| 摘要(英) |
In this paper, we use Boomerang Chart that we published in the past to analyze the classified wafer maps in a great view, whether the distribution of defects uniform or not and verify it in mass production.
At first, we choose several kinds of size of wafers that we would like to analyze, and simulate basic curve according to these several kinds of size. In this experiment, we will create parameters NBD and NCD from every wafer in every data, and normalize the two parameters to create two new parameters, NNBD and NNCD. We will get the standard deviation according to the two parameters and compare with basic standard deviation to observe every failure type’s on the change in value, we will judge whether a wafer uniform or not and the situation of clustering of bad dice by this. Then, we will view whether there are systematic errors in non-classified data based on the result.
In this experiment, we use the relationship between standard deviation and normal distribution , To identify whether the system is a systematic error type by observing the feature value , and find out the position and the situation of clustering of every failure type by observing Z-Score. Finally confirm the practicability of Z-Score through non-classified data set to get the achievement of increasing yield、testing efficiency and reduce the production cost. |
| 參考文獻 |
參考文獻
[1] Jwu-E Chen, Mill-Jer Wang, Yen-Shung Chang, Shaw Cherng Shyu, and
Yung-Yuan Chen, “ Yield Improvement by Test Error Cancellation ”, in Test
Symposium (ATS), pp.258-260, Nov. 1996.
[2] C. - K. Hsu, Lin, F., Cheng, K. - T. Tim, Zhang, W., Li, X., Carulli, J. M., and
Butler, K. M., “Test data analytics - Exploring spatial and test-item correlations
in production test data”, in Test Conference (ITC), pp.1-10, Sep. 2013.
[3] Ming-Ju Wu, Jyh-Shing Roger Jang, and Jui-Long Chen, “Wafer Map Failure
Pattern Recognition and Similarity Ranking for Large-scale Datasets”, IEEE
Transactions on Semiconductor Manufacturing, vol.28, no.1, pp.1-12, Feb. 2015.
[4] S. Zhang, Lin, F., Hsu, C. - K., Cheng, K. - T. Tim, and Wang, H., “Joint Virtual
Probe: Joint exploration of multiple test items′ spatial patterns for efficient silicon characterization and test prediction”, in Design, Automation and Test in Europe Conference and Exhibition (DATE), pp.1-6, Mar. 2014.
[5] F. Lin, Hsu, C. - K., and Cheng, K. - T. Tim, “Learning from Production Test
Data: Correlation Exploration and Feature Engineering”, in Test Symposium
(ATS), pp.236-241, Nov. 2014.
[6] F. Lin, Hsu, C. - K., and Cheng, K. - T. Tim, “Feature engineering with canonical
analysis for effective statistical tests screening test escapes”, in Test Conference (ITC), pp.1-10, Oct. 2014.
[7] 廖仁男, “Boomerang Equivalence: A Classifier for Uniform Wafer Maps ” , 碩
士論文﹐中央大學﹐2010.
[8] 曾國銓, “A Non-uniformly Distributed Defect Map Analysis by Quantification
Model” , 碩士論文﹐中華大學﹐2013.
[9] 林正田,“Wafer Map Analysis from a Random-Defect-Source Perspective”,
碩士論文﹐中央大學﹐2012.
[10] 邱政文,“Bat-wing : an inductive model for wafer map characterization and generation”, 碩士論文﹐中央大學﹐2006.
[11] MATLAB之工程應用,http://bime-matlab.blogspot.tw/
[12] 葉昱緯,“Application of Boomerang Chart to Real-World Mass Production Wafer Maps”,碩士論文﹐中央大學﹐2016. |
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