Reducing the overkills and retests in wafer testing process

S. Horng, S. Lin, M.H. Cheng, F. Yang, C.H. Liu, W. Lee, C. Tsai
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引用次数: 4

Abstract

Reducing overkills is one of the main objectives in the wafer testing process, however the major mean to prevent overkills is retest. In this paper, we formulate the problem of reducing overkills and retests as a stochastic optimization problem to determine optimal threshold values concerning the number of good dies and the number of bins in a lot and wafer to decide whether to go for a retest after a regular wafer probing. The considered stochastic optimization problem is an NP hard problem. We propose an Ordinal Optimization theory based two-level method to solve the problem for good enough threshold values to achieve lesser overkills and retests within a reasonable computational time. Applying to a case based on the true mean of bins of a real semiconductor product, the threshold values we obtained are the best among 1000 sets of randomly generated threshold values in the sense of lesser overkills under a tolerable retest rate.
减少晶圆测试过程中的重复测试
减少过量是晶圆测试过程中的主要目标之一,但防止过量的主要手段是重新测试。在本文中,我们将减少过量和复试的问题表述为一个随机优化问题,以确定在常规晶圆探测后是否进行复试的最佳阈值,该阈值与批次和晶圆中好模的数量和箱的数量有关。所考虑的随机优化问题是一个NP困难问题。我们提出了一种基于有序优化理论的两级方法来解决足够好的阈值问题,以在合理的计算时间内实现较少的过量和重复测试。应用于基于实际半导体产品箱体真实均值的案例,在可容忍的复测率下,我们得到的阈值在1000组随机生成的阈值中是最好的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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