Digital twin simulation for operational decision making

Simulation models are commonly used as part of system design or management projects and are only now beginning to appear as part of operational control systems. When used to solve problems in real time, simulation models are typically described as being, or forming part of, a digital twin. Using a simulation model as part of a digital twin enables testing of different strategies or system settings based on the current state of the system. For this to be effective, results need to be returned quickly, requiring efficient algorithms for simulation optimization and effective use of data analytics and machine learning methods to complement the simulation modelling. Beginning with a discussion of digital twin models in the context of process simulation, we cover some of the key concepts that enable digital twins to support real-time decision-making, including metamodelling, multi-fidelity simulation optimization and simulation analytics.