	US 12,111,355 B2
	Semiconductor substrate yield prediction based on spectra data from multiple substrate dies
Xin Song, Andover, MA (US); and Jian Lu, Chelmsford, MA (US)
Assigned to ONTO INNOVATION INC., Wilmington, MA (US)
Filed by Onto Innovation Inc., Wilmington, MA (US)
Filed on Nov. 22, 2021, as Appl. No. 17/532,700.
Prior Publication US 2023/0160960 A1, May 25, 2023
Int. Cl. G01R 31/3185 (2006.01); G01R 1/073 (2006.01); G01R 31/26 (2020.01); G01R 31/28 (2006.01); G06F 30/00 (2020.01); H01L 21/66 (2006.01)

CPC G01R 31/318511 (2013.01) [G01R 31/2642 (2013.01); G01R 31/2831 (2013.01); G01R 31/2886 (2013.01); H01L 22/14 (2013.01); G01R 1/07342 (2013.01); G06F 30/00 (2020.01); H01L 22/34 (2013.01); H01L 2924/00 (2013.01); H01L 2924/0002 (2013.01)]

28 Claims

1. A method for predicting yield of a substrate, the method comprising:

combining first spectra data for a first die of a plurality of dies on the substrate and second spectra data for the first die of the plurality of dies on the substrate into combined data, the first spectra data for the first die being generated from a first inspection of only the first die of the plurality of dies at a first time, the second spectra data for the first die being generated from a second inspection of only the first die of the plurality of dies at a second time, the second time being different from the first time; and

generating, based on the combined data, a predicted yield for the substrate, including providing the combined data as input to a trained machine learning model.