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Material Database for Efficient Development Using Materials Informatics

Article of Honda R&D Technical Review Vol.32 No.2

Summary

A comprehensive material database that enables the storage, management and export of material data and related information in a standardized format has been constructed to promote the use of materials informatics to achieve highly efficient materials research, such as the application of information science to predict physical properties in order to reduce experimental trial and error.
Usability and user differences such as expertise were taken into account when selecting the database tools and creating the internal structure. As a result, storage of around 10,000 test data and standard properties in various material fields has been completed.
It was confirmed that this enables a reduction in the work time required for data cleansing, which is an issue for use of materials informatics. It also facilitates the acquisition of data needed for design and CAE, etc., and helps to increase operations efficiency and reduce development costs.

Reference

(1) Imanishi, T., Asami, A., Saneyoshi, Y.: Large-sized and Lightweight Aluminum Hollow Diecast Subframe Using High Pressure Diecasting, Honda R&D Technical Review, Vol. 29, No. 1, p. 46-51
(2) Yamane, Y., Sakuraba, T.: Development of Lightweight CFRP Hood and Rear Spoiler, Honda R&D Technical Review, Vol. 15, No. 1, p. 209-214
(3) Washizu, K., Takeishi, I., Sato, N., Ogishi, H., Tabata, M.: Development of High-pressure Diecast Magnesium Intake Manifold, Honda R&D Technical Review, Vol. 17, No. 2, p. 32-37
(4) Asanuma, M., Endo, T., Sakai, H.: Introduction of Heat Exchanger Production Technique for Stirling Engine Using Additive Manufacturing, Honda R&D Technical Review, Vol. 28, No. 1, p. 174-182
(5) Furukawa, A., Ikeda, T., Okayama, T.: Materials Research Method using Smart Materials Informatics, Honda R&D Technical Review, Vol. 29, No. 1, p. 90-97
(6) https://findy-code.io/engineer-lab/machine-learning-tough-work
(7) Norio, S.: Education and Human Resource Development of Machine Learning in Toyota Motor Kyushu, Journal of the Japanese society for quality control, Vol. 49, No. 2, p. 160-164, (2019) (In Japanese)
(8) Metallic Materials Properties Development and Standardization (MMPDS), 14th Edition, Federal Aviation Administration, p. 2535, (2019)
(9) https://www.totalmateria.com/

Author (organization or company)

Tsuyoshi ITO(Honda Motor Co., Ltd.)、Satoko ISHII(Honda Motor Co., Ltd.)、Hiroshi HONDA(Honda Motor Co., Ltd.)、Nao SUGIMOTO(Honda Motor Co., Ltd.)、Yoichi TOYOOKA(Honda Motor Co., Ltd.)、Toru FURUSAWA(Honda Motor Co., Ltd.)

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