A Novel Embedding Model Based on a Transition System for Building Industry-Collaborative Digital Twin

  • Minyeol Yang
  • , Junhyung Moon
  • , Jongpil Jeong
  • , Seokho Sin
  • , Jimin Kim

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Recently, the production environment has been rapidly changing, and accordingly, correct mid term and short term decision-making for production is considered more important. Reliable indicators are required for correct decision-making, and the manufacturing cycle time plays an important role in manufacturing. A method using digital twin technology is being studied to implement accurate prediction, and an approach utilizing process discovery was recently proposed. This paper proposes a digital twin discovery framework using process transition technology. The generated digital twin will unearth its characteristics in the event log. The proposed method was applied to actual manufacturing data, and the experimental results demonstrate that the proposed method is effective at discovering digital twins.

Original languageEnglish
Article number553
JournalApplied Sciences (Switzerland)
Volume12
Issue number2
DOIs
StatePublished - 1 Jan 2022

Keywords

  • Digital twin
  • GRU
  • Manufacturing process
  • Process mining
  • Process prediction

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