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SCEJ 88th Annual Meeting (Tokyo, 2023)

Last modified: 2023-12-13 19:12:50

Session programs : SS-7

The preprints(abstracts) are now open (Mar. 1st). These can be viewed by clicking the Paper IDs. The ID/PW sent to the Registered participants in Period I/II and invited persons are required.

SS-7 Efforts to Utilize DX (Digital Transformation) to Create Vibrant and Sustainable On-Site Capabilities (Poster)

Organizer: Sawada Yuko (SCEJ)

Towards the realization of sustainable society, various research and development is being carried out. Among them, ammonia in particular is being studied as hydrogen carrier and carbon-free fuel. This session will focus on the utilization of ammonia, and introduce the latest trends and research cases.

Hall Q, Day 3

TimePaper
ID
Title / AuthorsKeywordsTopic codeAck.
number
Hall Q(Gymnasium), Day 3(Mar. 17)
(16:00–17:30) (Chair: Kawase Susumu)
16:0017:30Q301[Invited lecture] Smart factory for chemical manufacturers
(JMA Consultants) Kamiyama Yosuke
Smart factory
Practical theory
Case study
SS-7322
Q302[Requested talk] Data Utilization Activity for DX of Production Field and AI Platform
(Kaneka) *(Cor)Kinaka Shingo, *(Cor)Ichiriki Hiroaki
DX
Data Utilization
AI Platform
SS-7324
Q303[Invited lecture] Salesforce reference case for Cx including Quality Management / Blockchain reference case for refrigerant circulation platform
(IBM Japan) *Miyabe Naoki, *Saegusa Kenichiro
Saleseforce
Blockchain
DX
SS-7329
Q304[Requested talk] In Oil and Chemical industries, the damage mechanisms prediction of facilities from the chemical environments by user development of AI machine learning
(Facility Eng. Laboratory) (Reg)Matsuda Hiroyasu
AI
Decision Tree
Damage Mechanism Prediction
SS-7338
Q305[Invited lecture] Energy-saving operation by AI autonomous control
(Yokogawa Digital) Kobuchi Keiichiro
AI control
Reinforcement learning
Energy-saving
SS-7345
Q306[Requested talk] Practical use of digital technology at chemical plant
(Sumitomo Chemical) (Reg)Hiraishi Yasuaki
chemical plant
digital transformation
machine learning
SS-7348
Q307Inverse design of functional separation materials using deep generation models.
(Kogakuin U.) *(Stu)Matsumoto Takumi, (Reg)Miyagawa Masaya, (Reg)Takaba Hiromitsu
machine learning
polymer membrane
gas separation
SS-7357
Q308[Requested talk] Introduction of AI support for overall plant operation including optimization and anomaly detection
(Chiyoda) *(Cor)Sato Hideki, (Cor)Ogawa Rentaro, (Cor)Furuichi Kazuya
AI
anomaly detection
operation improvement
SS-7369
Q309[Requested talk] Recommendation of diagnosis of heating medium boilers and equipment using heat medium
(Soken Tecnix) *(Cor)Matsuoka Daisuke, (Cor)Sakashita Ryuji
diagnosis
maintenance
inspection
SS-7373
Q310[Invited lecture] Utilizing Robotics for "Smart Inspection/DX" of Factories, Plants, etc.
(Blue innovation) Hirabaru Sho, *Yamaguchi Yudai
drone
robotics
digital transformation
SS-7376
Q311[Invited lecture] Inventory reduction through color mixing using CCM
(Dainichiseika Color & Chemicals) Maeda Satoshi
CCM
colormixing
inventory
SS-7382
Q312[Requested talk] Online Trainings on Process Safety Triggered by COVID-19
(SCE惻Net) *(Reg)Ushiyama Satoshi, (Reg)Takeuchi Ryo
On-line
Training
Process Safety
SS-7383
Q313[Requested talk] Improvement of on-site capabilities through digitalization of production technology and improvement of productivity through autonomous control of processes
(Sumitomo Bakelite) (Cor)Tanaka Go
Production engineering AI IoT
Gemba-ryoku kaizen(Field capabilities improvement)
Productivity improvement
SS-7388
Q314[Invited lecture] AI use cases in predictive maintenance that have entered the practical stage
(Brains Tech.) Hayashi Takuma
AI
Machine Learning
Predictive Maintenance
SS-7393
Q315[Requested talk] Eco-friendly semiconductor cleaning technology using ozone water
(Ecodesign) *Nagakura Masaya, Saito Junichiro, Yamaguchi Daisuke, Sakamoto Yukiko
Semiconductor Cleaning
SS-7396

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SCEJ 88th Annual Meeting (Tokyo, 2023)


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