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Novel Technique to Separate Systematic and Random Defects During...

建立日期：2018/02/21
  • 作者： Allen Park
  • 出處： KLA –Tencor Corporation, 1 Technology Drive, Milpitas CA 95035, USA
  • 內容： Defect inspections performed during process development often result in 105 to 106 defect counts on a single wafer. Such defect data include both systematic and random defects, only some of which may be yield-limiting. The traditional method of reviewing a random sample of only 50 to 100 defects on the SEM makes it difficult to identify important systematic defects from a defect wafer map.
    This paper describes a powerful new method to discover and separate systematic defects within a large defect sample, prior to SEM review. By integrating design data with defect data, this method enabled us, for the first time, to accurately bin randomly distributed structural systematic defects using the design background.
    Instead of relying on inefficient random review sampling to identify defects of interest (DOI), our technique applied a pattern search engine accessing the design files to correlate the DOI to its pattern background. It was able to group defects occurring within the context of a particular pattern, independent of their spatial distribution. Based on this approach we have identified numerous systematic defects including a residue defect that is described as an example in this paper. Once identified, spatial pattern can be better visualized via use of wafer map and the severity of particular defect type can be understood via resulting pareto chart.
    By comparing the results against the design layout, specific failure locations in the design were confirmed. Then, the defect types were further confirmed using SEM and FIB. This novel binning technique allowed users to quantify systematic defect types quickly and efficiently from wafer maps that consist of random and systematic defects, and the analysis enabled users to take prompt corrective action.
  • 檔案下載：Novel Technique to Separate Systematic and Random
  • 下載次數：673
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