Smart Warehouse Management Using Digital Twins and Machine Learning
DOI:
https://doi.org/10.7166/37-1-3254Abstract
In warehouse operations, digital twin technology integrates physical systems with software components, thereby improving overall productivity. In this study, we developed a digital twin system using the R programming language to analyse product demand patterns and support the slotting storage configuration of outbound processes in a warehouse. By integrating radio-frequency identification (RFID) tag data with Flexsim simulations, the system enhances productivity tracking by 42% – measured by the number of pallets processed per hour – and reduces the time required for dispatching products in the distribution centre by 41%.
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Published
2026-05-22
How to Cite
Taquía Gutiérrez, J., & Machuca de Pina, . J. (2026). Smart Warehouse Management Using Digital Twins and Machine Learning. The South African Journal of Industrial Engineering, 37(1), 17–27. https://doi.org/10.7166/37-1-3254
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