A Methodology for Efficient Dynamic Spatial Sampling and Reconstruction of Wafer Profiles
- Submitting institution
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Queen's University of Belfast
- Unit of assessment
- 12 - Engineering
- Output identifier
- 147259315
- Type
- D - Journal article
- DOI
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10.1109/TASE.2017.2786213
- Title of journal
- IEEE Transactions of Automation Science and Engineering
- Article number
- -
- First page
- 1692
- Volume
- 15
- Issue
- 4
- ISSN
- 1545-5955
- Open access status
- Other exception
- Month of publication
- January
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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C - Electrical and Electronic
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research was motivated by a problem statement provided by the semiconductor manufacturing industry - how to reduce the volume of costly non-valued add wafer metrology without impacting quality control. The proposed solution, which leverages data analytics and machine learning techniques, is transformative relative to current practice in the semiconductor industry. The static sampling version of the methodology has been successfully trialled at Seagate’s read-write head manufacturing facility. (paul.a.scullion@seagate.com). A software platform for the commercial deployment and piloting of the dynamic sampling methodology is currently in development.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -