Wafer Sort Bitmap Data Analysis Using the PCA-Based Approach for Yield Analysis and Optimization

被引:7
|
作者
Hsieh, Yeou-lang [1 ,2 ]
Tzeng, Gwo-hshiung [1 ]
Lin, T. R. [1 ]
Yu, Hsiao-cheng [1 ]
机构
[1] Natl Chiao Tung Univ, Inst Management Technol, Hsinchu 300, Taiwan
[2] Taiwan Semicond Mfg Co, Customer Tech Supporting Div, Hsinchu 300, Taiwan
关键词
Bitmap; cluster analysis; discriminate analysis; principal component analysis (PCA); yield analysis; yield loss space; COMPONENTS;
D O I
10.1109/TSM.2010.2065510
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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).
引用
收藏
页码:493 / 502
页数:10
相关论文
共 50 条
  • [41] A multivariate normal boundary intersection PCA-based approach to reduce dimensionality in optimization problems for LBM process
    Gabriela Belinato
    Fabrício Alves de Almeida
    Anderson Paulo de Paiva
    José Henrique de Freitas Gomes
    Pedro Paulo Balestrassi
    Pedro Alexandre Rodrigues Carvalho Rosa
    Engineering with Computers, 2019, 35 : 1533 - 1544
  • [42] Improving PCA-based anomaly detection by using multiple time scale analysis and Kullback-Leibler divergence
    Callegari, Christian
    Gazzarrini, Loris
    Giordano, Stefano
    Pagano, Michele
    Pepe, Teresa
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2014, 27 (10) : 1731 - 1751
  • [43] A new LPV modeling approach using PCA-based parameter set mapping to design a PSS
    Jabali, Mohammad B. Abolhasani
    Kazemi, Mohammad H.
    JOURNAL OF ADVANCED RESEARCH, 2017, 8 (01) : 23 - 32
  • [44] Mapping disturbance in mangrove ecosystems: Incorporating landscape metrics and PCA-based spatial analysis
    Toosi, Neda Bihamta
    Soffianian, Ali Reza
    Fakheran, Sima
    Waser, Lars T.
    ECOLOGICAL INDICATORS, 2022, 136
  • [45] PCA-Based Multiple-Trait GWAS Analysis: A Powerful Model for Exploring Pleiotropy
    Zhang, Wengang
    Gao, Xue
    Shi, Xinping
    Zhu, Bo
    Wang, Zezhao
    Gao, Huijiang
    Xu, Lingyang
    Zhang, Lupei
    Li, Junya
    Chen, Yan
    ANIMALS, 2018, 8 (12):
  • [46] An Analysis of PCA-based Vocal Entrainment Measures in Married Couples' Affective Spoken Interactions
    Lee, Chi-Chun
    Katsamanis, Athanasios
    Black, Matthew P.
    Baucom, Brian R.
    Georgiou, Panayiotis G.
    Narayanan, Shrikanth S.
    12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5, 2011, : 3108 - +
  • [47] A Supervised Learning Framework for PCA-based Face Recognition using GNP Fuzzy Data Mining
    Zhang, Deng
    Mabu, Shingo
    Wen, Feng
    Hirasawa, Kotaro
    2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2011, : 516 - 520
  • [48] Data assimilation and uncertainty assessment for complex geological models using a new PCA-based parameterization
    Hai X. Vo
    Louis J. Durlofsky
    Computational Geosciences, 2015, 19 : 747 - 767
  • [49] Quantitative analysis on PCA-based statistical 3D face shape modeling
    Maghari, A. Y. A.
    Liao, I. Yi
    Belaton, B.
    COMPUTATIONAL MODELLING OF OBJECTS REPRESENTED IN IMAGES: FUNDAMENTALS, METHODS AND APPLICATIONS III, 2012, : 13 - 18
  • [50] Extreme flash flood susceptibility mapping using a novel PCA-based model stacking approach
    Shojaeian, Amirreza
    Shafizadeh-Moghadam, Hossein
    Sharafati, Ahmad
    Shahabi, Himan
    ADVANCES IN SPACE RESEARCH, 2024, 74 (11) : 5371 - 5382