公开(公告)号：WO2021081213A1

公开(公告)日：2021-04-29

申请号：PCT/US2020/056876

申请日：2020-10-22

Applicant: LAM RESEARCH CORPORATION

Inventor： SAWLANI, Kapil Umesh ,  BASU, Atashi ,  FRIED, David Michael ,  DANEK, Michal ,  ALDEN, Emily Ann

IPC: G06F30/33 ,  H01L21/768 ,  G06N20/00 ,  G06F115/08 ,  G06F119/18

Abstract: Methods, systems, and computer programs are presented for determining the recipe for manufacturing a semiconductor with the use of machine learning (ML) to accelerate the definition of recipes. One general aspect includes a method that includes an operation for performing experiments for processing a component, each experiment controlled by a recipe, from a set of recipes, that identifies parameters for manufacturing equipment. The method further includes an operation for performing virtual simulations for processing the component, each simulation controlled by one recipe from the set of recipes. An ML model is obtained by training an ML algorithm using experiment results and virtual results from the virtual simulations. The method further includes operations for receiving specifications for a desired processing of the component, and creating, by the ML model, a new recipe for processing the component based on the specifications.

公开(公告)号：WO2021154747A1

公开(公告)日：2021-08-05

申请号：PCT/US2021/015121

申请日：2021-01-26

Applicant: LAM RESEARCH CORPORATION

Inventor： SAWLANI, Kapil Umesh ,  DANEK, Michal ,  VELLANKI, Ravi ,  GOPINATH, Sanjay ,  COHEN, David G. ,  ROHAM, Sassan ,  SRIRAMAN, Saravanapriyan ,  HASKELL, Benjamin Allen ,  BROGAN, Lee J.

IPC: H01L21/66 ,  G05B15/02 ,  G05B17/02 ,  G06N20/00

Abstract: Methods, systems, and computer programs are presented for predicting the performance of semiconductor manufacturing equipment operations. One method includes an operation for obtaining machine-learning (ML) models, each model related to predicting a performance metric for an operation of a semiconductor manufacturing tool. Further, each ML model utilizes features defining inputs for the ML model. The method further includes an operation for receiving a process definition for manufacturing a product with the semiconductor manufacturing tool. One or more ML models are utilized to estimate a performance of the process definition used in the semiconductor manufacturing tool. Additionally, the method includes presenting, on a display, results showing the estimate of the performance of the manufacturing of the product. In some aspects, the use of hybrid models improves the predictive accuracy of the system by augmenting the capabilities of data-driven models with the reinforcement provided by the physics-based models.