Digital Twin Technology: A Review and Its Application Model for Prognostics and Health Management of Microelectronics

Adwait Inamdar*, Willem Dirk van Driel, Guoqi Zhang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Digital Twins (DT) play a key role in Industry 4.0 applications, and the technology is in the process of being mature. Since its conceptualisation, it has been heavily contextualised and often misinterpreted as being merely a virtual model. Thus, it is crucial to define it clearly and have a deeper understanding of its architecture, workflow, and implementation scales. This paper reviews the notion of a Digital Twin represented in the literature and analyses different kinds of descriptions, including several definitions and architectural models. A new fit-for-all definition is proposed which describes the underlying technology without being context-specific and also overcomes the pitfalls of the existing generalised definitions. In addition, the existing three-dimensional and five-dimensional models of the DT architecture and their characteristic features are analysed. A new simplified two-branched model of DT is introduced, which retains a clear separation between the real and virtual spaces and outlines the latter based on the two key modelling approaches. This model is then extended for condition monitoring of electronic components and systems, and a hybrid approach to Prognostics and Health Management (PHM) is further elaborated on. The proposed framework, enabled by the two-branched Digital Twin model, combines the physics-of-degradation and data-driven approaches and empowers the next generation of reliability assessment methods. Finally, the benefits, challenges, and outlook of the proposed approach are also discussed.
Original languageEnglish
Article number3255
Number of pages21
JournalElectronics (Switzerland)
Volume13
Issue number16
DOIs
Publication statusPublished - 2024

Keywords

  • Digital Twin
  • Industry 4.0
  • microelectronics reliability
  • physics of degradation
  • material modelling
  • multi-physics simulation
  • data-driven model
  • condition monitoring
  • hybrid PHM

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