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.
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Park, J.S., Kim, S.B. (2015). Prediction of Package Chip Quality Using Fail Bit Count Data of the Probe Test. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_63
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DOI: https://doi.org/10.1007/978-3-319-19066-2_63
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