NDLI: Using process experienced correlation table to improve the accuracy and reliability of data mining for yield improvement

Content Provider	IEEE Xplore Digital Library
Author	Haw-Jyue Luo Wang, S.R. Chen, C.C. Hung-En Tai Chen-Fu Chien Pei-Nong Chen
Copyright Year	2004
Description	Author affiliation: Powerchip Semicond. Corp., Nat. Tsing Hua Univ., Hsinchu (Haw-Jyue Luo; Wang, S.R.; Chen, C.C.; Hung-En Tai; Chen-Fu Chien; Pei-Nong Chen)
Abstract	The rapid innovation of new process technologies in the semiconductor industry, especially 12 inches Fab, along with continuously growing amounts of data, it is difficult to find root cause when problems occur in some process steps. It causes large amount of wafer scrapping. The analysis methods of traditional EDA system rely on experience of senior engineers. They need to define the suspected process step by their experience and then perform analysis. The analysis methods consume large amounts of human resources in order to determine the root cause of process and yield excursions. Hence, it is important that a knowledge retention method be incorporated to improve the efficiency of root cause analysis. Data mining, a new data analysis method that combines information science and technology of statistical analysis, is developed recently. The new generation data analysis method includes statistical, information science and mathematical calculation to find correlation between the target parameter, for example yield and other parameters. It will provide important clue to the analyzer. In addition, it also provides a direction to find root cause rapidly. It is difficult to find the correlation between the target parameter and other parameters by traditional statistical analysis method, and data mining can solve the blind point of the traditional method. This article discusses the design of how to define the relation between all data sources of semiconductor industry based on the experience of senior engineers. And it installs the relation to data mining analysis, it performs the analysis to identify relationship among all data sources. So, engineers can find the root cause of process issue in a short period of time
Sponsorship	Taiwan Semiconductor Ind. Assoc. IEEE Electron Devices Soc. Taipei Chapter
Starting Page	127
Ending Page	130
File Size	245846
Page Count	4
File Format	PDF
ISBN	0780384695
DOI	10.1109/SMTW.2004.1393746
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-09
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Performance analysis Data analysis Electronics industry Information science Statistical analysis Technological innovation Electronic design automation and methodology Humans Data engineering
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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