Suppr超能文献

适用于逆高斯退化过程项目的变量验收可靠性抽样方案。

Variables acceptance reliability sampling plan for items subject to inverse Gaussian degradation process.

作者信息

Cha Ji Hwan, Badía F G

机构信息

Department of Statistics, Ewha Womans University, Seoul, Republic of Korea.

Department of Statistical Methods, University of Zaragoza, Zaragoza, Spain.

出版信息

J Appl Stat. 2020 Feb 7;48(3):393-409. doi: 10.1080/02664763.2020.1723505. eCollection 2021.

Abstract

Until now, in the literature, a variety of acceptance reliability sampling plans have been developed based on different life test plans. In most of the reliability sampling plans, the decision procedures to accept or reject the corresponding lot are developed based on the lifetimes of the items observed on tests, or the number of failures observed during a pre-specified testing time. However, frequently, the items are subject to degradation phenomena and, in these cases, the observed degradation level of the item can be used as a decision statistic. In this paper, we develop a variables acceptance sampling plan based on the information on the degradation process of the items, assuming that the degradation process follows the inverse Gaussian process. It is shown that the developed sampling plan improves the reliability performance of the items conditional on the acceptance in the test and that the lifetimes of items after the reliability sampling test are stochastically larger than those before the test. A study comparing the proposed degradation-based sampling plan with the conventional sampling plan which is based on a life test is also performed.

摘要

到目前为止,在文献中,已经基于不同的寿命测试计划开发了各种验收可靠性抽样方案。在大多数可靠性抽样方案中,接受或拒绝相应批次的决策程序是基于测试中观察到的项目寿命,或者在预先指定的测试时间内观察到的故障数量来制定的。然而,通常情况下,项目会出现退化现象,在这些情况下,观察到的项目退化水平可以用作决策统计量。在本文中,我们基于项目退化过程的信息开发了一种变量验收抽样方案,假设退化过程遵循逆高斯过程。结果表明,所开发的抽样方案在测试中接受的条件下提高了项目的可靠性性能,并且可靠性抽样测试后项目的寿命在统计上大于测试前的寿命。还进行了一项研究,将所提出的基于退化的抽样方案与基于寿命测试的传统抽样方案进行比较。

相似文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验