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SCEJ 55th Autumn Meeting (Sapporo, 2024)

Last modified: 2024-09-09 18:25:12

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

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
Hall L(Block N 3F N302), Day 1(Sep. 11)
(13:00–14:00) (Chair: Takeda Kazuhiro)
13:0013:20L113Machine 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-66102
13:2013:40L114Validation 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-66214
13:4014:00L115Development 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-66260
(14:00–14:40) (Chair: Xia Junqing)
14:0014:20L116Development 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-66509
14:2014:40L117Application 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-66806
(15:00–16:00) (Chair: Kaneko Hiromasa)
15:0015:20L119Digital 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-66521
15:2015:40L120Elucidation 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-66192
15:4016:00L121A 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-66326
(16:00–17:00) (Chair: Oishi Takuya)
16:0016:20L122Development 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-66565
16:2016:40L123Numerical 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-66195
16:4017:00L124[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-66209
Hall L(Block N 3F N302), Day 2(Sep. 12)
(9:00–10:20) (Chair: Hayashi Yusuke)
9:009:20L201Digital 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-66940
9:209:40L202Improved 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-66104
9:4010:00L203Development 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-66468
10:0010:20L204Digital 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-66275
(10:40–12:00) (Chair: Kim Sanghong)
10:4011:00L206Design 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-66567
11:0011:20L207In-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-66161
11:2011:40L208Process 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-66734
11:4012:00L209Development 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-668
(13:00–14:00) (Chair: Kataoka Sho)
13:0013:20L213Optimization 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-66273
13:2013:40L214Discussion 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-66573
13:4014:00L215The 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-661064
(14:00–15:00) (Chair: Taguchi Tomoyuki)
14:0014:20L216Deep Learning Prediction Model for Solubility of Nanoparticles From Perspective of Similarity
(TUAT) *(Reg·PCE)Xia Junqing, (Reg)Yamashita Yoshiyuki
Nanoparticle solubility
Deep learning
SY-66677
14:2014:40L217Modeling 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-66457
14:4015:00L218Design 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-66304
(15:00–15:40) (Chair: Yamada Akira)
15:0015:20L219Molecular 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-66140
15:2015:40L220Surrogate 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-66671

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SCEJ 55th Autumn Meeting (Sapporo, 2024)


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