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Sang Jeen Hong
Sang Jeen Hong
Verified email at mju.ac.kr
Title
Cited by
Cited by
Year
Neural network modeling of reactive ion etching using optical emission spectroscopy data
SJ Hong, GS May, DC Park
IEEE Transactions on Semiconductor Manufacturing 16 (4), 598-608, 2003
1182003
Fault Detection and Classification in Plasma Etch Equipment for Semiconductor Manufacturing -Diagnostics
SJ Hong, WY Lim, T Cheong, GS May
IEEE Transactions on Semiconductor Manufacturing 25 (1), 83-93, 2011
932011
Neural network-based real-time malfunction diagnosis of reactive ion etching using in situ metrology data
SJ Hong, GS May
IEEE transactions on semiconductor manufacturing 17 (3), 408-421, 2004
562004
Neural-network-based sensor fusion of optical emission and mass spectroscopy data for real-time fault detection in reactive ion etching
SJ Hong, GS May
IEEE Transactions on Industrial Electronics 52 (4), 1063-1072, 2005
502005
Machine learning-based process-level fault detection and part-level fault classification in semiconductor etch equipment
SH Kim, CY Kim, DH Seol, JE Choi, SJ Hong
IEEE Transactions on Semiconductor Manufacturing 35 (2), 174-185, 2022
372022
Use of plasma information in machine-learning-based fault detection and classification for advanced equipment control
DH Kim, SJ Hong
IEEE Transactions on Semiconductor Manufacturing 34 (3), 408-419, 2021
302021
Artificial immune system for fault detection and classification of semiconductor equipment
H Park, JE Choi, D Kim, SJ Hong
Electronics 10 (8), 944, 2021
292021
Fault detection in reactive ion etching systems using one-class support vector machines
T Sarmiento, SJ Hong, GS May
IEEE/SEMI Conference and Workshop on Advanced Semiconductor Manufacturing …, 2005
282005
High-aspect ratio through-silicon vias for the integration of microfluidic cooling with 3D microsystems
H Oh, JM Gu, SJ Hong, GS May, MS Bakir
Microelectronic Engineering 142, 30-35, 2015
272015
Fault diagnosis in semiconductor etch equipment using Bayesian networks
JM Nawaz, MZ Arshad, SJ Hong
JSTS: Journal of Semiconductor Technology and Science 14 (2), 252-261, 2014
232014
Machine learning-based virtual metrology on film thickness in amorphous carbon layer deposition process
JE Choi, SJ Hong
Measurement: Sensors 16, 100046, 2021
222021
Surface Analysis of Chamber Coating Materials Exposed to CF4/O2 Plasma
SH Park, KE Kim, SJ Hong
Coatings 11 (1), 105, 2021
212021
An object-oriented neural network simulator for semiconductor manufacturing applications
C Davis, S Hong, R Setia, R Pratap, T Brown, B Ku, G Triplett, G May
The 8th world multi-conference on systemics cybernetics informatics 5, 365-370, 2004
192004
In-situ monitoring of multiple oxide/nitride dielectric stack PECVD deposition process
DB Jang, SJ Hong
Transactions on Electrical and Electronic Materials 19, 21-26, 2018
182018
Copper pillar tin bump on semiconductor chip and method of forming the same
K Lee, SJ Hong
US Patent 7,781,325, 2010
182010
Characterization of low-temperature SU-8 photoresist processing for MEMS applications
SJ Hong, S Choi, Y Choi, M Allen, GS May
2004 IEEE/SEMI Advanced Semiconductor Manufacturing Conference and Workshop …, 2004
182004
Virtual metrology for etch profile in silicon trench etching with SF₆/O₂/Ar plasma
JE Choi, H Park, Y Lee, SJ Hong
IEEE Transactions on Semiconductor Manufacturing 35 (1), 128-136, 2021
162021
Surface analysis of amorphous carbon thin film for etch hard mask
KP Kim, WS Song, MK Park, SJ Hong
Journal of Nanoscience and Nanotechnology 21 (3), 2032-2038, 2021
162021
Neural-network-based time series modeling of optical emission spectroscopy data for fault detection in reactive ion etching
SJ Hong, GS May
Process and Materials Characterization and Diagnostics in IC Manufacturing …, 2003
162003
Endpoint detection in low open area TSV fabrication using optical emission spectroscopy
JM Gu, PA Thadesar, A Dembla, MS Bakir, GS May, SJ Hong
IEEE Transactions on Components, Packaging and Manufacturing Technology 4 (7 …, 2014
152014
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