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

`SCEJ 89th Annual Meeting (Sakai, 2024)`

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

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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

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Hall K(B3 2F 204), Day 1(Mar. 18)
(13:20–14:20) (Chair: Sotowa Kenichiro)
13:20– 13:40	K114	Monitoring 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-a	26
13:40– 14:00	K115	Quality prediction in a small data environment for batch processes (Kaneka) (Cor)Yamaguchi Takafumi	Machine Learning Quality Prediction Small data	6-a	286
14:00– 14:20	K116	Development 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-a	673
(14:20–15:40) (Chair: Noda Masaru, Yamaguchi Takafumi)
14:20– 14:40	K117	Design 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-b	359
14:40– 15:00	K118	Model-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-b	234
15:00– 15:20	K119	Data-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-b	235
15:20– 15:40	K120	Flow 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-b	95
(15:40–17:00) (Chair: Sakai Mikio, Kataoka Sho)
15:40– 16:00	K121	Modeling and control of systems with large time delay (ENEOS) *(Reg)Daiguji Masaharu, (TUAT) (Reg)Yamashita Yoshiyuki	process control	6-d	733
16:00– 16:20	K122	(withdrawn)		100	189
16:20– 16:40	K123	The Utilization of AI in Process Plants (Chiyoda) (Cor)Ogawa Rentaro	Physical model Machine-learning Plant efficiency enhancement	6-e	624
16:40– 17:00	K124	Dynamic 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-c	695
Hall K(B3 2F 204), Day 2(Mar. 19)
(13:20–14:00) (Chair: Sugiyama Hirokazu, Morishita Tetsunori)
13:20– 13:40	K214	Improved 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-f	239
13:40– 14:00	K215	A 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-f	44
(14:00–14:40) (Chair: Hara Nobuo, Oishi Takuya)
14:00– 14:20	K216	Model-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-g	92
14:20– 14:40	K217	Coarse-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-g	220

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SCEJ 89th Annual Meeting (Sakai, 2024)

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