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Survey of recent advanced statistical models for early life failure probability assessment in semiconductor manufacturing

机译:用于半导体制造中早期失效概率评估的最新高级统计模型的调查

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In semiconductor manufacturing, early life failures have to be screened out before delivery. This is achieved by means of burn-in. With the aim to prove a target reliability level and release burn-in testing of the whole population, a burn-in study is performed, in which a large number of items is investigated for early life failures. However, from a statistical point of view, there is substantial potential for improvement with respect to the modeling of early life failure probabilities by considering further available information in addition to the performed burn-in studies. In this paper, we provide ideas on how advanced statistics can be applied to efficiently reduce the efforts of burn-in studies. These ideas involve scaling the failure probability with respect to the sizes of the different products, as well as taking advantage of synergies between different chip technologies within the estimation of the chips' failure probability level.
机译:在半导体制造中,必须在交付之前筛选出早期使用寿命方面的故障。这是通过老化来实现的。为了证明目标可靠性水平并发布整个人群的老化测试,我们进行了老化研究,其中对许多项目进行了研究,以了解其早期寿命失败的原因。但是,从统计学的角度来看,通过进行除老化试验之外的其他信息,在早期寿命失效概率的建模方面还有很大的改进潜力。在本文中,我们提供了有关如何应用高级统计信息以有效减少老化研究工作的想法。这些想法涉及相对于不同产品的尺寸来缩放故障概率,以及在估计芯片故障概率水平的过程中利用不同芯片技术之间的协同作用。

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