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IJAT Vol.14 No.5 pp. 700-712
doi: 10.20965/ijat.2020.p0700
(2020)

Paper:

Digital Twin of Artifact Systems: Models Assimilated with Monitoring Data from Material Microstructures to Social Systems

Taira Okita*,†, Tomoya Kawabata*, Hideaki Murayama**, Nariaki Nishino*, and Masaatsu Aichi**

*School of Engineering, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Corresponding author

**Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan

Received:
March 25, 2020
Accepted:
July 13, 2020
Published:
September 5, 2020
Keywords:
multiscale modelling, inspection, adaptive development, service, co-creation
Abstract

In contemporary society, where changes in the environment surrounding artifacts as well as changes in the purpose and operating conditions of artifacts occur frequently, it is necessary to equip artifacts with resilience and plasticity, and to incorporate this knowledge in the succeeding generation of artifacts. For this purpose, we propose digital twin of artifact systems (DTAS) that focuses on structural materials, from their microstructure to the environment and social systems in which the artifacts are used. The realization of DTAS requires the development of modelling and monitoring technologies from the atomic scale to the social system, the development of technologies to operate these technologies in multiscale in an integrated way, and the development of technologies for model uncertainty assessment. In the future, the information on models and monitoring of artifact systems stored in DTAS is expected to be shared and utilized not only by designers but also among various stakeholders, contributing to the realization of a framework for co-creative development and consensus building through interaction between designers and users.

Cite this article as:
T. Okita, T. Kawabata, H. Murayama, N. Nishino, and M. Aichi, “Digital Twin of Artifact Systems: Models Assimilated with Monitoring Data from Material Microstructures to Social Systems,” Int. J. Automation Technol., Vol.14, No.5, pp. 700-712, 2020.
Data files:
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