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
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML