运行和修复同时进行的固有可用度定时截尾试验方案

针对如何设计一个试验以完成检验系统固有可用度、平均故障间隔时间和平均修复时间等3个指标参数的问题,将试验分为同时进行的可靠性和维修性定时截尾试验2个项目,假设运行时间和修复时间均服从指数分布,且可靠性和维修性试验方案已知,提出了一种固有可用度定时截尾试验方案．该试验方案通过合理选择累积运行时间和累积修复时间,同时满足检验3个指标参数的承制方和使用方风险,可完成对3个指标参数的检验．     

定时截尾与序贯截尾可靠性试验方案分析比较

在生产方、使用方风险及MTBF值同等条件下,对定时截尾与序贯截尾2种试验方案的优缺点、基本原理和方法等进行了对比分析。定时截尾试验能够在事先确定最大累计工作时间及所消耗资源,但所需时间较长,试验成本较高,可应用于武器装备可靠性鉴定和验收试验;序贯截尾试验事先对试验总时间及试验所需用资源无法确定,只能根据事先拟定的接收、拒收条件结束试验,无法估计MTBF的真值,但是所需试验时间较短,费用相对较低,可用于武器装备可靠性验收试验,也可广泛运用于医学及其它科学试验领域。提出了选择可靠性试验方案的基本原则,为科学选择试验方案提供了依据。     

指数寿命产品可靠性增长试验的Bayes分析

针对指数寿命产品的定时、定数截尾试验方案,推广了Mazzuchi-Soyer模型的应用范围。首先引入模型假设,以狄氏分布作为先验分布,综合利用产品研制的历史信息和专家信息,结合产品研制各阶段试验数据,给出了各阶段可靠性的联合后验分布。然后利用Gibbs抽样算法解决后验推断计算问题,得到各阶段产品可靠性的Bayes点估计和区间估计。最后给出产品可靠性增长分析实例,表明了模型的优越性。     

枪械可靠性试验统计方案与参数估计研究

为了提高对枪械可靠性指标试验考核的系统性,对枪械故障分布规律进行了建模研究和特征分析,说明在使用寿命内可以用指数分布来近似;以指数分布为基础,运用可靠性工程理论和数学方法,开展了枪械定时截尾和序贯截尾两类试验统计方案的研究,举例说明了各试验要素的量化确定方法;对于定时截尾试验提出了枪械可靠性要求常用特征量故障率的点估计与区间估计公式,以便于定量地把握枪械的可靠性特征;通过实例应用验证了枪械可靠性试验统计方案与参数估计方法的可行性和有效性。     

利用验前信息时，飞行器试验鉴定技术研究—— 一次现场试验下的精度鉴定方法

研究了具有验前信息下的飞行器落点精度的鉴定问题,适用于只作一次现场飞行试验的情况。文中给出了鉴定方案,并进行了风险计算和信度分析。对于一次试验结果与验前信息的一致性．给出了验证方法。本文所提供的理论方法,可用于一般武器装备系统的试验定型和鉴定。     

维修性试验验前信息融合方法

针对小子样维修性试验因数据异总体而导致验前信息融合精度低的问题,提出了基于信息可用度的验前信息折合模型,解决了因数据异总体无法融合的问题;利用随机加权法对验前分布参数进行了拟合,准确地表述了验前分布;提出了基于支持度的融合权值确定方法,提高了各验前分布融合权值分配的合理性;最后,通过某装备维修性试验验前信息融合实例,表明了该方法具有一定的工程应用价值。     

寿命型产品定数截尾可靠性鉴定试验方案研究

相对于定时截尾可靠性鉴定试验方案来说,寿命型产品定数截尾试验方案方面的研究较少。首先从理论上证明了,寿命服从指数分布的产品,无论对定数截尾试验中的故障产品是否用新产品替换,其鉴定试验方案的设计公式完全相同。之后推导出了同时能满足检验上限、检验下限、生产方风险、使用方风险要求的定数截尾鉴定试验方案设计公式,并用GB5080.7中的数据验证了公式的正确性。给出了指数寿命型产品定数截尾试验中的接收概率公式,并推论出了同一产品在不同试验方案的鉴定结果可能完全相反。最后建议,应在鉴定试验前尽可能知晓产品的可靠性水平,从而可有目的地选择或设计试验方案,以求产品高概率通过鉴定试验。     

利用验前信息的一种序贯检验方法——序贯验后加权检验方法

序贯验后加权检验方法是Bayes 统计观点在假设检验中的运用。本文提出了该方法的一般理论,给出了当总体的分布参数具有验前信息时的序贯检验方法。文中确定了决策区的划分,同时讨论了序贯截尾方案,给出了检验中可能犯两类错误的概率的上界,并将一般理论应用于产品的可靠性检验和再入飞行器随机落点的精度鉴定。由于运用了验前信息,因此能有效地在少量试验之下进行统计假设检验。本文所提供的方法对于昂贵产品试验结果的统计评定具有普遍意义。     

多源信息的验前分布融合方法研究

验前分布的获取和表示是B ayes理论应用中的一个关键问题。针对目前多源验前信息融合中存在的过分依赖专家信息的问题,提出了一种基于第2类极大似然估计原理(M L-II)确定验前分布权重的方法,该方法将现场试验数据看作是由其边缘分布产生的样本,然后根据不同验前分布下现场样本似然性的大小来确定其在验前分布融合中的作用,并以此进一步确定不同验前分布的权重因子。最后通过算例证明了该方法比基于专家信息的融合方法更为合理和有效。     

一种新的火炮武器系统射击精度试验方法

射击精度是反应火炮武器系统性能的最重要技术指标,通过对以往射击精度试验中采用的建立在大子样统计理论基础上的传统评定方法进行了分析,对目前采用的序贯截尾原理和方法进行阐述,并指出前两种方法没有利用验前信息,试验次数和试验风险比较大等缺点,由此提出一种新的贝叶斯截尾序贯检验法。这种小样本统计推断方法的基本思想是充分利用已有的验前信息,实现了多阶段试验信息的综合利用,能够减少试验次数,缩短试验周期,节约试验经费。     

Weibull型产品的可靠性验证

讨论了Weibull型产品的可靠性验证问题 ,首先分析了Weibull型产品分布参数的无信息验前分布问题 ,利用验前信息可以得到分布参数的验前概率密度函数 ,进而分析了产品的可靠性验证问题 ,顾及了使用方利益和生产方利益。仿真算例表明 ,使用方利益和生产方利益是相互折衷的。     

轻武器寿命可靠性模型研究

为轻武器寿命可靠性评定提供理论依据,运用经典的可靠性理论,将轻武器装备寿命试验归结为可修复系统的有替换定时截尾试验,通过分析某型机枪的寿命试验数据,对母体寿命可能的分布类型作出假设,选择χ2检验法对假设进行拟合优度检验,利用最小二乘法得出对应分布的线性相关系数,通过比较确定母体分布类型,建立了该型机枪寿命的可靠性数学模型,对同类轻武器装备的可靠性指标评定提供了一定的参考。     

Bayesian sampling plans for exponential distributions with interval censored samples

This article studies the problem of designing Bayesian sampling plans (BSP) with interval censored samples. First, an algorithm for deriving the conventional BSP is proposed. The BSP is shown to possess some monotonicity. Based on the BSP and using the property of monotonicity, a new sampling plan modified by the curtailment procedure is proposed. The resulting curtailed Bayesian sampling plan (CBSP) can reduce the duration time of life test experiment, and it is optimal in the sense that its associated Bayes risk is smaller than the Bayes risk of the BSP if the cost of the duration time of life test experiment is considered. A numerical example to compute the Bayes risks of BSP and CBSP and related quantities is given. Also, a Monte Carlo simulation study is performed to illustrate the performance of the CBSP compared with the BSP. The simulation results demonstrate that our proposed CBSP has better performance because it has smaller risk. The CBSP is recommended. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 604–616, 2015     

Progressive Type‐II censoring and coherent systems

A new connection between the distribution of component failure times of a coherent system and (adaptive) progressively Type‐II censored order statistics is established. Utilizing this property, we develop inferential procedures when the data is given by all component failures until system failure in two scenarios: In the case of complete information, we assume that the failed component is also observed whereas in the case of incomplete information, we have only information about the failure times but not about the components which have failed. In the first setting, we show that inferential methods for adaptive progressively Type‐II censored data can directly be applied to the problem. For incomplete information, we face the problem that the corresponding censoring plan is not observed and that the available inferential procedures depend on the knowledge of the used censoring plan. To get estimates for distributional parameters, we propose maximum likelihood estimators which can be obtained by solving the likelihood equations directly or via an Expectation‐Maximization‐algorithm type procedure. For an exponential distribution, we discuss also a linear estimator to estimate the mean. Moreover, we establish exact distributions for some estimators in the exponential case which can be used, for example, to construct exact confidence intervals. The results are illustrated by a five component bridge system. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 512–530, 2015     

Bayes sequential design of stock levels

Bayesian determination of optimal stock levels is studied for the case of Poisson distribution of the demand variable, and prior gamma distribution of the expected demand. Bayes sequential procedure is derived, assuming that stock level can be adjusted at the beginning of each period so that a shortage can be immediately replenished and an overstock can be corrected. The Bayes sequential procedure is more difficult to obtain if this assumption is removed. A dynamic programming method for obtaining the general Bayes sequential procedure is outlined. Finally, an empiric Bayes estimation procedure of the optimal Bayesian stock level is presented.     

Statistical analysis for masked system life data from Marshall‐Olkin Weibull distribution under progressive hybrid censoring

This paper considers the statistical analysis of masked data in a series system, where the components are assumed to have Marshall‐Olkin Weibull distribution. Based on type‐I progressive hybrid censored and masked data, we derive the maximum likelihood estimates, approximate confidence intervals, and bootstrap confidence intervals of unknown parameters. As the maximum likelihood estimate does not exist for small sample size, Gibbs sampling is used to obtain the Bayesian estimates and Monte Carlo method is employed to construct the credible intervals based on Jefferys prior with partial information. Numerical simulations are performed to compare the performances of the proposed methods and one data set is analyzed.     

Bayesian inference based on partial monitoring of components with applications to preventive system maintenance

Consider a binary, monotone system of n components. The assessment of the parameter vector, θ, of the joint distribution of the lifetimes of the components and hence of the reliability of the system is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often of importance and can indeed conveniently be incorporated by the Bayesian approach. It may also be important to continuously extract information from a system currently in operation. This may be useful both for decisions concerning the system in operation as well as for decisions improving the components or changing the design of similar new systems. As in Meilijson [12], life‐monitoring of some components and conditional life‐monitoring of some others is considered. In addition to data arising from this monitoring scheme, so‐called autopsy data are observed, if not censored. The probabilistic structure underlying this kind of data is described, and basic likelihood formulae are arrived at. A thorough discussion of an important aspect of this probabilistic structure, the inspection strategy, is given. Based on a version of this strategy a procedure for preventive system maintenance is developed and a detailed application to a network system presented. All the way a Bayesian approach to estimation of θ is applied. For the special case where components are conditionally independent given θ with exponentially distributed lifetimes it is shown that the weighted sum of products of generalized gamma distributions, as introduced in Gåsemyr and Natvig [7], is the conjugate prior for θ. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 551–577, 2001.