Digital twins for manufacturing and logistics systems: is simulation practice ready?

  • Francesco Longo 
  • Antonio Padovano, 
  • Letizia Nicoletti, 
  • Mohaiad Elbasheer, 
  • Rafael Diaz
  • a,b DIMEG, University of Calabria, Ponte Pietro Bucci, Cubo 45C, Third Floor, Arcavacata di Rende (CS), 87036, Italy
  • CAL-TEK S.r.l., Rende (CS) 87036, Italy
  • Modeling & Simulation Center – Laboratory of Enterprise Solutions (MSC-LES), University of Calabria, Ponte Pietro Bucci, Arcavacata di Rende (CS), 87036, Italy
  • Old Dominion University, 5115 Hampton Boulevard Norfolk, VA 23529, United States of America
Cite as
Longo F., Padovano A., Nicoletti L., Elbasheer M., Diaz R. (2021). Digital twins for manufacturing and logistics systems: is simulation practice ready?. Proceedings of the 33rd European Modeling & Simulation Symposium (EMSS 2021), pp. 435-442. DOI:


This article provides a theoretical contribution to the state-of-the-art of digital twins for manufacturing and logistics systems. The primary goal of this paper is to draw attention to the gap between the theoretical framework of digital twins in manufacturing and supply chain and their practical implementation from a simulation modeling point of view. Therefore, highlighting the recent innovations in the simulation practice that could provide the basis for digital twins with high levels of data integration, automation, and smart capabilities. This study follows a comparative approach to analyzing theoretical and technical readiness for developing digital twins with high fidelity and computational power. The methodology is based on a benchmarking analysis that aims to identify the current sate of the art from a theoretical and a practical standpoint.


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