Digital Twins for Embedded, Edge, and Cloud Platforms

In today’s world of the next industrial revolution, many key industry players are forced to change their conventional process and practices. To join this major transformation, usually referred to as Industry 4.0, they must pursue extensive R&D efforts in developing cyber-physical systems.

A digital twin concept as a part of Industry 4.0 strategy can offer answers for these challenges by integrating and deploying different variants of digital twins (production, product, and performance) of the physical assets on various systems such as embedded, edge, and cloud platforms.

This talk will discuss the development of a gas turbine performance digital twin using tools such as Simulink Real-Time™ and Simulink PLC Coder™. The performance digital twin utilizes real-time high-speed computing and can be leveraged with various enterprise and IoT cloud platforms. Proposed solutions are provided in a form of modular software architecture for a range of hardware platforms with corresponding functionalities to support model-based control strategies and advanced asset health management.

This project explored novel advanced techniques, which can meet the challenging requirements of increased reliability, improved efficiency, and extended operational life of gas turbine assets. The digital twin, based on real-time dynamic engine models, has emerged as the most viable approach for solving challenging control and diagnostics requirements.

The real-time, online digital twin technology has the ability to enhance current state-of-the-art offerings which are predominantly based on non-real time and offline solutions. The devised solution highlights the next generation of digital twins that exploit modular functionalities distributed across the whole IoT chain consisting of embedded, edge, and cloud computational platforms. The gas turbine performance digital twin has been deployed on the operational site, and collected field data have been analyzed and presented in this study.