Identifying and characterising uncertainty in digital twin engineering

Digital twin technologies are increasingly deployed in complex industrial systemswhere uncertainty management is critical to ensure their reliability, robustness, andresilience. However, there is currently limited literature on the management of uncer-tainties for digital twins, and even less a structured framework for a better under-standing of the uncertainties, focusing on the identification and characterisation ofuncertainties within the context of digital twin engineering. In this work, a conceptualframework is proposed, structured around three key pillars: a conceptual model, a life-cycle, and maturity levels of the digital twin. A systematic literature review, followingthe PRISMA methodology, is conducted to identify and map four major categories ofuncertainty across these pillars. The findings show how uncertainty types correspondto the 5D conceptual model of the digital twin, at which lifecycle stages they becomemost critical, and how they evolve as the digital twin progresses towards highermaturity levels. The proposed framework positions uncertainty characterisation as acore engineering principle of digital twins, paving the way for future research onstructuring uncertainty management across digital twin engineering practices.