L219 - SY-66 - Session programs - SCEJ 55th Autumn Meeting (Sapporo, 2024)

`SCEJ 55th Autumn Meeting (Sapporo, 2024)`

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Session programs : SY-66 : L219

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SY-66 [Symposium of Division of Systems, Information and Simulation Technologies]
Recent Research and Development of Process Systems Engineering

Organizers:

Kim Sanghong (Tokyo Univ. of Agri. and Tech.), Hayashi Yusuke (Univ. of Tokyo)

There is a need to develop systematic methodologies for rational decision making in chemical plant design, control, planning, operation, diagnosis, and maintenance, consistent with the ever-increasing sophistication, automation, and informatization of chemical plants. This symposium aims to provide an opportunity for active discussion of recent research and technology in the field of process systems engineering. *This session is eligible for the SIS Section Award.

Hall L, Day 1 | Hall L, Day 2

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Hall L(Block N 3F N302), Day 1(Sep. 11)
(13:00–14:00) (Chair: Takeda Kazuhiro)
13:00– 13:20	L113	Machine learning model estimating blood glucose monitoring from mid-infrared spectra measured by the photothermal monitoring method (Meiji U.) *(Stu)Takami Yuta, (Mitsubishi Electric) Miyagawa Keita, Tsuda Yuki, Akiyama Koichi, (Meiji U.) (Reg)Kaneko Hiromasa	mid-infrared spectra noninvasive blood glucose monitoring machine learning	SY-66	102
13:20– 13:40	L114	Validation on Multi-timescale Data-driven Reduced Order Model for Fast Predictive Simulations in a Fluidized Bed (U. Tokyo) *(Stu)Yang Kai-En, (Reg)Li Shuo, (Reg)Sakai Mikio	Data-driven Multi-timescale ROM DEM-CFD Fast Predictive Simulations	SY-66	214
13:40– 14:00	L115	Development of a soft sensor model that takes into account the dynamic characteristics of the process and two similar qualities (Meiji U.) *(Stu)Ohkuma Ayami, (Mitsubishi Chemical) (Cor)Yamauchi Yoshihito, (Cor)Yamada Nobuhito, (Cor)Ooyama Satoshi, (Meiji U.) (Reg)Kaneko Hiromasa	machine learning soft sensor time delay	SY-66	260
(14:00–14:40) (Chair: Xia Junqing)
14:00– 14:20	L116	Development of a Generative AI-Powered Support System for Creating Equipment Design Guidelines for Organizational Integration (Resonac) *(Cor)Masuda Satoru, (Cor)Okano Yu, (Cor)Yoshida Katsuhisa, (Cor)Sugiyama Tamotsu, (Cor)Onodera Toshiya	Generative AI Large Language Models	SY-66	509
14:20– 14:40	L117	Application of Reinforcement Learning to the Control of Thermal Storage System in Concentrating Solar Power (Kyoto U.) *(Stu)Kuroiwa T., (UNIST) (Int)Oh T. H., (Kyoto U.) (Reg)Tonomura O., (Reg)Sotowa K.	Reinforcement Learning Concentrating Solar Power Plant Optimal Control	SY-66	806
(15:00–16:00) (Chair: Kaneko Hiromasa)
15:00– 15:20	L119	Digital Utilization of P&ID: Challenges in Using Topology Data from PFD to P&ID and 3D (JGC) *(Cor)Iwamuro Norito, (Cor)Koito Hiroyuki, (Cor)Yamada Yoshinori, (Cor)Kokubo Hiroki, (Cor)Kaida Sachiko, (Cor)Hori Reo	Piping and Instrument Diagram Plant Design Topology	SY-66	521
15:20– 15:40	L120	Elucidation on suction effect for powder filling in a rotary tablet press (U. Tokyo) *(Stu)Hashimoto Arata, (Reg)Sakai Mikio	multi-physics simulation discrete element method powder die filling	SY-66	192
15:40– 16:00	L121	A method for estimating the reaction rates by inverse analysis of elementary reaction and transport model simulating a denitrification system (Toshiba Energy Systems & Solutions) *(Reg)Nakamura Kotaro, Takeyama Daiki, Tsukada Keisuke, Fukuta Masato	Kinetic model Surface reaction Optimization	SY-66	326
(16:00–17:00) (Chair: Oishi Takuya)
16:00– 16:20	L122	Development of Plot Plan design automation system for chemical plant (JGC) *(Cor)Yamada Yoshinori, (Cor)Koito Hiroyuki, (Cor)Kokubo Hiroki, (Cor)Iwamuro Norito, (Waseda U.) Arakawa Masao	Piping and Instrument Diagram Plant Design Plot Plan	SY-66	565
16:20– 16:40	L123	Numerical study on ellipsoidal particle mixing in a cylindrical tank (U. Tokyo) *(Stu)Kyoya Keita, (Reg)Li Shuo, (Reg)Sakai Mikio	discrete element method ellipsoidal particle powder mixing	SY-66	195
16:40– 17:00	L124	[Featured presentation] Wavelength-weighting concentration prediction robust against spectra-unknown components using few samples (Kyoto U.) *(Stu)Kobayashi Sakuya, (Reg)Kato Shota, (Reg)Kano Manabu	spectroscopic analysis	SY-66	209
Hall L(Block N 3F N302), Day 2(Sep. 12)
(9:00–10:20) (Chair: Hayashi Yusuke)
9:00– 9:20	L201	Digital Utilization of P&ID: Paradigm Shift in Design Processes Initiated by Plant Maintenance (Brownreverse) (Reg)Kanamaru Takehisa	Piping and Instrument Diagram Digital Twin Reverse Engineering	SY-66	940
9:20– 9:40	L202	Improved accuracy of anomaly detection through optimization of scaling factor in multiway-MSPC (Powrex/TUAT) *(Reg)Oishi Takuya, (Powrex) (Reg)Kodama Satoshi, (TUAT) (Reg)Kim Sanghong	Multivariate Statistical Process Control Multiway-Principal Component Analysis Pharmaceutical Manufacturing Process	SY-66	104
9:40– 10:00	L203	Development of Anomaly Classification Technology based on Measured Data (Fuji Electric) *(Div)Murakami Kenya, (Div)Santana Adamo, (Div)Suzuki Satoshi, (Div)Iizaka Tatsuya	Anomaly Classification Trouble Prevention	SY-66	468
10:00– 10:20	L204	Digital Utilization of P&ID : Development and Practical Implementation of an Automated Routing Algorithm for Pipes and Cables (PlantStream) (Cor)Narue Seitaro	Piping and Instrument Diagram Plant Design Auto Routing	SY-66	275
(10:40–12:00) (Chair: Kim Sanghong)
10:40– 11:00	L206	Design space determination in freezing processes for human iPS cell-derived spheroids using hybrid models (U. Tokyo) *(Stu)Fujioka Masaharu, (Reg)Hayashi Yusuke, (Sumitomo Pharma) Yamaguchi Yuta, Fujii Tetsuya, (U. Tokyo) (Reg)Sugiyama Hirokazu	Manufacturing Regenerative medicine Numerical simulation	SY-66	567
11:00– 11:20	L207	In-line near-infrared spectroscopic monitoring of molding process of polymer blends (Kyoto U.) *(Stu)Yoshikawa Itsuki, (AIST) (Reg)Hikima Yuta, (Kyoto U.) Ohshima Masahiro, (Reg)Sotowa Ken-Ichiro	in-line monitoring polymer processing near-infrared spectroscopy	SY-66	161
11:20– 11:40	L208	Process Topology-Enhanced Deep Learning for Small Data Analysis (TUAT) *(Stu·PCEF)Horiuchi Hiroki, (Reg)Yamashita Yoshiyuki	Graph Convolutional Networks Process Flow Diagram Small Data Analytics	SY-66	734
11:40– 12:00	L209	Development of an integration algorithm of design of experiment for understanding chemical space and fast optimization (Shizuoka U.) *(Reg)Takeda Kazuhiro, (U. Shizuoka) (Reg)Kondo Masaru, (Osaka U.) (Reg)Takizawa Shinobu	definitive screening design Bayesian optimization chemical space	SY-66	8
(13:00–14:00) (Chair: Kataoka Sho)
13:00– 13:20	L213	Optimization of property prediction model in dynamic manufacturing process for carbon materials using a genetic algorithm (Meiji U.) *(Stu)Matsubara Masayoshi, (Mitsubishi Chemical) (Cor)Sasaki Ryo, (Cor)Takahara Jun, (Cor)Moritake Shinji, (Cor)Harada Yasuyuki, (Meiji U.) (Reg)Kaneko Hiromasa	Machine learning Genetic-algorithm-based process variables and dynamics selection Multi-objective optimization	SY-66	273
13:20– 13:40	L214	Discussion toward the application of mathematical models in controlling cell cultivation and antibody production (U. Tokyo) *(Reg·SPCE)Yamada Akira, (Reg)Sugiyama Hirokazu	Cell Cultivation Antibody production Process Control	SY-66	573
13:40– 14:00	L215	The effect of the number of degree of freedoms of temperature control in cooling batch crystallization on the productivity and the quality of crystalline particles (TUAT) *(Stu)Iizuka Saki, (Reg·APCE)Kim Sanghong	Crystallization Process synthesis Distributed parameter system	SY-66	1064
(14:00–15:00) (Chair: Taguchi Tomoyuki)
14:00– 14:20	L216	Deep Learning Prediction Model for Solubility of Nanoparticles From Perspective of Similarity (TUAT) *(Reg·PCE)Xia Junqing, (Reg)Yamashita Yoshiyuki	Nanoparticle solubility Deep learning	SY-66	677
14:20– 14:40	L217	Modeling of monoclonal antibody production processes using data from automated cultivation experiment (U. Tokyo) *(Stu)Nemoto Kosuke, (Int)Badr Sara, (Reg)Hayashi Yusuke, (Stu)Yoshiyama Yuki, (Reg)Okamura Kozue, (Chitose Laboratory) Morisasa Mizuki, Iwabuchi Junshin, (U. Tokyo) (Reg)Sugiyama Hirokazu	Hybrid modeling Dynamic simulation Biopharmaceuticals	SY-66	457
14:40– 15:00	L218	Design of Experiments for Identification Using Small-Sample Data: Minimizing the Volume of the Nonasymptotic Confidence Region of the Model Parameters (Kyoto U.) *(Stu·PCEF)Oshima Masanori, (TUAT) (Reg·APCE)Kim Sanghong, (TU Ilmenau) Shardt Yuri, (Kyoto U.) (Reg)Sotowa Ken-Ichiro	system identification design of experiments finite-sample data	SY-66	304
(15:00–15:40) (Chair: Yamada Akira)
15:00– 15:20	L219	Molecular design with direct inverse analysis of autoencoder-based QSAR/QSPR model (Meiji U.) *(Stu)Shino Yuto, (Reg)Kaneko Hiromasa	Machine learning Inverse analysis Molecular design	SY-66	140
15:20– 15:40	L220	Surrogate Modeling for Process Optimization Using Quantum Annealing Machines (Tohoku U.) *(Stu)Fukushima Kazuki, (Stu)Inukai Motoaki, (Reg)Yagihara Koki, (Reg)Ohno Hajime, (Reg)Fukushima Yasuhiro	Optimization Chemical Process Quantum Annealing	SY-66	671

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SCEJ 55th Autumn Meeting (Sapporo, 2024)

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SCEJ 55th Autumn Meeting (Sapporo, 2024)

Session programs : SY-66 : L219

SY-66 [Symposium of Division of Systems, Information and Simulation Technologies] Recent Research and Development of Process Systems Engineering

`SCEJ 55th Autumn Meeting (Sapporo, 2024)`

SY-66 [Symposium of Division of Systems, Information and Simulation Technologies]
Recent Research and Development of Process Systems Engineering