Digital twins for electro-physical, chemical, and photonic processes

Yuebin Guo, Andreas Klink, Paulo Bartolo, Weihong Grace Guo

Research output: Contribution to journalArticlepeer-review

Abstract

Manufacturing processes are becoming increasingly data-driven. Integrating manufacturing data and process models in real-time, a digital twin (DT) may function as an autonomous and dynamic digital replica. This, in turn, may enable manufacturers to not only understand and monitor a process but also proactively control it in real-time or a product over its life cycle. This paper examines the DT concept and its evolution and presents a future DT framework. DTs’ key components (e.g., process models) and implementation are focused on additive manufacturing, electrical discharge machining, and electrochemical machining. Furthermore, current challenges and future research directions are summarized.

Original languageAmerican English
Pages (from-to)593-619
Number of pages27
JournalCIRP Annals
Volume72
Issue number2
DOIs
StatePublished - Jan 2023

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Keywords

  • Digital twin
  • Industry 4.0
  • Manufacturing process

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