Applied Stochastic Models in Business and Industry has just published a special issue on Digital Twins: A Revolution in Modeling and Simulation, guest edited by Jean-Michel Poggi and Murat Caner Testik.

A Digital Twin (DT) is a virtual representation of a physical system with real-time data integration that can cover the entire lifecycle of the physical system, from design and manufacturing to operation and maintenance. Not very long ago, the DT paradigm started to rapidly transform how we design, develop, and operate products, processes, and systems across a wide range of businesses and industries. Considering its significance and growing interest in various industries and academia, the European Network for Business and Industrial Statistics (ENBIS) organized its 2023 Spring Meeting on DTs in Copenhagen, Denmark (see https://conferences.enbis.org/event/35/). Exploring the studies on the DT technology and its relevance to the industrial statistics, it was decided to edit this special issue of the Applied Stochastic Models in Business and Industry to bring together a collection of cutting-edge research papers on DTs.

The papers in this special issue showcase the latest advancements in the DT studies and implementations, indicating their potential to revolutionize diverse industries. These studies address critical challenges in developing and implementing digital twins and explore the application of DTs in varying domains, including manufacturing, aerospace, construction, and environmental modeling.

Read the special issue here.