Skip to main content
SpringerLink
Log in

Development of a new cluster index for wafer defects

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Defect number and defect clustering are two key determinants of wafer yield. Preventing and detecting wafer defects thus is an important issue in integrated circuit manufacturing. Defect clustering tends to grow with increasing wafer size. Methods have been developed for assessing defect clustering on wafers. However, these methods require either statistical assumptions regarding defect distribution or complex computations. This study develops a new cluster index, utilizing the rotating axis technique from multivariate analysis to accurately quantify defect clusters on a wafer. The developed defect-clustering index does not require making assumptions regarding defect distribution. Thus, the proposed method can be efficiently used by engineers with little statistical background. A simulation experiment is conducted to demonstrate the effectiveness of the proposed defect-clustering index.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Cunningham JA (1990) The use and evaluation of yield models in integrated circuit manufacturing. IEEE T Semiconduct M 3(2):60–71

    Article  MathSciNet  Google Scholar 

  2. Friedman DJ, Hansen MH, Nair VN, James DA (1997) Model-free estimation of defect clustering in integrated circuit fabrication. IEEE T Semiconduct M 10(3):344–359

    Article  Google Scholar 

  3. Jun CH, Hong Y, Kim SY, Park KS, Park H (1999) A simulation-based semiconductor chip yield model incorporating a new defect cluster index. Microelectron Reliab 39:451–456

    Article  Google Scholar 

  4. Rogers A (1974) Statistical analysis of spatial dispersion: the quadrat method. Pion, London

    Google Scholar 

  5. Raghavachari M, Srinivasan A, Sullo P (1997) Poisson mixture yield models for integrated circuits: a critical review. Microelectron Reliab 37(4):565–580

    Article  Google Scholar 

  6. Stapper CH (1973) Defect density distribution for LSI yield calculations. IEEE Trans Electron Dev ED-20:655–657

    Google Scholar 

  7. Sharma S (1996) Applied multivariate techniques. Wiley, New York

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering and Management, National Chiao Tung University, HsinChu, Taiwan-Republic of China

    Lee-Ing Tong

  2. Department of Computer Science, Chung Cheng Institute of Technology, National Defense University, Taoyuan, Taiwan-Republic of China

    Chung-Ho Wang

  3. Total Quality Management Committe, United Microelectronic Corporation, HsinChu, Taiwan-Republic of China

    Da-Lun Chen

Authors
  1. Lee-Ing Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chung-Ho Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Da-Lun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chung-Ho Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tong, LI., Wang, CH. & Chen, DL. Development of a new cluster index for wafer defects. Int J Adv Manuf Technol 31, 705–715 (2007). https://doi.org/10.1007/s00170-005-0240-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-005-0240-5

Keywords

Search

Navigation