| 摘要(英) |
Under the process variation, the yield of the chips which are at the different locations with different characterization is in the same wafer. With the entry of the nanometer era, the wafer defect patterns become more various. The easiest way to observe these defect patterns due to process variation is from the viewpoint of the wafer map. In previous research, we use the Poisson distribution model to generate and analyze the homogeneous random defect wafer map. In this paper, we use the Bat-wing model to generate the nonhomogeneous random defect wafer map and calculate the distance between the wafer center and every bad die, then we can get the mean (DistanceMean) and the standard deviation (DistanceSTD) of the distance.
Next, we use the actual wafer map data, which is the WM-811K wafer database released by TSMC to calculate DistanceMean and DistanceSTD. The ring partition is based on these two parameters. The wafer map is partitioned into three zones which are out-ring, inner-ring, and circle. The size of the three zones is dynamic due to the difference between the number and the distribution of bad die. Afterward, we calculate the ratio of the bad die and the defective rate of each zone. We analyze and use these parameters to help us classify the nine failure patterns which are Center, Donut, Scratch, Edge-Ring, Edge-Loc, Loc, Near-full, Random, none. |
| 參考文獻 |
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