Year: 2026
Type: article
Abstract: The rapid development of digital twin technology has created new opportunities for modelling and optimisation of complex manufacturing systems.However, most existing studies treat digital twins primarily as simulation tools and seldom address emergent behaviour arising from subsystem interactions.Emergence is a fundamental property of complex systems in which global behaviour cannot be reduced to the sum of individual component behaviours.This article proposes a mathematical framework for analysing emergent behaviour in digital twins of manufacturing systems.The digital twin is modelled as a dynamic network of interacting subsystems described by a system of differential equations.An entropy-based emergence index is introduced to quantify collective complexity.Two stability theorems and one optimality theorem are formally proved.A variational Principle of Minimum Emergent Complexity is formulated, linking information-theoretic complexity directly to manufacturing efficiency.Numerical simulations with four scientific figures confirm the theoretical predictions.The proposed formalisation provides a foundation for intelligent control in Industry 5.0 environments.
Author: Sergiy Kovalevskyy
Institution: Donbass State Engineering Academy
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7203837280