Last Update: 2018-12-17 03:35:01

List of Received Applications (SY-68) [Japanese]


SY) SCEJ Division Symposium

SY-68. [Symposium of Division of Systems, Information and Simulation Technologies] Recent Research and Development of Process Systems Engineering

Organizer(s): Kano Manabu (Kyoto Univ.), Takatsuka Kayoko (Univ. of Miyazaki), Horie Takafumi (Kobe Univ.)

Most recent update: 2018-12-17 03:35:01

The keywords that frequently used
in this topics code.
KeywordsNumber
Design of Experiments1
Gray-box model1
Fault detection1
quality1
multivariate process data1
Multi-variable analysis1
Mixture designs1
nonlinear regression model1
time series data1
Keeling model1
estimation1
Scheduling1
Grey-box modeling1
Soft-sensor1
risks of infection1
hyper-parameter1
soft sensor1
Decision-making1
Product yield1
machine learning1
process design model1
vitamin E purification1
Czochralski process1
Domain knowledge1
project management1
factor identification1
Digitalization1
Cryobiology1
big data1
actual biomass system1
Numerical simulation1
Smart manufacturing1

ACKN
No.
Title/Author(s)KeywordsStyle
18Management of project cost estimation process based on its resource flow
(Kanagawa U.) *(Reg)Ishii Nobuaki, (U. Tsukuba) Takano Yuichi, (Tokyo Tech) (Reg)Muraki Masaaki
engineering-to-order
project management
simulation
O
232Framework for data-driven process improvement and operations support in biopharmaceutical drug product manufacturing
(U. Tokyo) *(Stu)Casola Gioele, (Hoffmann-La Roche) Siegmund Christian, Mattern Markus, (U. Tokyo) (Reg)Sugiyama Hirokazu
Digitalization
Smart manufacturing
Decision-making
O
249Data-driven predictive monitoring and operation support for decontamination processes in biopharmaceutical manufacturing
(U. Tokyo) *(Stu)Zeberli Anicia, Badr Sara, (Hoffmann-La Roche) Siegmund Christian, Mattern Markus, (U. Tokyo) (Reg)Sugiyama Hirokazu
machine learning
predictive maintenance
big data
O
280Investigation of the effect of utilizing the process knowledge for sample selection in soft-sensor design
(Kyoto U.) *(Stu·PCEF)Matsuyama Yukio, (Reg·APCE)Kim Sanghong, (Reg)Hasebe Shinji
Soft-sensor
Sample selection
Domain knowledge
O
312Development of a new evaluation method for soft sensors based on time series data
(Meiji U.) *(Stu)Kojima Takumi, (Reg)Kaneko Hiromasa
soft sensor
time series data
hyper-parameter
O
431Freeze-thaw process design of induced pluripotent stem cells using mechanistic models
(U. Tokyo) *(Stu)Hayashi Yusuke, (Osaka U.) (Reg)Horiguchi Ikki, (Reg)Kino-oka Masahiro, (U. Tokyo) (Reg)Hirao Masahiko, (Reg)Sugiyama Hirokazu
Cryobiology
Numerical simulation
Multiobjective process design
O
455Machine combination adjustment in multi-process production system for improving product yield
(Kyoto U.) Suzuki Yoshiaki, *(Reg)Kano Manabu, (Toshiba) Soga Akira, Yanagimachi Takeshi, Murao Ryo, Takaki Masaya
Machine combination
Product yield
Scheduling
O
457Quantification of variable importance based on nonlinear regression model and its application to causal analysis of defective steel products
(Kyoto U.) Kawakita Takuya, *(Reg)Kano Manabu, (Nippon Steel & Sumitomo Metal) Tani Masahiro, Mori Junichi, Ise Junji, Nishimura Ryohichi, Harada Kohhei
Causal analysis
nonlinear regression model
steel product
O
461A new method of identifying major quality factors from multivariate process data
(Fuji Electric) *(Div)Murakami K., (Div)Iisaka T., (Div)Matsui T., (Reg)Tanaka M.
multivariate process data
quality
factor identification
O
473Approach to quantitative improvement of the trade-off relationship between the risks of infection with foot-and mouth disease and budget for epidemic prevention
(U. Miyazaki) *(Reg)Takatsuka Kayoko, Sekiguchi Satoshi, Mukunoki Masayuki, Okazaki Naonobu
Keeling model
risks of infection
budget
O
501Model predictive control of Czochralski process producing 300 mm single crystal silicon ingot
(Kyoto U.) *(Stu)Kato Shota, (Stu)Yoshioka Hironobu, (Reg·APCE)Kim Sanghong, (Reg)Kano Manabu, (SUMCO) Fujiwara Toshiyuki, (Reg)Mizuta Masahiko, (Kyoto U.) (Reg)Hasebe Shinji
Model predictive control
Czochralski process
Gray-box model
O
670Physical-knowledge based extension of attributes for process monitoring
(TUAT) *(Stu·PCEF)Xia Junqing, (Reg)Yamashita Yoshiyuki
Fault detection
Grey-box modeling
Multi-variable analysis
O
1021Natural vitamin E purification process design based on the competitive adsorption model ~ development from model system to actual system ~
(Tohoku U.) *(Stu·PCEF)Watanabe Tomoya, (Reg·PCEF)Hiromori Kousuke, (Reg)Takahashi Atsushi, (Reg)Shibasaki-Kitakawa Naomi
process design model
vitamin E purification
actual biomass system
O
1057Optimization of monomer compositions with non-linear regression model for functional polymer design
(U. Tokyo) *(Stu)Shibayama Shojiro, (Reg)Funatsu Kimito
Mixture designs
Optimization
Design of Experiments
O
1065A study for estimation of internal state of a micro wave flow reactor using a absorption parameter
(Shizuoka U.) *(Stu)Kitagawa Akiko, (Stu)Uchiyama Taro, (Stu)Tanaka Tatsuya, (Reg)Takeda Kazuhiro
micro wave
flow reactor
estimation
O

List of received applications (By topics code)

List of received applications
SCEJ 50th Autumn Meeting (Kagoshima, 2018)