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A combinatorial estimation approach for storage reliability with initial failures based on periodic testing data

机译:基于定期测试数据的具有初始故障的存储可靠性的组合估计方法

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Storage reliability that measures the ability of products in a dormant state to keep their required functions is studied in this paper. Unlike the operational reliability, storage reliability for certain types of products may not be always 100% at the beginning of storage since there are existing possible initial failures that are normally neglected in the models of storage reliability. In this paper, a new combinatorial approach, the nonparametric measure for the estimates of the number of failed products and the current reliability at each testing time in storage, and the parametric measure for the estimates of the initial reliability and the failure rate based on the exponential reliability function, is proposed for estimating and predicting the storage reliability with possible initial failures. The proposed method has taken into consideration that the initial failure and the reliability testing data, before and during the storage process, are available for providing more accurate estimates of both initial failure probability and the probability of storage failures. When storage reliability prediction that is the main concern in this field should be made, the nonparametric estimates of failure numbers can be used into the parametric models for the failure process in storage. In the case of exponential models, the assessment and prediction method for storage reliability is provided in this paper. Finally, numerical examples are given to illustrate the method. Furthermore, a detailed comparison between the proposed method and the traditional method, for examining the rationality of assessment and prediction on the storage reliability, is presented. The results should be useful for planning a storage environment, decision-making concerning the maximum length of storage, and identifying the production quality.
机译:本文研究了衡量产品在休眠状态下保持其所需功能的能力的存储可靠性。与操作可靠性不同,某些类型产品的存储可靠性在存储开始之初并不总是100%,因为存在可能存在的初始故障,而这些故障通常在存储可靠性模型中被忽略。本文提出了一种新的组合方法,即在存储的每个测试时间对失效产品数量和当前可靠性进行估计的非参数度量,以及基于可靠性的初始可靠性和失效率评估的参数度量。提出了指数可靠性函数,用于估计和预测可能出现初始故障的存储可靠性。所提出的方法已经考虑到初始故障和可靠性测试数据在存储过程之前和期间可用于提供初始故障概率和存储故障概率的更准确的估计。在进行存储可靠性预测(这是该领域的主要关注点)时,可以将故障数量的非参数估计值用于存储过程中故障过程的参数模型。在指数模型的情况下,本文提供了存储可靠性的评估和预测方法。最后,通过数值算例说明了该方法。此外,提出的方法与传统方法之间进行了详细的比较,以检验存储可靠性评估和预测的合理性。结果对于计划存储环境,有关最大存储时间的决策以及确定生产质量应该是有用的。

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