ABSTRACT
After a decade of development, Digital Twins (DT) has been applied to almost all industrial sectors covering different lifecycle phases. Although the benefit of DT is undoubted, it faces challenges when dealing with specific complex industrial systems for advanced intelligent tasks. It requires the integration of multiple relevant DTs corresponding to different system levels and lifecycle phases. The concept of Cognitive Digital Twin (CDT) has been recently proposed, which reveals a promising evolution of the current DT paradigm toward a more intelligent, comprehensive, and full-lifecycle representation of complex systems. Compared to the current DT concept, CDT is enhanced with cognitive and autonomous capabilities. This chapter will first introduce the evolutionary process of the CDT concept; the existing CDT definitions and paradigms will be investigated through a literature review; then the CDT conceptual and implementation architectures will be analyzed; some research and industrial efforts are then summarized, followed by a case study from the aerospace industry; finally, the challenges and opportunities of CDT are discussed in the end.
