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A Bidirectional Digital Twin System for Adaptive Manufacturing

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Vydáno v:Journal of Manufacturing and Materials Processing vol. 9, no. 12 (2025), p. 400-423
Hlavní autor: Heide, Klaas Maximilian
Další autoři: Denkena Berend, Winkler, Martin
Vydáno:
MDPI AG
Témata:
Accuracy
Data exchange
Adaptability
Quality control
Closed loops
Machine tools
Predictive control
Data processing
Aerospace industry
Production planning
Manufacturing
Monitoring
Turbines
Simulation
Adaptive systems
Physics
Artificial intelligence
Digital twins
Milling (machining)
Sensors
Decision making
Orthopaedic implants
Process controls
Cycle time
Anomalies
Feed rate
Machining centres
Real time
Industry 4.0
Feedback control
Orthopedics
Run time (computers)
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Abstrakt:Digital Twin Systems (DTSs) are increasingly recognized as enablers of data-driven manufacturing, yet many implementations remain limited to monitoring or visualization without closed-loop control. This study presents a fully integrated DTS for CNC milling that emphasizes real-time bidirectional coupling between a real machine and a virtual counterpart as well as the use of machine-native signals. The architecture comprises a physical space defined by a five-axis machining center, a virtual space implemented via a dexel-based technological simulation environment, and a digital thread for continuous data exchange between those. A full-factorial simulation study investigated the influence of dexel density and cycle time on engagement accuracy and runtime, yielding an optimal configuration that minimizes discretization errors while maintaining real-time feasibility. Latency measurements confirmed a mean response time of 34.2 ms, supporting process-parallel decision-making. Two application scenarios in orthopedic implant milling validated the DTS: process force monitoring enabled an automatic machine halt within 28 ms of anomaly detection, while adaptive feed rate control reduced predicted form error by 20 µm. These findings demonstrate that the DTS extends beyond passive monitoring by actively intervening in machining processes; enhancing process reliability and part quality; and establishing a foundation for scalable, interpretable digital twins in regulated manufacturing.
ISSN:2504-4494
DOI:10.3390/jmmp9120400
Zdroj:ABI/INFORM Global