The invention provides an
optical proximity correction method and
system based on
mask error model optimization, and a terminal, and the method comprises the steps: building a data sample set containing a plurality of
process conditions through obtaining a large amount of
mask manufacturing data under a specific photoetching process; and based on the sample set, constructing a physical optical sub-model and a
machine learning sub-model to form a
mask error model for outputting a final mask
key size value. And then, according to a plurality of preset alternative
weight coefficient combinations, reconstructing an objective function which introduces a mask error term, calculating corresponding objective function values, and correcting the photoetching pattern by using an OPC
algorithm corresponding to each objective function value to obtain
performance index data so as to determine an
optimal weight coefficient combination. And finally, optimizing the OPC
algorithm by using the target function of the
optimal combination, thereby realizing the accurate correction of the photoetching pattern, and improving the precision and yield of
semiconductor manufacturing. According to the method, the mask error model comprehensively considering
physical optics and
machine learning is established, and the OPC process is introduced, so that the influence of the mask error can be predicted and compensated more accurately, the
critical dimension deviation and the like are reduced, and the device performance and the yield are improved. The method can adapt to different
process conditions, and parameters and weight coefficients can be dynamically adjusted. And moreover,
rework can be reduced, automatic adjustment is realized through closed-loop
feedback control, the production stability and efficiency are improved, and the cost is reduced.