In the back-end process of mask manufacturing, AIMS™ plays a crucial role to evaluate defect printing and verify the results of repair. Comparing the difference of luminous intensity between defect and reference regions, the influence of defect could be taken into control accurately. Nevertheless, providing reference images for computation would be a tough task while performing on single die photomasks. Hence, we have developed a methodology for reference searching which take advantage of the pattern matching function in Smart-MRC. By setting up criteria with results of pattern matching, identical or extremely similar reference locations would be point out. It is more dependable and efficient than manual operation on the whole mask. With this Mask Data Preparation technique, the workflow of back-end process becomes smoothly, and the quality of photomask can be guarantee.
Mask Data Preparation, MDP contains comprehensive contents such as reticle layout, mask fracturing, manufacture rule check, etc. We have demonstrated a MDP application on KLA DB inspection. In order to calculate the rendering compensation, Pre-Swath Calibration, PSC is performed before DB inspection. We have built a rule on PSC point searching function which combines the density function of Smart MRC with algorithm. The result shows that this function could save the PSC selection time and also improvement the fail rate of PSC selection. A well-prepared inspection recipe could be done by automation tool. Therefore, the setup time on DB inspection could be minimized, also could save inspection resource as well.
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