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A data-driven approach to selection of critical process steps in the semiconductor manufacturing process considering missing and imbalanced data

Title
A data-driven approach to selection of critical process steps in the semiconductor manufacturing process considering missing and imbalanced data
Author
이동희
Keywords
Semiconductor manufacturing; Data mining; Missing value imputation; Re-Sampling; Feature selection
Issue Date
2019-07
Publisher
ELSEVIER SCI LTD
Citation
JOURNAL OF MANUFACTURING SYSTEMS, v. 52, Page. 146-156
Abstract
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.
URI
https://www.sciencedirect.com/science/article/pii/S0278612518302735?via%3Dihubhttps://repository.hanyang.ac.kr/handle/20.500.11754/152388
ISSN
0278-6125; 1878-6642
DOI
10.1016/j.jmsy.2019.07.001
Appears in Collections:
ETC[S] > 연구정보
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