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Increasing detectability in semiconductor foundry by multivariate statistical process control (Record no. 27063)

000 -LEADER
fixed length control field 02152naa a2200229uu 4500
001 - CONTROL NUMBER
control field 8071616112010
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190211164018.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 080716s2008 xx ||||gr |0|| 0 eng d
999 ## - SYSTEM CONTROL NUMBERS (KOHA)
Koha Dewey Subclass [OBSOLETE] PHL2MARC21 1.1
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name YANG, Chyan
9 (RLIN) 35024
245 10 - TITLE STATEMENT
Title Increasing detectability in semiconductor foundry by multivariate statistical process control
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Oxfordshire, UK :
Name of publisher, distributor, etc. Taylor & Francis,
Date of publication, distribution, etc. May-June 2008
520 3# - SUMMARY, ETC.
Summary, etc. Quality has become a key determinant of success in all aspects of modern industries. It is especially prominent in the semiconductor industry. This paper reviews the contributions of statistical analysis and methods to modern quality control and improvement. The two main areas are statistical process control (SPC) and experimentation. The statistical approach is placed in the context of recent developments in quality management, with particular reference to the total quality movement.
520 3# - SUMMARY, ETC.
Summary, etc. In SPC, Hotelling T2 has been applied in laboratories with good result; however, it is rarely used in mass production, especially in the semiconductor industry. An advance process control (APC) of R&D study, involving Hotelling T2 and principal component analysis (PCA), is performed on a high density plasma chemical vapour deposition (HDP CVD) equipment in the 12-inch wafer fab. The design of experiment (DOE) of gas flow and RF power effects is used to work the feasibility of PCA for SPC and examine the correlation among tool parameters. In this work, the Hotelling T2 model is shown to be sensitive to variations as small as (+/ - )5% in the tool parameters. Compared with classical PDCA and qualitative analysis, applying statistical in process control is more effective and indeed necessary. This model also is especially suitable to the semiconductor industry
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name CHANG, Chao-Jung
9 (RLIN) 35025
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name NIU, Han-Jen
9 (RLIN) 35026
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name WU, Hsueh-Chang
9 (RLIN) 35027
773 08 - HOST ITEM ENTRY
Title Total quality management & business excellence
Related parts 19, 5-6, p. 429-440
Place, publisher, and date of publication Oxfordshire, UK : Taylor & Francis, May-June 2008
International Standard Serial Number ISSN 14783363
Record control number
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Periódico
998 ## - LOCAL CONTROL INFORMATION (RLIN)
-- 20080716
Operator's initials, OID (RLIN) 1611^b
Cataloger's initials, CIN (RLIN) Tiago
998 ## - LOCAL CONTROL INFORMATION (RLIN)
-- 20081209
Operator's initials, OID (RLIN) 1017^b
Cataloger's initials, CIN (RLIN) Zailton

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