using field failure data is proposed. The proposal is based on the use of non‐parametric inferential methods, associated with resampling techniques to derive confidence intervals for the reliability estimates. Test results show the adequacy of the proposed method to calculate reliability estimates and their confidence interval for different populations, including cases with highly right‐censored failure data. The method is shown to be particularly useful when the sampling distribution is not known, which happens to be the case in a large number of practical reliability evaluations. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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Xintao Xia 《Quality and Reliability Engineering International》2012,28(8):981-990
For costly and dangerous experiments, growing attention has been paid to the problem of the reliability analysis of zero‐failure data, with many new findings in world countries, especially in China. The existing reliability theory relies on the known lifetime distribution, such as the Weibull distribution and the gamma distribution. Thus, it is ineffective if the lifetime probability distribution is unknown. For this end, this article proposes the grey bootstrap method in the information poor theory for the reliability analysis of zero‐failure data under the condition of a known or unknown probability distribution of lifetime. The grey bootstrap method is able to generate many simulated zero‐failure data with the help of few zero‐failure data and to estimate the lifetime probability distribution by means of an empirical failure probability function defined in this article. The experimental investigation presents that the grey bootstrap method is effective in the reliability analysis only with the few zero‐failure data and without any prior information of the lifetime probability distribution. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Koosha Rafiee Qianmei Feng David W. Coit 《Quality and Reliability Engineering International》2017,33(7):1351-1366
In this study, we introduce reliability models for a device with two dependent failure processes: soft failure due to degradation and hard failure due to random shocks, by considering the declining hard failure threshold according to changes in degradation. Owing to the nature of degradation for complex devices such as microelectromechanical systems, a degraded system is more vulnerable to force and stress during operation. We address two different scenarios of the changing hard failure threshold due to changes in degradation. In Case 1, the initial hard failure threshold value reduces to a lower level as soon as the overall degradation reaches a critical value. In Case 2, the hard failure threshold decreases gradually and the amount of reduction is proportional to the change in degradation. A condition‐based maintenance model derived from a failure limit policy is presented to ensure that a device is functioning under a certain level of degradation. Finally, numerical examples are illustrated to explain the developed reliability and maintenance models, along with sensitivity analysis. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Vivien Fa‐Si‐Oen Antonio Pievatolo 《Quality and Reliability Engineering International》2000,16(1):17-22
We model the yearly counts of occurred ruptures in a metropolitan gas distribution network using both a homogeneous Poisson process and a power law process. Covariates such as depth, diameter and site of the pipes are included via standard generalized linear modelling for Poisson data in the first case and via a proportional intensity function in the second case. It is found that the homogeneous Poisson process provides an acceptable interpretation of the data, thus confirming the hypothesis that the cast iron pipes do not suffer from erosion and that only the traffic conditions on the site above the pipes seem to affect the rupture rate. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
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基于可靠性理论的包装振动试验方法改进 总被引：1，自引：0，他引：1
目的基于可靠性理论改进包装件的振动试验方法。方法通过界定产品平均寿命、试验截止时间和失效数,研究了样本大小对整个试验可靠程度的影响,以及改变包装阻尼与振动频率对试件振动幅值的影响。结果保证包装产品的可靠性有必要明确样本的大小,样本过小将不能完全体现该批产品的可靠程度;样本过大,虽然能充分体现该批产品的可靠程度,但试验费用将大大提高。随着产品样本的增大,使用者的风险降低。结论在包装件振动试验中融入可靠性理论,并在试验标准中加入失效率验证程序和失效率等级等内容,提高了包装件的可靠性。 相似文献
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This paper analyzes the competing and dependent failure processes for multi-state systems suffering from four typical random shocks. Reliability analysis for discrete degradation is conducted by explicitly modeling the state transition characteristics. Semi-Markov model is employed to explore how the system vulnerability and potential transition gap affect the state residence time. The failure dependence is specified as that random shocks can not only lead to different abrupt failures but also cause sudden changes on the state transition probabilities, making it easier for the system to stay at the degraded states. Reliability functions for all the exposed failure processes are presented based on the corresponding mechanisms. Interactions between different failure processes are also taken into account to evaluate the actual reliability levels in the context of degradation and distinct random shocks. An illustrative example of a multi-state air conditioning system is studied to demonstrate how the proposed method can be applied to the engineering practice. 相似文献
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Zhihua Wang Shihao Cao Wenbo Li Chengrui Liu Jingjing Mu 《Quality and Reliability Engineering International》2023,39(1):47-66
Most systems experience both random shocks (hard failure) and performance degradation (soft failure) during service span, and the dependence of the two competing failure processes has become a key issue. In this study, a novel dependent competing failure processes (DCFPs) model with a varying degradation rate is proposed. The comprehensive impact of random shocks, especially the effect of cumulative shock, is reasonably considered. Specifically, a shock will cause an abrupt degradation damage, and when the cumulative shock reaches a predefined threshold, the degradation rate will change. An analytical reliability solution is derived under the concept of first hitting time (FHT). Besides, a one-step maximum likelihood estimation method is established by constructing a comprehensive likelihood function. Finally, the reasonability of the closed form reliability solution and the feasibility and effectiveness of the proposed DCFPs modeling methodology are demonstrated by a comparative simulation study. 相似文献
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Qingbiao Song;Jiayin Tang;Honglei Wei;Yong Li; 《Quality and Reliability Engineering International》2024,40(5):2584-2602
The two dependent competing risks are soft failure due to aging degradation and fragmentation caused by shocks and hard failure due to spring breakage caused by the same shock process. Considering the complexity of the product itself and the instability of the working environment, this study proposed a generalized reliability model for systems experiencing dependent competing failure processes (DCFPs) of degradation and random shocks, which considered two kinds of DCFP: (1) shock process could affect soft failure thresholds; (2) degradation process could affect hard failure thresholds. In case (1), we considered the effect that a cumulative number of shocks above a certain magnitude could have on the change in the soft failure threshold. In case (2), we considered not only the shock process's impact on the soft failure threshold but also the total degradation (including continuous degradation and sudden degradation caused by shock) on the hard failure threshold. The model captures the features that the shocks experienced by the system affect the degradation process, accelerating the system degradation and causing soft failures; the degradation process of the system affects the shock process, making the system more susceptible to failure from external shocks. Finally, an example using micro-electro-mechanical systems devices illustrates the effectiveness of the proposed approach with sensitivity analysis. 相似文献
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S. A. Eide 《Reliability Engineering & System Safety》2003,80(2):123-132
To support the development of probabilistic risk assessments of US commercial nuclear power plants, significant effort has been expended to develop generic failure rates for components. Generic failure rates indicate industry-average performance of components, rather than component performance at a specific plant. Most publicly available, generic failure rate databases are typically based on data collected in the 1970s and 1980s for US nuclear power plants. Recent data analysis programs sponsored by the US Nuclear Regulatory Commission and data collection programs sponsored by the Institute of Nuclear Power Operations provide an opportunity to compare more recent failure rate estimates with those obtained in the 1970s and 1980s. These recent results indicate that many component generic failure rates are now lower than observed in the 1970s and 1980s. Suggestions for up-to-date failure rates are presented. Also, failure to run rates for standby components are presented for both short- and longer-term run times. 相似文献
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Lei Zhang Jianguo Zhang Lingfei You Shuang Zhou 《Quality and Reliability Engineering International》2019,35(1):263-279
The traditional reliability analysis method based on probabilistic method requires probability distributions of all the uncertain parameters. However, in practical applications, the distributions of some parameters may not be precisely known due to the lack of sufficient sample data. The probabilistic theory cannot directly measure the reliability of structures with epistemic uncertainty, ie, subjective randomness and fuzziness. Hence, a hybrid reliability analysis (HRA) problem will be caused when the aleatory and epistemic uncertainties coexist in a structure. In this paper, by combining the probability theory and the uncertainty theory into a chance theory, a probability‐uncertainty hybrid model is established, and a new quantification method based on the uncertain random variables for the structural reliability is presented in order to simultaneously satisfy the duality of random variables and the subadditivity of uncertain variables; then, a reliability index is explored based on the chance expected value and variance. Besides, the formulas of the chance theory‐based reliability and reliability index are derived to uniformly assess the reliability of structures under the hybrid aleatory and epistemic uncertainties. The numerical experiments illustrate the validity of the proposed method, and the results of the proposed method can provide a more accurate assessment of the structural system under the mixed uncertainties than the ones obtained separately from the probability theory and the uncertainty theory. 相似文献
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Li-Sha Zhu Hao Lu Yi-Min Zhang 《Quality and Reliability Engineering International》2021,37(6):2950-2969
Despite many advances in the field of computational system reliability analysis, estimating the joint probability distribution of correlated non-normal state variables on the basis of incomplete statistical data brings great challenges for engineers. To avoid multidimensional integration, system reliability estimation usually requires the calculation of marginal failure probability and joint failure probability. The current article proposed an integrated approach for estimating system reliability on the basis of the high moment method, saddle point approximation, and copulas. First, the statistic moment estimation based on the stochastic perturbation theory is presented. Thereafter, by constructing CGF (concise cumulant generating function) for the state variable with its first four statistical moments, a fourth moment saddle point approximation method is established for the component reliability estimation. Second, the copula theory is briefly introduced and extensively utilized two-dimensional copulas are presented. The best fit copula for estimating the probability of system failure is selected according to the AIC (Akaike Information Criterion). Finally, the derived method is applied to three numerical examples for the sake of a comprehensive validation. 相似文献
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本文提出一种动态测试中单次性信号测试数据的贝叶斯推断方法,其中单次性的被测信号和输出信号被认为是随机过程的现实。通常,在进行测试之前获得这些现实的一些知识是有用的。为了从单次性的动态测试中获取最多的信息,引入了贝叶斯方法使实验者根据测试结果提供的新的信息修改其先验置信度。 相似文献
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Hao Lyu;Bing Lu;Hualong Xie;Hongchen Qu;Zaiyou Yang;Li Ma;Yuliang Jiang; 《Quality and Reliability Engineering International》2024,40(1):605-618
In this paper, a novel model is proposed for the reliability analysis of systems subjected to dependent competing failure processes at random cycle times. The model takes into account the effect of random cycle time on degradation rate and hard failure threshold. Random cycle time is the time required for the system to complete a run. With the continuous operation of the system in a period of cycle time, the degradation rate of the system is accelerated, and its resistance to random shocks is decreased, so the degradation rate and hard failure threshold are supposed to vary with the number of cycles. When the overall degradation exceeds the soft failure threshold, soft failure is triggered. When the shock magnitude is larger than the hard failure threshold, hard failure occurs. Combined with the stress-strength interference model, the reliability function of the system is derived. Finally, a Micro-Electro-Mechanical System is used to verify the validity of the proposed model. The validity of the model is demonstrated by sensitivity analysis. 相似文献
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Hyunju Lee Ji Hwan Cha Gianpaolo Pulcini 《Quality and Reliability Engineering International》2017,33(7):1455-1473
In this study, we propose a new class of flexible bivariate distributions for discrete random variables. The proposed class of distribution is based on the notion of conditional failure rate for a discrete‐type random variable. We derive general formulae for the joint distributions belonging to the proposed class that, unlike other discrete bivariate models already proposed in the literature such as the well‐known and most popular Holgate's bivariate Poisson distribution, can model both positive and negative dependence. We discuss general statistical properties of the proposed class as well. Specific families of bivariate distributions can be generated from the general class proposed in this paper just by specifying the ‘baseline distributions’. Furthermore, specific discrete bivariate distributions belonging to the proposed class are applied to analyze three real data sets, and the results are compared with those obtained from conventional models. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献