適用 - Program search result - SCEJ 88th Annual Meeting (Tokyo, 2023)

`SCEJ 88th Annual Meeting (Tokyo, 2023)`

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Program search result : 適用 : 6 programs

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.

Title (J) field includes “適用”; 6 programs are found.
The search results are sorted by the start time.

Time	Paper ID	Title / Authors	Keywords	Topic code	Ack. number
Day 1 13:20– 14:20	PA143	Development of dispersant for ceramic fine particles having the effect of high dispersion and viscosity reduction for application to electric components (Miyoshi Oil & Fat) *(Reg)Takamatsu Yuichiro, Tanaka Shuya, Terada Kazuhiro, Kawai Koji	dispersant viscosity reduction electric components	12-a	623
Day 1 16:00– 16:20	I122	Application of stiction compensation method for control valves to an actual process (ENEOS) *(Reg)Daiguji Masaharu, (TUAT) (Reg)Yamashita Yoshiyuki	process control optimization	6-d	699
Day 2 10:20– 10:40	I205	Proposal of a method to improve the performance of MSPC by appropriate standardization of input variables and its application to continuous pharmaceutical manufacturing (Powrex/TUAT) *(Reg)Oishi Takuya, (Powrex) (Reg)Nagato Takuya, (TUAT) (Reg)Kim Sanghong	Multivariate Statistical Process Control Continuous Pharmaceutical Manufacturing Wet Granulation	6-d	68
Day 2 13:25– 13:45	A214	[The SCEJ Award for Outstanding Young Engineer] Applications of practical process modeling based on statistics, multivariate analysis, and simulation in pharmaceutical development (Daiichi Sankyo) (Reg)Tanabe Shuichi	The SCEJ Award for Outstanding Young Engineer	0-e	778
Day 2 14:20– 15:20	PC224	Application of mixer-type freeze-dryers to ceramic powders by spray-freeze granulation. (Kobelco Eco-Solutions) *(Cor)Kishi Yusuke, (Cor)Ogawa Tomohiro, (Reg)Maeseto Tomoharu, (PRECI) (Reg)Kawaguchi Shinya	freeze dry lyophilization mixer type	2-f	663
Day 2 14:20– 15:20	PC230	Application of machine learning and physical modeling for detecting hydrogen leakage from hydrogen pipeline (Yokohama Nat. U.) *(Stu)Suzuki Yuki, Suzuki Tomoya, Nakayama Jo, (NEC) Soma Tomoya, (Yokohama Nat. U.) (Reg)Izato Yuichiro, (Reg)Miyake Atsumi	hydrogen pipeline leak detection machine learning	10-e	269

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SCEJ 88th Annual Meeting (Tokyo, 2023)

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