A new framework for electronic assembly/system reliability prediction

K. Wong
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引用次数: 1

Abstract

The inaccuracies of existing reliability prediction methods necessitate a fresh look at the methodology. At least 3 papers appeared in 1995 proposing new approaches for reliability prediction. A new framework for the prediction of part failure rates was published in the March IEEE Trans. Reliability 1995. Still lacking is an approach to bridge the gap between the part failure rates and the system probability of success. This paper presents a reliability prediction framework for assembly/system levels using predicted part failure rates as the takeoff point. Multipliers and environmental stress screening (ESS) times are used to modify part failure rates to give assembly/system failure rates. These multipliers reflect the influences of parts/assemblies interactions, learning curve effects, user malfunction tolerance, repair effectiveness, and management priority on maintenance. The ESS times manifest themselves as time shifts in the equations. Avionic system failure data show that avionic failure rates tend to be higher at the early part of a mission. A mission-time related multiplier is used to modify the standard survival function to give the final probability of system success. If data are available for quantifying the multipliers, the reliability practitioner should use them within this framework immediately. If data are not available one must begin to accumulate the information so that reliability predictions at the assembly/system level can be improved.
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电子装配/系统可靠性预测的新框架
现有可靠性预测方法的不准确性要求我们重新审视可靠性预测方法。1995年至少有3篇论文提出了可靠性预测的新方法。一个预测零件故障率的新框架发表在3月的IEEE Trans上。1995年的可靠性。仍然缺乏一种方法来弥合零件故障率和系统成功概率之间的差距。本文提出了一个以零件故障率预测为出发点的装配/系统级可靠性预测框架。乘数和环境应力筛选(ESS)时间用于修改零件故障率,以给出装配/系统故障率。这些乘数反映了零件/组件交互、学习曲线效应、用户故障容忍度、维修效率和维护管理优先级的影响。ESS时间在方程中表现为时移。航空电子系统故障数据表明,在任务的早期,航空电子系统的故障率往往更高。使用任务时间相关乘数来修改标准生存函数以给出系统成功的最终概率。如果数据可用于量化乘数,可靠性实践者应立即在此框架内使用它们。如果没有可用的数据,则必须开始积累信息,以便改进装配/系统级别的可靠性预测。
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