Wafer sort bitmap data analysis using the PCA-based approach for yield analysis and optimization

Yeou Lang Hsieh*, Gwo Hshiung Tzeng, Tr Lin, Hsiao Cheng Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Yield analysis is one of the most important subjects in IC companies. During the initial stage of new process development, several factors can greatly impact the yield simultaneously. Traditionally, several learning cycle iterations are required to solve yield loss issues. This paper describes a novel way to diagnose yield loss issues in less iteration. First, the failure classification of bitmap data is transferred to a new basis using principal component analysis. Second, the defective rates are calculated and the original bitmap data is reconstructed in the principal basis, allowing the yield loss space to be generated by Cluster Analysis. Third, physical failure analysis samples can be selected to solve yield loss issues. Furthermore, the new yield loss basis can be used to monitor the progress of yield improvement as a discriminate analysis measure for reducing failure patterns (bitmap failures).

Original languageEnglish
Article number3
Pages (from-to)493-502
Number of pages10
JournalIEEE Transactions on Semiconductor Manufacturing
Issue number4
StatePublished - 1 Nov 2010


  • Bitmap
  • cluster analysis
  • discriminate analysis
  • principal component analysis (PCA)
  • yield analysis
  • yield loss space

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