| 摘要(英) |
When we doing wafer testing, we constructed the Boomerang chart in a random way. This paper considers the average defects on the basis of the parameters of known wafers. By inferring the number of defects, we hope to define the true meaning of the number of defects on the wafer maps, and then accelerate wafer analysis.
This paper is based on the Poisson yield model, obtains the average defects λ0, and compares characteristic equation λw that established in [5]. After making two parameters equal, we can infer the ideal CL, then join the model of Boomerang bound made by [14], and define a new parameter: defect efficiency
Next, we performed 1.96 times the standard deviation (95% confidence interval), 2.58 times (99% confidence interval) and 3.89 times (99.99% confidence interval) inspection of the equivalent defects, and observed whether the distribution of equivalent defects conform to the normal distribution. Do the same analysis on the defect efficiency.
Finally, compare the relationship between B-score and defect efficiency, and observe how it differs from B-score. |
| 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] 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.
[5] 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.
[6] Takeshi Nakazawa, and Deepak V. Kulkarni, “Wafer Map Defect Pattern Classification and Image Retrieval Using Convolutional Neural Network”, in IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, VOL. 31, NO. 2, MAY 2018
[7] 林正田,“Wafer Map Analysis from a Random-Defect-Source Perspective”,碩士論文﹐中央大學﹐2012.
[8] 曾國銓,“A Non-uniformly Distributed Defect Map Analysis by Quantification Model” , 碩士論文﹐中華大學﹐2013
[9] 蕭寶威,“Wafer Map Analysis from Random Distributed Defects”, 碩士論文﹐中央大學﹐2016.
[10] 葉昱緯,“Application of Boomerang Chart to Real-World Mass Production Wafer Maps”, 碩士論文﹐中央大學﹐2016.
[11] 吳雅軒,“Wafer Map Partition Analysis to Enhance Systematic Error Resolution”, 碩士論文﹐中央大學﹐2018.
[12] 林敬儒,“Identification of the Classifier for the Pattern of Spatial Randomness”, 碩士論文﹐中央大學﹐2018.
[13] 林威沅 ,“Verification of B-score Randomness by Synthetic Random Wafer Maps and Application to Special Patterns”, 碩士論文﹐中央大學﹐2019.
[14] 侯睿軒 "Model Refinement for the Classifier of the Spatial Pattern Randomness",碩士論文，中央大學，2019
[15] 吳承晏”Application of Yield and Randomness Homogeneity Tests to Wafer Map Analysis”,碩士論文，中央大學，2020 |
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