Digital twins for decision making in complex production and logistic enterprises

Abstract

The operation and optimization of complex production and logistic enterprises requires modern, data and simulation driven multi criteria decision approaches. Digital enterprise systems are complex systems, in terms of layout variability, control strategies, business processes and system parameter. All of these aspects are not independent and even due to the system dynamics the optimal solution may differ depending on the actual situation applying specific requirements. In order to improve operative decision making in production and logistic enterprises a digital twin concept can be applied. These digital twins are virtual clones of real systems or subsystems. With simulation and artificial intelligence technologies new opportunities for operative decision making are possible. Digital twins can cover the entire lifecycle of an asset or process by forming a closed-loop chain for smart, connected products, services and production and logistic processes, from design to operation, from deployment to continuous improvement.