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SCEJ 89th Annual Meeting (Sakai, 2024)

Last modified: 2024-06-18 12:32:12

Session programs : 6. Systems, information, and simulation technologies : K216

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6. Systems, information, and simulation technologies

Hall K, Day 1 | Hall K, Day 2

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
Hall K(B3 2F 204), Day 1(Mar. 18)
(13:20–14:20) (Chair: Sotowa Kenichiro)
13:2013:40K114Monitoring pseudoplasticity modification of rice porridge by ultrasonic in-line rheometry
(Hokkaido U.) *(Stu)Ohie Kohei, (Reg)Yoshida Taiki, (Reg)Tasaka Yuji, Murai Yuichi
Rheology
In-line measurement
Rice porridge
6-a26
13:4014:00K115Quality prediction in a small data environment for batch processes
(Kaneka) (Cor)Yamaguchi Takafumi
Machine Learning
Quality Prediction
Small data
6-a286
14:0014:20K116Development of a new indicator for comprehending cyclic variations in process behavior by applying frequency analysis
(TUAT) *(Stu)Wada Tetsuya, (Reg)Yamashita Yoshiyuki
Wavelet Transformation
Fault Detection
Stability Indicator
6-a673
(14:20–15:40) (Chair: Noda Masaru, Yamaguchi Takafumi)
14:2014:40K117Design and Optimization of an Integrated CO2 Capture, Utilization and Storage System for Large-scale Removal of CO2 emissions
(AIST) *(Reg)Nguyen Thuy, Taniguchi Satoshi, (Reg)Yamaki Takehiro, (Reg)Hara Nobuo, (Reg)Kataoka Sho
integrated CCUS system
large-scale CO2 emission sources
process design and optimization
6-b359
14:4015:00K118Model-based approach to design space determination in drug substance flow synthesis using Grignard reaction
(U. Tokyo) *(Reg)Kim Junu, (Reg)Hayashi Yusuke, (Reg)Badr Sara, (Pharmira) Okamoto Kazuya, Hakogi Toshikazu, (Reg)Furukawa Haruo, (Shionogi Pharma) (Reg)Yoshikawa Satoshi, (Reg)Nakanishi Hayao, (U. Tokyo) (Reg)Sugiyama Hirokazu
Hybrid model
Flow chemistry
Disturbance
6-b234
15:0015:20K119Data-driven approach to automated reaction process analysis
(U.Tokyo/Auxilart) *(Reg)Kim Junu, (Riken AIP) Sakata Itsushi, (Ubitone) Yamatsuta Eitaro, (U.Tokyo) (Reg)Sugiyama Hirokazu
Mechanistic model
Machine learning
Neural network
6-b235
15:2015:40K120Flow Analysis of Gravure Coating Room Using Cloud-Native CAE
(Kozo Keikaku Eng.) *(Cor)Yamanaka Yuma, (Cor)Watanabe Kaoru, (AndanTEC) (Reg)Hamamoto Nobuo
Gravure Coating Room
Cloud-Native CAE
CFD
6-b95
(15:40–17:00) (Chair: Sakai Mikio, Kataoka Sho)
15:4016:00K121Modeling and control of systems with large time delay
(ENEOS) *(Reg)Daiguji Masaharu, (TUAT) (Reg)Yamashita Yoshiyuki
process control
6-d733
16:0016:20K122(withdrawn)

100189
16:2016:40K123The Utilization of AI in Process Plants
(Chiyoda) (Cor)Ogawa Rentaro
Physical model
Machine-learning
Plant efficiency enhancement
6-e624
16:4017:00K124Dynamic Process Simulation for Green Ammonia Synthesis Considering Wind and Solar Condition
(NIT Nagaoka) *(Reg)Atsumi Ryosuke, (Stu)Kaneuchi Taiyo, (Stu)Hada Yasuyuki
Dynamic simulation
Green ammonia
Machine learning
6-c695
Hall K(B3 2F 204), Day 2(Mar. 19)
(13:20–14:00) (Chair: Sugiyama Hirokazu, Morishita Tetsunori)
13:2013:40K214Improved accuracy of MSPC through optimization of scaling factor of multivariable independent of domain knowledge.
(Powrex/TUAT) *(Reg)Oishi Takuya, (Powrex) (Reg)Nagato Takuya, (TUAT) (Reg)Kim Sanghong
Pharmaceutical Continuous Manufacturing
Wet Granulation
Multivariate Statistical Process Control
6-f239
13:4014:00K215A parameter estimation method for chromatographic separation process based on physics-informed neural network
(Nagoya U.) *(Stu)Zou Tao, (Reg)Yajima Tomoyuki, (Reg)Kawajiri Yoshiaki
parameter estimation
chromatographic process
physics-informed neural network
6-f44
(14:00–14:40) (Chair: Hara Nobuo, Oishi Takuya)
14:0014:20K216Model-based design framework for antibody drug production processes considering perspectives from cell characteristics to social requirements
(UTokyo) *(Stu)Okamura K., (Int)Badr S., (Reg)Sugiyama H.
Biopharmaceuticals
Process design
IDEF0
6-g92
14:2014:40K217Coarse-Grained Force Field Parametrization for Polymers Using Machine Learning
(Toyota Motor) *(Reg)Morishita Tetsunori, (Massachusetts Inst. Tech.) Leon Pablo, Gomez-Bombarelli Rafael
Coarse-Grained Force Field
Machine Learning
6-g220

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SCEJ 89th Annual Meeting (Sakai, 2024)


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