Sequential Screening in Semiconductor Manufacturing
Sequential Screening in Semiconductor Manufacturing
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In our eReader you can find the full English version of the book. Read Sequential Screening in Semiconductor Manufacturing Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Sequential Screening in Semiconductor Manufacturing
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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 - • ' - ;.
What to read after Sequential Screening in Semiconductor Manufacturing?
You can find similar books in the "Read Also" column, or choose other free books by Jihong Ou to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
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 - • ' - ;.
What to read after Sequential Screening in Semiconductor Manufacturing?
You can find similar books in the "Read Also" column, or choose other free books by Jihong Ou to read onlineMoreLess
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