US 12,072,689 B2
Model-based scheduling for substrate processing systems
Raymond Chau, San Ramon, CA (US); Chung-Ho Huang, San Jose, CA (US); Henry Chan, Morgan Hill, CA (US); Vincent Wong, Fremont, CA (US); Yu Ding, Los Altos, CA (US); Ngoc-Diep Nguyen, Portland, OR (US); and Gerramine Manuguid, Lake Oswego, OR (US)
Assigned to LAM RESEARCH CORPORATION, Fremont, CA (US)
Appl. No. 17/442,517
Filed by LAM RESEARCH CORPORATION, Fremont, CA (US)
PCT Filed Mar. 24, 2020, PCT No. PCT/US2020/024478
§ 371(c)(1), (2) Date Sep. 23, 2021,
PCT Pub. No. WO2020/205339, PCT Pub. Date Oct. 8, 2020.
Claims priority of provisional application 62/826,185, filed on Mar. 29, 2019.
Prior Publication US 2022/0171373 A1, Jun. 2, 2022
Int. Cl. G05B 19/418 (2006.01); C23C 14/54 (2006.01); C23C 16/52 (2006.01); H01J 37/32 (2006.01)
CPC G05B 19/41865 (2013.01) [C23C 14/54 (2013.01); C23C 16/52 (2013.01); G05B 19/41885 (2013.01); H01J 37/32926 (2013.01); G05B 2219/39001 (2013.01); G05B 2219/45031 (2013.01); G05B 2219/45212 (2013.01); H01J 2237/334 (2013.01)] 55 Claims
OG exemplary drawing
 
1. A system for processing semiconductor substrates in a tool comprising a plurality of processing chambers configured to process the semiconductor substrates according to a recipe, the system comprising:
a processor; and
non-transitory memory storing instructions for execution by the processor, wherein the instructions are configured to:
receive first data from the tool regarding processing of the semiconductor substrates in the plurality of processing chambers according to the recipe;
receive second data regarding a configuration of the tool and the recipe;
simulate, using the second data, a plurality of processing scenarios and scheduling parameters for the plurality of processing scenarios for processing the semiconductor substrates in the plurality of processing chambers according to the recipe;
simulate the processing of the semiconductor substrates in the plurality of processing chambers according to the recipe using the plurality of processing scenarios and the scheduling parameters for the plurality of processing scenarios;
train a model using the first data and data generated by the simulation to predict optimum scheduling parameters for processing the semiconductor substrates in the plurality of processing chambers according to the recipe;
receive inputs from the tool regarding processing of one of the semiconductor substrates in the plurality of processing chambers according to the recipe;
predict based on the inputs, using the model, optimum scheduling parameters for processing the one of the semiconductor substrates in the plurality of processing chambers according to the recipe; and
schedule operations of the tool based on the optimum scheduling parameters for processing the one of the semiconductor substrates in the plurality of processing chambers according to the recipe.