Journal
JOURNAL OF MANUFACTURING SYSTEMS
Volume 52, Issue -, Pages 146-156Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jmsy.2019.07.001
Keywords
Semiconductor manufacturing; Data mining; Missing value imputation; Re-Sampling; Feature selection
Categories
Funding
- National Research Foundation of Korea [2016K2A9A2A11938390]
- Hanyang University [HY-2018]
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Semiconductor wafers are fabricated through sequential process steps. Some process steps have a strong relationship with wafer yield, and these are called critical process steps. Because wafer yield is a key performance index in wafer fabrication, the critical process steps should be carefully selected and managed. This paper proposes a systematic and data-driven approach for identifying the critical process steps. The proposed method considers troublesome properties of the data from the process steps such as imbalanced data, missing values, and random sampling. As a case study, we analyzed hypothetical operational data and confirmed that the proposed method works well.
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