Evaluation of process variations on OPC model predictions

Process models have been in use for performing proximity corrections to designs for placement on lithography masks for a number of years. In order for these models to be used they must provide an adequate representation of the process while also allowing the corrections themselves to be performed in a reasonable computational time. In what is becoming standard Optical Proximity Correction (OPC), the models used have a largely physical optical model combined with a largely empirical resist model. Normally, wafer data is collected and fit to a model form that is found to be suitable through experience. Certain process variables are considered carefully in the calibration process-such as exposure dose and defocus - while other variables-such film thickness and optical parameter variations are often not considered. As the semiconductor industry continues to march toward smaller and smaller dimensions-with smaller tolerance to errorwe must consider the importance of those process variations. In the present work we describe the results of experiments performed in simulations to examine the importance of many of those process variables which are often regarded as fixed. We show examples of the relative importance of the different variables.