基于临界相关相似性分析的可靠性预测

A. Jackson, A. K. Jain, T. Jackson
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引用次数: 0

摘要

在本文中,作者描述了一种他们称之为临界相关相似性分析(CASA)的方法,该方法通过应用以下基于经验的猜想系统地开发可靠性预测:新产品(即从未投入使用的产品)的预测可靠性与证明可靠性的比率等于对其预测可靠性和证明可靠性进行了调整以反映新产品的所有故障和潜行模式、机制和根本原因的类似在役产品的相应比率。当新设计的电子设备与已证明可靠的现役电子设备足够相似时,CASA方法是实用和有效的。该方法的应用将得到比传统可靠性预测方法更精确的可靠性预测结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliability predictions based on criticality-associated similarity analysis
In this paper, the authors describe a methodology that they call criticality-associated similarity analysis (CASA), which systematically develops a reliability prediction by applying the following empirical-based conjecture: the ratio of predicted to demonstrated reliability for a new product (i.e., a product that has never been placed in-service) is equal to the corresponding ratio for a similar in-service product that has both its predicted and demonstrated reliabilities adjusted to reflect all the failure and sneak modes, mechanisms, and root causes of the new product. The CASA methodology is practical and efficient when there is newly designed electronics equipment that is sufficiently similar to in-service electronics equipment that has a demonstrated reliability. The application of this methodology will result in a reliability prediction that is more precise than those obtained by using traditional reliability prediction methodologies.
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