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Reseacher

Name SAITO Aya
Official Title Professor
Affiliation Faculty Of Design And Data Science
E-mail asaito@tcu.ac.jp
Web
  1. https://www.risys.gl.tcu.ac.jp/Main.php?action=profile&type=detail&tchCd=1005110000
Profile My area of expertise is Industrial Engineering, in particular the improvement and design of factory layouts and production processes.
A production system is a system that integrates people, products, money, and information. The scope of the design and operation of these production systems is expanding as globalization progresses. In addition, the speed of change has greatly increased due to advances in ICT technology. I am working on the development of methodology for designing and improving production systems corresponding to this.
What I place particular emphasis on is knowing what is actually happening in the field. As analysis technology becomes more sophisticated, it is easy to fall into modeling to solve problems, and it is often seen that there is a gap between the solution of real problems and the solution of problems. In order to avoid this, I place importance on always incorporating the latest on-site information.
I am also focusing on developing educational programs to spread industrial engineering. The reality is that small and medium-sized enterprises do not have a system in place to conduct IE education on their own. On the other hand, companies tend to rely on their own methodologies. We organize them and develop educational programs that contribute to improving the improvement capabilities of small and medium-sized enterprises.
Research Field(Keyword & Summary)
  1. (1)Development of educational programs for popularization of Industrial Engineering

    Develop on-demand teaching materials for training human resources who can practice industrial engineering in companies.

  2. (2)Efficiency of order picking work considering the physical characteristics of elderly and female workers

    Measure and quantify differences in stress caused by differences in the physical characteristics of workers such as the elderly and women. The next step is to analyze the work motions at actual logistics sites and identify the motions that cause high stress and the flow of those motions. Appropriate job design is performed by improving the identified high-stress work.
Representative Papers
  1. (1)Hideyuki OZAWA, Yosuke MITSUSADA,Aya SAITO,"Measurement of Corporate Attitude Using Alternative Data and Its Application to　Corporate Analysis: Quantification of Corporate Attitude Toward Advanced Technologies　such as AI and Analysis of Characteristics Possessed by Groups of Companies",System Design Society of Japan,Vol.2, No.2 (2022/2)
  2. (2)Kazuho YOSHIMOTO,Aya SAITO,etc."A Thionic for Service Visualization",The Journal of The Institute of Electronics,Information and Communication Engineers,Vol.96,No.8(2013/8)
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS) https://nrid.nii.ac.jp/ja/nrid/1000000218835/
Recruitment of research assistant(s) No
Affiliated academic society (Membership type) JIMA (member)
Education Field (Undergraduate level) Industrial Engineering
Education Field (Graduate level) Industrial Engineering

Affiliation