Establishing a reliable mechanism model of the digital twin machining system: An adaptive evaluation network approach

Shimin Liu, Yicheng Sun, Pai Zheng (Corresponding Author), Yuqian Lu, Jinsong Bao (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Digital twin technology can build virtual replicas of physical entities to observe, analyze, and control the machining process. The virtual model always simplifies the physical entity as limited by the current technical level, so that the digital twin model cannot fully reflect the physical entity with high-fidelity, leading to a particular error rate in the prediction and decision-making. Such systematic decision-making lacks enough reliability, which could mislead decision-makers and even lead to irreparable losses. To overcome this challenge, this paper constructs an adaptive evaluation network for the digital twin machining system (DTMS), where the decision-making error on the process route is formed into the network to evaluate its reliability. Finally, the feasibility of the proposed method is verified by the reliability evaluation on the DTMS of an aerospace part's machining process.

Original languageEnglish
Pages (from-to)390-401
Number of pages12
JournalJournal of Manufacturing Systems
Volume62
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Adaptive evaluation network
  • Digital twin
  • Machining system
  • Mechanism model
  • System reliability evaluation

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Hardware and Architecture
  • Industrial and Manufacturing Engineering

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