Bibliographic Details
| Title: |
ATTACHABLE IOT-BASED DIGITAL TWIN FRAMEWORK SPECIALIZED FOR SME PRODUCTION LINES. |
| Authors: |
Kang, B. G.1 bgkang@kitech.re.kr, Kim, B. S.2 bskim@seoultech.ac.kr |
| Source: |
International Journal of Simulation Modelling (IJSIMM). Sep2024, Vol. 23 Issue 3, p471-482. 12p. |
| Subject Terms: |
*MACHINE learning, *DIGITAL twin, *DIGITAL transformation, *SMALL business, *ECONOMIC uncertainty |
| Abstract: |
While large enterprises are actively preparing for digital transformation by leveraging technologies such as digital twins, smaller companies face challenges due to economic constraints and market uncertainties, leading to a relative lack of awareness and readiness. To address this situation, this study proposes a digital twin development framework tailored for small and medium-sized enterprises (SMEs). This framework utilizes attachable IoT devices for real-time collection of manufacturing data and leverages public server systems for data management. Moreover, it enables the refinement and optimization of digital twins by training machine learning models on collected data. Additionally, the framework includes the integration of simulation models and machine learning models for comprehensive digital twin modelling. Finally, the paper suggests a process for applying and validating this framework in real manufacturing companies, demonstrating the effects of digital twin implementation on productivity enhancement in the production lines of two SMEs. [ABSTRACT FROM AUTHOR] |
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| Database: |
Academic Search Complete |
