Intelligent factory layout design framework through collaboration between optimization, simulation, and digital twin

Seon Han Choi () and Byeong Soo Kim ()
Additional contact information
Seon Han Choi: Ewha Womans University
Byeong Soo Kim: Seoul National University of Science and Technology

Journal of Intelligent Manufacturing, 2025, vol. 36, issue 3, No 2, 1547-1561

Abstract: Abstract In the era of the fourth industrial revolution, various internet and communications technologies (ICTs) are being applied to manufacturing systems. Based on these technologies, many companies utilize smart manufacturing systems to optimize the design and operation of their lines and to diagnose failures. To build and/or improve production lines, various computer-aided engineering (CAE) tools such as optimization solvers and simulation tools for validation are required. In addition, experts depend on their experience or utilize numerous trial and error processes, implying that a large time investment is required obtain the best layout design, without any guarantee that the result is in fact the best. Therefore, the paper proposes an integrated intelligent layout design framework that automatically derives an optimal layout according the requirements of the layout. The proposed framework uses mixed integer linear programming, simulation-based optimization, and digital twin to perform processes such as assembly line balancing, cell/buffer optimization, and layout planning sequentially and repeatedly to derive an optimal layout. By applying this, it is possible to automatically derive the optimal layout design considering limited resources and physical constraints. In addition, it can contribute to improving productivity and work efficiency at manufacturing sites.

Keywords: Assembly line layout; Digital twin; Integer linear programming; Intelligent manufacturing systems; Simulation-based optimization (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-024-02340-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:36:y:2025:i:3:d:10.1007_s10845-024-02340-3

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-024-02340-3

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().