@inproceedings{b27e0a1572434deb94d4fc4963be5515,
title = "Prediction of package chip quality using fail bit count data of the probe test",
abstract = "The quality prediction of the semiconductor industry has been widely recognized as important and critical for quality improvement and productivity enhancement. The main objective of this paper is to establish a prediction methodology of semiconductor chip quality. Although various research has been conducted for predicting a yield, these studies predict a yield by lot-level and do not consider characteristics of the data. We demonstrate the effectiveness of the proposed procedure using a real data from a semiconductor manufacturing.",
keywords = "Nonparametric variable Selection, Probe test, Quality prediction, Smote",
author = "Park, {Jin Soo} and Kim, {Seoung Bum}",
year = "2015",
doi = "10.1007/978-3-319-19066-2_63",
language = "English",
isbn = "9783319190655",
volume = "9101",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "655--664",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
note = "28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015 ; Conference date: 10-06-2015 Through 12-06-2015",
}