Sequential Screening in Semiconductor Manufacturing

Cover Sequential Screening in Semiconductor Manufacturing
Sequential Screening in Semiconductor Manufacturing
Jihong Ou
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Numerical results are reported in Section 5. Concluding remarks on this paper and Longtin et al. Can be found in Section 7 of the latter paper.
1. The Yield Model and Industrial Data Our yield model assumes that the number of defective chips on each wafer in a given lot is an independent gamma random variable with shape parameter q and scale parameter J. An empirical Bayes approach is used, where the shape parameter q is the same for all lots but the scale parameter J varies from lot to lot: fo
...r each lot. The value of the parameter J is chosen independently from a gamma prior distribution with known parameters a and h. The two gamma distributions form a conjugate pair, if the parameter J has a gamma ia. B) distribution prior to testing a wafer, and if . R chips on the wafer are found to be defective, then 3 has a gamma (a + a, b + x) posterior distribution.
Figure 1 Die Yields of 11 Batches from Factory CI 1 1 i 1 1 1 1 1 i 1 1 HO . 1: .
S - . . . Li P r 1 ^ «» ^ ! f }. U - • ' - ;.


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