A Unified Digital Twin Approach Incorporating Virtual, Physical, and Prescriptive Analytical Components to Support Adaptive Real-Time Decision-Making

Abstract

The concept of a digital twin, tightly linking the physical and digital world, promises capabilities such as real-time monitoring and optimization of systems. Both in current practice and in the existing literature, the full value of the digital twin has not been realized. Although the ability to mirror, monitor, and interact with systems seems to have been described, the ability to predict and adjust to changing circumstances in real-time is a capability that is not as well refined.Based on an overview of the historical and rapidly expanding literature on digital twins, we identify fundamental capabilities that outline a general and adaptable twin that supports system development, real-time interactions, prescribing courses of action, and actualizing them. We relate these capabilities to business analytics concepts and decision-making processes geared toward rapid adaptation to changing situations. This leads to a general digital twin architecture supporting a system throughout its lifecycle implemented with components including Internet of Things (IoT) devices, a virtual reality environment, network communications, and an analytic simulation. We demonstrate the capabilities through examples, highlighting important timing and synchronization questions critical to fulfilling the twin’s fundamental role of reacting to evolving real-world conditions.

Keywords: Digital twin, Simulation, augmented/virtual reality, real-time decision-making