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Cognitive Digital Twins

  • Xiaochen Zheng
  • , Jinzhi Lu
  • , Rebeca Arista
  • , Jože Martin Rožanec
  • , Stavros Lounis
  • , Kostas Kalaboukas
  • , Dimitris Kiritsis
  • Swiss Federal Institute of Technology Lausanne
  • Airbus Group
  • Jožef Stefan Institute
  • Athens University of Economics and Business
  • Gruppo Maggioli

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.

Original languageEnglish
Title of host publicationHandbook of Digital Twins
PublisherCRC Press
Pages51-65
Number of pages15
ISBN (Electronic)9781003850809
ISBN (Print)9781032546070
DOIs
StatePublished - 1 Jan 2024
Externally publishedYes

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