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http://dx.doi.org/10.7232/JKIIE.2014.40.3.257

A Prediction of Chip Quality using OPTICS (Ordering Points to Identify the Clustering Structure)-based Feature Extraction at the Cell Level  

Kim, Ki Hyun (School of Industrial Management Engineering, Korea University)
Baek, Jun Geol (School of Industrial Management Engineering, Korea University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.40, no.3, 2014 , pp. 257-266 More about this Journal
Abstract
The semiconductor manufacturing industry is managed by a number of parameters from the FAB which is the initial step of production to package test which is the final step of production. Various methods for prediction for the quality and yield are required to reduce the production costs caused by a complicated manufacturing process. In order to increase the accuracy of quality prediction, we have to extract the significant features from the large amount of data. In this study, we propose the method for extracting feature from the cell level data of probe test process using OPTICS which is one of the density-based clustering to improve the prediction accuracy of the quality of the assembled chips that will be placed in a package test. Two features extracted by using OPTICS are used as input variables of quality prediction model because of having position information of the cell defect. The package test progress for chips classified to the correct quality grade by performing the improved prediction method is expected to bring the effect of reducing production costs.
Keywords
Cell Defect; Cell Level; Feature Extraction; OPTICS; Quality Prediction;
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Times Cited By KSCI : 3  (Citation Analysis)
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