Vol. 18, No. 8, August 31, 2024
10.3837/tiis.2024.08.019,
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Abstract
The current automotive industry is transitioning from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs), adopting a mixed assembly production approach to respond to fluctuating demand. While mixed assembly production offers the advantages of lower investment costs and flexibility in responding to changing demands, the supply of EV components requires more extensive provisioning compared to ICE vehicle components, potentially leading to unexpected issues such as congestion of transport vehicles. This study proposes a digital twin system architecture that uses Discrete Event Simulation (DES) and Business Intelligence (BI) tools to specifically address logistics challenges. The proposed architecture facilitates real-time, data-driven decision making across three layers; Data source, Simulation, and BI. It was implemented in factories engaged in the mixed assembly production of ICE and EV vehicles. The simulation challenges involve a tier 1 vendor supplying parts to Korean automobile manufacturers that produce both ICE and EV parts. A total of 240 scenarios were created to run the simulations. The deployment of the proposed architecture demonstrates its capability to quickly respond to diverse experimental situations and promptly identify potential issues.
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Cite this article
[IEEE Style]
G. Hwang, J. Han, H. Kim, "A Digital Twin Architecture for Automotive Logistics– An Industry Case Study," KSII Transactions on Internet and Information Systems, vol. 18, no. 8, pp. 2399-2416, 2024. DOI: 10.3837/tiis.2024.08.019.
[ACM Style]
Gyusun Hwang, Jun-hee Han, and Haejoong Kim. 2024. A Digital Twin Architecture for Automotive Logistics– An Industry Case Study. KSII Transactions on Internet and Information Systems, 18, 8, (2024), 2399-2416. DOI: 10.3837/tiis.2024.08.019.
[BibTeX Style]
@article{tiis:101107, title="A Digital Twin Architecture for Automotive Logistics– An Industry Case Study", author="Gyusun Hwang and Jun-hee Han and Haejoong Kim and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2024.08.019}, volume={18}, number={8}, year="2024", month={August}, pages={2399-2416}}