ABSTRACT

Industrial digital transformation is enabled by new information and communication technology (ICT) and data-intensive methodologies. Digital twinning is a disruptive technology that creates a living model of industrial assets. The digital twin living model can continually adapt to changes in the environment or operations using real-time sensory data and forecast the future of the physical asset. A digital twin can proactively identify potential issues with its real physical counterpart. It allows the prediction of the remaining useful life of the physical twin by leveraging a combination of physics-based models and data-driven analytics. The digital twin ecosystem comprises sensor and measurement technologies, industrial Internet of Things, simulation and modeling, machine learning, artificial intelligence, and data/information fusion.

The digital twin has varied definitions, and numerous applications have been reported in the literature. A digital twin is often described as a "mirror" to highlight its capability to reflect the real-world entity's properties, behaviors, and performance. However, the "mirror" concept also needs to be defined. This talk will start from the digital twin’s concept and describe the creation and use of digital twin in different applications. Both the industry platforms and case studies will be presented. This talk consists of the following:

·         The concept of digital twin: a look into the mirror

·         Current trends and advances in digital twin technology

·         Creating a digital twin

·         System architecture of a digital twin

·         Digital twin applications and use cases

·         Future directions

·         Q&A and wrap-up

This talk will explore the foundational concepts and emerging frontiers of digital twin technology. Participants will gain a comprehensive understanding of the architectural and operational principles of digital twins. The talk will also introduce data and information fusion strategies in the context of a digital twin ecosystem and prepare participants to effectively apply digital twin technologies across diverse industrial and engineering domains.