Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI 2020), p.797 - 801, 2021/07
Ishihara, Masahiro; Saikusa, Akio; Iyoku, Tatsuo; Shiozawa, Shusaku; Ooka, Norikazu; *; *
JAERI-M 93-252, 39 Pages, 1994/01
no abstracts in English
Ishihara, Masahiro; Saikusa, Akio; Iyoku, Tatsuo; Shiozawa, Shusaku; Ooka, Norikazu; *; *; *; *; *
JAERI-M 93-197, 44 Pages, 1993/09
no abstracts in English
Takehisa, Masaaki*; Saito, Toshio*; Takahashi, Toru*; *; Tanaka, Susumu; Agematsu, Takashi; *; *
Cost-benefit Aspects of Food Irradiation Processing; IAEA-SM-328/22, p.243 - 257, 1993/00
no abstracts in English
Takehisa, Masaaki; Machi, Sueo; ; *; *; *; *; *; *; *; et al.
J.Appl.Polym.Sci., 24(3), p.853 - 864, 1979/00
Times Cited Count:5no abstracts in English
Takehisa, Masaaki; *; *; *; *; *; ; *; Machi, Sueo; *; et al.
Dai-8-Kai Nihon Aisotopu Kaigi Hobunshu, A-RC-6, 3 Pages, 1968/00
no abstracts in English
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Ito, Mari*; Suzuki, Masaaki*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Maintenance scheduling is currently manually handled, which is a time-consuming process because of the large number of components and constraints that must be taken into account when creating a schedule. Besides, to develop next-generation power plants with excellent operability, it is necessary to make it possible to evaluate operability and maintainability in advance at the design stage. Our objective is to develop and implement an automatic scheduling system using the mathematical technique of Operations Research for addressing the inspection process scheduling problem in a sodium-cooled fast reactor plant. This study constructs a scheduling model that performs optimization in two stages to reduce the computation costs.
Ito, Mari*; Suzuki, Masaaki*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
To realize the reasonable and effective maintenance of nuclear power plants, it is essential to optimize the aging management from the viewpoints of both safety and efficiency. However, maintenance scheduling is currently manually handled, which is a time-consuming process because of the large number of components and constraints that must be taken into account when creating a schedule. Besides, there is plenty of room for improvement in the schedules because most of the maintenance requirements are manually checked. This study is to develop an automatic optimization scheduling system using the mathematical technique for addressing the inspection-process-scheduling problem in a sodium-cooled fast reactor plant.
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
Maintenance scheduling is typically performed manually, which is a time- and resource-consuming process due to the many components and constraints that must be considered. Besides, to develop next-generation power plants with excellent operability, it is necessary to make it possible to evaluate maintainability in advance at the design stage. Thus, this paper proposes a maintenance-scheduling model based on swarm intelligence to develop an automatic scheduling system for addressing the inspection process scheduling problem in a SFR plant.
Suzuki, Masaaki*; Ito, Mari*; Hashidate, Ryuta; Takahashi, Keita; Yada, Hiroki; Takaya, Shigeru
no journal, ,
In order to achieve a smooth operation that balances safety and economic viability in next-generation reactors, it is essential to implement a design that considers maintenance. Currently, there is a lack of technology to repeatedly assess operability during the pre-construction phase and identify design aspects that pose challenges to maintenance, creating a bottleneck in the process. This study employs swarm intelligence techniques to learn and analyze inspection process schedules that satisfy various constraints in sodium-cooled fast reactors.