Digital Twin Enabled Smart Control Engineering as an Industrial AI: A New Framework and Case Study
Jairo Viola, YangQuan Chen
Abstract
In Industry 4.0, the increasing complexity of industrial systems introduces unknown dynamics that affect the performance of manufacturing processes. Thus, Digital Twin appears as a breaking technology to develop virtual representations of any complex system design, analysis, and behavior prediction tasks to enhance the system understanding via enabling capabilities like real-time analytics, or Smart Control Engineering. In this paper, a novel framework is proposed for the design and implementation of Digital Twin applications to the development of Smart Control Engineering. The framework involve the steps of system documentation, Multidomain Simulation, Behavioral Matching, and real-time monitoring, which is applied to develop the Digital Twin for a real-time vision feedback temperature uniformity control. The obtained results show that Digital Twin is a fundamental part of the transformation into Industry 4.0.